Interdisciplinary Computing Blog

Computer Aided Composition & Hallucinations

2012-01-25T22:35:00.000-08:00

The term "algorithmic composition" is loaded with baggage. Although the phrase pops up in our conversation fairly often, because of the loaded nature of the words, Alexis Kirke prefers "Computer Aided Composition" to describe the process he uses to compose music.

Although perfectly capable of coding, and having done so in the past, Alexis now prefers to work collaboratively with a professional programmer so that he can focus on the overall composition. "Programming is a creative act in itself" and it is all too easy to get sucked into it, he explains. Listening to Alexis describe how he is developing Insight, I couldn't help but think of a Vulcan Mind Meld. Alexis desires to "share the unsharable" - his consciousness, internal feelings, his Palinopsia hallucinations. (See the previous post for more on Alexis and how Palinopsia inspired this particular body of work)

According to the current plan, if you are in the audience at the February 10th performance you will see Alexis standing on stage behind a music stand holding an iPad. Perhaps he will be holding a pen. A Macintosh laptop is within arm's reach. The programmer sits in the front row of seats, and there is a flute player somewhere on stage with his own computer monitor. Alexis sees you; he also sees lighting designed to trigger his hallucinations.

It is difficult to formulate words to describe what this application program will probably look like, but I'm going to give it a whirl. The iPad will show Alexis a camera image of what he is seeing at any moment, an "augmented reality". The software on the iPad will incorporate parameters that correspond to common elements of Alexis' hallucinations. As Alexis experiences hallucinations, he will activate afterimage functionality and trigger an afterimage on the iPad. (At this point, a poor video connection on our Skype call produced a well timed "trail" as Alexis moved his hand across my line of sight). When this happens he is presented with visual options, filters and parameters. These are produced in partial response to an iterative feedback loop between himself and the programmer: he selects, via multi-touch, tapping, double tapping, 3 fingered presses, which parameters are appropriate and what filters to apply. For example, he can adjust the iPad screen brightness to correspond to his perception of brightness. He can likewise adjust screen size, the specific pattern of an afterimage, the rate of visual decay, single or multiple images, random patterns, and many other aspects of the visual echo. Alexis is simultaneously saying "yes, that" "no, not that" to presented options, and creating from scratch on the fly what he sees. He has to make the iPad "see" what he sees.

All this is happening extremely rapidly as his hallucinations develop, exist, and are replaced (sometimes in milliseconds) with the next hallucination. And we must not forget that this is not a completely free form activity - there will be at least 3 sections to the composition. Each section of the piece has different parameters. Alexis will reach over to the laptop to change sections. All of the visuals are handled by the iPad. When a hallucination is accurate, it is packaged up and sent wirelessly to the laptop, where the music resides. One reason for this division of labor is that the visual software is processor intensive. Memory optimization has been critical, and Alexis brought in someone who focused exclusively on iPad memory optimization.

Somehow, it all gets put together and coordinated: visual hallucinations from the iPad, musical scores from the laptop, contribution from a live flute player watching the iPad output.

You, sitting in the audience would see Alexis' hallucinations projected on a large screen, and hear his musical score to go along with it. All in 12 minutes.

The performance of Insight, at the Peninsula Arts Contemporary Music Festival, is going to be filmed. Let's hope it becomes available online!

Computing...Music...Palinopsia

2012-01-22T14:23:00.000-08:00

What would you do if, under the right circumstances, you saw hallucinations (no drugs involved)? If your name was Alexis Kirke you would take your two PhDs (one in arts, one in technology) and create a professional demonstration to share with the public.

I had no idea what to expect when, prior to our conversation, I read about Alexis and learned we were going to talk about his upcoming performance that would share live visual hallucinations. Who is this guy, I wondered?

Alexis Kirke is a member of Plymouth University's (UK) Interdisciplinary Centre for Computer Music Research, and Composer in Residence at the Plymouth Marine Institute. As part of his latter role, he has composed a score for a performance of "artificially intelligent whales" interacting with a saxophone. Impossible to describe; you just have to go here and expose yourself to it. Then there are other performances with titles such as: "Phrased and Confused" and "Drum Abuse". What next?

Afterimages. Ever look straight at a lightbulb and then been half blinded with the image of the bulb well after you stop looking at it? That is an afterimage. Afterimages come in two types, positive and negative. Positive afterimages are the same color as the original image and thought (according to my brief research) to have a neurological origin. An often cited example of positive afterimages are the "trails" associated with use of LSD. Conversely, negative afterimages invert the colors and are thought to have an optical/retinal origin.

Alexis has Palinopsia, a neurological condition that produces (most often positive) afterimages. What this means to Alexis is that when he is extremely tired, stressed, or in just the right lighting conditions, he will start to see afterimages. No drugs involved. He describes it as unnerving sometimes, but, he stresses, unlike schizophrenia there is never any question about what is real and what is a hallucination.

Most people with Palinopsia presumably find ways to work with and around the condition and there are resources out there to help such as The Palinopsia Foundation. Alexis, on the other hand, is going beyond co-existence. His first PhD was in the area of theoretical multi-robot systems and he spent time interacting with neuroscience research groups. After earning his degree, he worked in the fields of finance, and speech and sound recognition. Following a calling to move deeper into music, he then completed a second PhD in Computing Music and became a composer.

Composers work is performed; artists often take their inspiration from their own experiences. As I spoke to Alexis about the lead up to the creation of Insight, which will premier February 10 of this year, it no longer seemed bizarre to create a composition that uses computers to enable the sharing of visual hallucinations.

In the next post, I'll explain more about how it all works. Don't stray too far...

What Would You Like?

2012-01-17T13:51:00.000-08:00

A short note this afternoon.

I have some very interesting material to share with you over the next few weeks if all goes according to schedule. I'm investigating several intriguing people and projects.

Meanwhile, as things are percolating here, I think this is a good time to throw a question out there. You can respond to me privately, as many of you already do, or post your ideas here as a comment if you feel brave.

Are there any any particular topics in interdisciplinary computing and/or socially beneficial computing that you would like to see me write about?

My ears are always open to your ideas.

Processing: Data Visualization and More

2012-01-06T20:59:00.000-08:00

Today's meeting of the Processing workshop was as stimulating as yesterday's (see the post from yesterday). As before, the day was a blend of interactive instruction about Processing and hand's on time to code with the system. However, we went deeper - one of today's topics was data visualization using Processing. Check out these examples of linguistic poetry visualization by Ira Greenberg.

Here is an absolutely fascinating data visualization of Eurozone debt. Although I don't know if this is written in Processing or not, I have learned enough these past two days to tell you it would be fairly straightforward to do so.

Data visualization brings together the computer science and the generative art solidly. It isn't just about making pretty pictures. In order to create meaning and relevance in your visualization you need to manipulate, perhaps transform, your data. Depending upon the application, this could mean pulling in calculus, trigonometry, geometry, physics, and chemistry. It could mean creating well thought out OOP code, efficient threading and algorithmic selections, array manipulation, random number generation. Another one of the workshop leaders, Deepak Kumar, showed us a class assignment where students must use an array of Objects to create a row of streetlamps (any design they want) that randomly turn on and off.

We experimented with creating code that behaves like those art boards where you paint with water: as you draw lines/shapes with your mouse they fade behind you at whatever rate you dictate.

Web interfaces, network communication, digital audio generation. One of our workshop participants expressed an interest yesterday in working with sound in Processing - today we were listening to her computer broadcasting music from across the conference room.

If you are interested in using Processing in your classroom, the workshop leaders (Deepak Kumar, Dianna Xu, Ira Greenberg) would be happy to talk with you.

This little guy is expressing his excitement:

(click on him and then be patient for a moment or two)

Computer Science via Generative Art and Vice Versa

2012-01-05T20:23:00.000-08:00

Reporting this evening from Dallas (Texas) where I am attending a workshop about the Processing system, a unique way to learn programming concepts using generative art. Within 10 minutes of starting to use Processing, I was sucked completely into coding, and was producing animated abstractions. This was my first program (a lot more interesting than any Hello World):

About 12 of us were sitting around the conference table and we were all heads down, heads up (to look at the overhead display where one of the presenters was explaining various features), heads down, heads up, type type type. College and University faculty, high school teachers, computer scientists, digital designers. Type, type type.

Before I knew it we were not only coding in Java (a language I generally dislike with a passion) but trying to figure out how to make loops, swoops, and geometric patterns bounce around the screen. And bounce they did - or grow, shrink, grow-shrink-grow-shrink. Change colors, size, shapes, speed up, slow down, fade in, out, turn corners, move around smooth rollercoaster-like curves...the only boundary was our imagination. When was the last time your first day of class was that productive and absorbing?

And this is no toy system. Processing has some unique attributes. Not only does the system use a real language (Java), it is accessible (such an easy interface), it is powerful and it is fun. It is also open source, contains excellent online help, and there is an exhibition space for uploading your creations along with their code. As open source, you can download other people's creations and code as well.

Designed originally by people affiliated with the MIT Media Lab as a language for artists to explore coding as a medium, it is now becoming well known in the computer science education community. One of our workshop leaders, Ira Greenberg, is a painter by training; he downloaded an early version of Processing around 2001 and not long after wrote a book (the first ever I believe) "Processing - Creative Coding and Computational Art". Fast forward: Now Ira has a dual appointment in Computer Science and Engineering and in the Meadows School of the Arts at Southern Methodist University.

What you can't see from these pictures I created (before lunch) is that they are dynamic. Both pictures, especially the one on the right, were moving under the direction of my code. Now yes, I have a background in programming and teaching Java, but I have no particular expertise in graphics. And I really do despise Java. Such a pain ...Usually. Not today.

More to the point, the two creations of mine included here are far less sophisticated than what others in our group were creating; one participant, a public high school teacher, created a brilliant beautiful demo on recursion this afternoon. Someone else created what looked like an ever expanding universe of pulsating multi-shaped colored particles.

There were a lot of fried brains by the end of the day because people barely looked up - most were glued to their laptops straight through lunch. By the end of the day it clear that we were well on our way into sophisticated concepts in science, math and computing. It just seemed to ... happen. I can't wait for tomorrow.

2012 Is Looking Good For Interdisciplinary Computing

2011-12-30T21:04:00.000-08:00

All signs are that 2012 is going to be a banner year for interdisciplinary computing. You don't have to look far to see evidence that more and more people are actively engaging in and publicizing interdisciplinary computing work.

On the computing education front: At the upcoming SIGCSE 2012 conference there will be sessions on studio based learning (several), digital humanities, interdisciplinary database applications, knitting patterns and program tracing, science fiction in computer science education. There will be presentations on healthcare and computing (several), and interdisciplinary travel. There will also be a special session devoted to the role of interdisciplinary computing in academia, research and industry. This session will be run by Ursula Wolz and Boots Cassel, the same people who organized the interdisciplinary computing meetings I attended and wrote about this past year. Interdisciplinary is becoming a hot topic in computing education.

In the private sector: Volumes of online and print text are dissecting everything that might have led to Steve Jobs repeated successes. Analyses of Jobs and the innovations he drove have repeated his comments about how Apple existed at the intersection of liberal arts and technology. A repercussion of these discussions is going to be (I predict) even greater corporate emphasis on how a meeting of minds between computing and traditionally non-technical fields can lead to innovation.

The term "social intelligence" is becoming more common as we look at what we can learn, intuit, predict, and know from analyzing social media. If we are to really understand what social media has to tell us about people, or, conversely, if we are to really use social media intelligently for business purposes (two sides of the same coin), we will have to do more to integrate our understandings from psychology, anthropology and sociology into our computing development work. There is huge potential here for intelligent forward thinking collaborations.

Most telling: If you pick up any computing / technology magazine off the supermarket rack and flip through it, you will find advertisements from organizations that tout their interdisciplinary or multidisciplinary achievements. Energy, water, biomedical, transportation, communication, disaster prediction and management, interactive literature.

One can focus on the exaggeration and hype inherent to much advertising, but that would be missing the bigger picture. The important thing to note is that the whole notion of promoting interdisciplinary computing has entered the mainstream. When large and small organizations jockey to convince potential customers and clients that *they* are on the forefront of interdisciplinary computing, then interdisciplinary computing is no longer on the fringe. Funding follows, and smart funding has the potential to nurture environments that drive technological innovation.

People will make the final decisions and determine the directions interdisciplinary computing takes. I am optimistic and excited about where we can go..

Happy Healthy Interdisciplinary New Year!

Computers and Society: Computing For Good Arrives Without a Flourish

2011-12-22T19:30:00.000-08:00

I am pleased to announce that my book "Computers and Society: Computing For Good" arrived on my doorstep yesterday, and is now officially out.

Many of the people I profiled in this book about computing and computers being used for social and environmental good, are both passionate about what they do and humble. As fate would have it, the arrival itself occurred in such a way as to reinforce the importance of being humble and remembering to value balance in life.

The guy from Fedex sprinted up the stairs and handed me a box while I was having a conversation with a guy trying to (at the very least) scam me for several hundred dollars. I suspect he was high on something as he kept hopping around and babbling. So busy trying to figure out what was going on with this guy that I set the box inside the door and forgot about it. Much later, after the growing evidence made me realize I had been dealing with a potentially dangerous criminal and I had called the police, I noticed the box from my publisher partially wedged behind a footstool. So much for the big moment of arrival!

I pried open the box and pulled out the book, not quite sure whether I was still upset with myself for having turned my back on the crazy guy when my computer chose the wrong moment to make a lot of noise. (This is how people get killed, I thought - don't turn your back on crazy people no matter what your computer does).

However, here it was in my hands - my first book. A book about people who are making the world a better place. Lots of people. The hundred or so people who shared their time and stories with me far outweigh the one crazy guy in my doorway. Whether working to save endangered sea turtles, helping kids in the neonatal intensive care unit, or modeling earthquakes, these people "rock" as they say. Life is short and precious and I'm honored beyond words to be able to share their work with you.

Challenges to STEM Education: Is it About Sex?

2011-12-16T14:58:00.000-08:00

I am disturbed by what I read today in the book "Nerds - How Dorks, Dweebs, Techies and Trekkies Can Save America* and Why They Might Be Our Last Hope". If you have a background in education, or simply opinions about the current state of STEM education (who doesn't?) the author's beliefs about where "reform" is needed are eye opening. (Hint: we need to pay attention to kids thinking about sex)

Anderegg (the author) builds a convincing argument that kids start learning at a very young age that "nerds" are social misfits, unattractive and bound to be sexual failures. Agreeing with this thesis leads to the conclusion that all the emphasis in the world on testing and assessment, all the attempts to show the economic benefits (good job, high pay) of a career in STEM will fall on mostly deaf ears, because: kids aren't making their decisions based on our adult logic. Kids make their decisions about what to study and feel proud of based upon social cues and a driving desire to fit in. By the time they are old enough to realize the innacurracies of the nerd stereotype it is too late.

Unless we are heaping criticism on a public figure, we don't like talking publicly about things like sex. (Does the idea of discussing sex and computing education bother you at all?)

American cultural anti-intellectualism is looking very guilty right now with regard to our problem attracting students into, and into doing well in, STEM classes.

If you buy this argument, it is no wonder we have such difficulty making computing careers attractive. Worse, because computing is everywhere we have a looming national crisis when large numbers of students turn away from computing education.

Although Anderegg does not (so far; I am still reading) separate computing out from science and math, I think we should do so for purposes of problem solving. For example, he writes that biology is as shunned as other sciences. He bases his arguments in great part on his clinicial practice as a developmental psychologist.

Computing educators and researchers see another set of data. Computing educators have amassed significant evidence that certain populations of students (e.g. women) are frequently drawn to biology. Showcasing the role of computer science in biological careers can put CS in a better light (from a student's perspective). I have written in the past about educators who are making connections between computing and the arts, music, social sciences (and other sciences) too. Students like these connections and revise their perceptions of computing because of them.

So on the one hand I am incredibly disturbed to see the evidence pile-up in "Nerds" telling us that we are approaching STEM education with blinders on.

On the other hand, and you really should read the book "Nerds" yourself to decide, I am incredibly relieved to read something that not only sheds new light on how serious the computing education challenge is, but provides a way forward.

Rainbow Simulation - Water Droplets

2011-12-13T17:47:00.000-08:00

Researchers at UC San Diego have been working on creating simulations that accurately model the formation of rainbows. In their news releases and presentations they talk about the physics behind rainbow creation and in particular the new discoveries that have been made about rainbows as a result of their work. Here is a quote from a press release:

"Computer scientists at UC San Diego, who set out to simulate all rainbows found in nature, wound up answering questions about the physics of rainbows as well. The scientists recreated a wide variety of rainbows – primary rainbows, secondary rainbows, redbows that form at sunset and cloudbows that form on foggy days – by using an improved method for simulating how light interacts with water drops of various shapes and sizes. Their new approach even yielded realistic simulations of difficult-to-replicate “twinned” rainbows that split their primary bow in two."

...

"Until now, most simulations of rainbows had assumed that water drops are spherical, which isn’t true for large rain drops, ... researchers have adopted a completely different approach and developed a more realistic model to recreate rainbows...offer the prospect of a better understanding of real rainbows,”

Stemming from a study of rainbow formation, there is an almost infinite set of topics we can learn more about from looking closely at the behavior of variously shaped water droplets. Here are a few ideas:

Weather modeling and forecasting

Animations in feature films

Atmospheric behavior on other planets that are found to contain water

Inspiration for new forms of studio art

Educational STEM software development

Frozen food storage behaviors over time

I could go further with my imagination but I'd like to know: What other ideas do you have?

I look forward to hearing your thoughts - you can comment here.

(UCSD Press release)

User Experience is ...

2011-12-09T14:36:00.001-08:00

Earlier this week I attended a meeting of people who all work in some way in the realm of user experience (UX). The word "realm" is so very appropriate. What is UX anyway? There are ongoing discussions on LinkedIn groups about what UX means, what is means to work in UX, what one needs to work in UX... Does one need to have a degree in HCI? In graphic arts? In Cognitive Science? Does one need to be able to program? Does one have to have a visual portfolio? etc.

Yes. No. It depends.

From what I could tell everyone at this meeting had a background and experience that ranged into the technical. Notice how I used another one of those broad words: "ranged". At least one person, I would call a "developer" - he talked a lot about the latest advances in HTML5 and the pros and cons of creating Native applications. Not so much about how users felt (affect) and what that means. There were several people with a graphic design background, who, I intuit, came out of the arts. They could probably create some very slick looking designs. There was a bit of eye glazing at that end of the table when CSS and HTML came up. There was someone who said that computer science and software engineering were the same thing (ouch); there were people who work in hardware-driven companies.

We were discussing the book "Mobile First" by Luke Wroblewski. Very nice little book (about 75 pages, I was able to read it in one sitting) that focuses on principles of design and their effect on the user experience in the world of mobile technology. Wroblewski made some very good points about how useful it can be to pare down online features to those that are most important to the end user and lose the rest. At least that was my take on it. I am all about finding out what the user's needs and goals are and what is and isn't working for them (and why!).

In addition, when I talk in a broader sense about "users" I include the organization that creates the page or app. After all, there are end users and there are the people who have something in mind when they develop an online presence. If there isn't a bridge between both groups, however different their worlds may be, then no one will be productive or happy. From my point of view trying to bridge that gap, everyone who has a stake in the success of a digital experience is a user.

Around our table, depending upon who was talking, we agreed or disagreed with the premise of "Mobile First", and our supporting evidence came with very different foci. Was it all about what the latest HTML would let you do? Was it about graphics on itty bitty screens? Was it about research methodologies such as Heuristic Evaluation? Was the whole idea of bottom up (mobile and then laptop and desktop) analysis and design the way to go? Wait a minute...wasn't it first about the user? (that was me).

I think, had anyone asked, that everyone around the table would have agreed that "it" was ultimately all about the end user and their experience with an application or web site. Occasionally I felt like we were all over the place in our discussions - and in fact we were. At first unsettling, I then became really excited, because I was experiencing, in a new setting, the broad nature of this field!

For example, in my own work I place a lot of focus on figuring out how to get at and experience a digital situation (web page, application, classroom situation) from the user's perspective - and backing that understanding up with rigorous research data. That reflects my background in cognitive science and educational research as well as in computer science. I am not likely to talk about HTML (5 or any other version) until after a lot of other leg work has been done.

Conversely, others in the room started from the technical constraints and worked up from there. If new technology permits new creative innovations, explore them. My geeky side appreciates this perspective. Sitting there, it was fascinating to be a bit schizophrenic by both taking part in the conversation and acting as a fly on the wall watching and listening to what everyone was saying and observing how it reflects their prior experience. No question about it, user experience work is not only an evolving discipline but one that has no fixed definition, no matter how much it might be nice to have one.

In fact I prefer a flexible definition of user experience. After all, the very words "user experience" tell you that the "experience" with a web app or software program is going to vary from user to user. There will be floating technical issues, front end and back end issues, psychological issues, sociological issues, software and hardware issues. People can be unpredictable and their interactions with technology can be revealing of so many things! The perspective viewed from each of these is different. That is what makes UX work so interesting. You have the opportunity to draw upon many different fields when you take on a UX project. And it is all about people - helping people.

Considering Collaboration with the Social Sciences?

2011-12-02T20:02:00.001-08:00

Psychology and computing have an interesting historical relationship. With the onslaught of All Things Digital, that relationship is becoming more complex. It should go without saying (although experience indicates periodic reminders are needed) that computing's relationship with psychology and other social sciences are as important as with any "hard" science - or should be. There are exciting questions to be considered and challenges to pounce on.

Historically, we tended to think of psychology as intersecting with computing via Human Computer Interaction (HCI), or in Artificial Intelligence. Yet, in both fields the emphasis has almost always been on the cognitive - efficiency and effectiveness in the former, data discover and interpretation in the latter.

But psychology is also about affect. As related in a recent article in UX Magazine about "Understanding Social Computing", the whole online user experience is more and more about personal interaction. Online educators know this. Marketing professionals know this - what marketing these days is not heavily digital? But there is so much more to talk about.

There is enormous opportunity for computing professionals who have a background in psychology (cognitive and affective). In the affective domain, we have opportunities well beyond the arena of sales and marketing. We have opportunities with educational software development to really maximize learning through sophisticated understanding of the interplay between the emotional and cognitive self. No doubt computer science can contribute to a greater ability to put that understanding into action. I wonder how often computer scientists work directly with educational psychologists?

Then there is anthropology and sociology. A friend, who is interested in the intersection of physics and anthropology got me thinking about this as we were joking around about her ideal future career in the search for extra-terrestrials. Where do computing and anthropology/sociology weave together?

Throwing a few thoughts out for your consideration: consider the context in which globally divergent groups perceive and interact with computing as cultural artifacts. Books and articles have been written by non-computing professionals on this topic. But how much has been written from within the computing disciplines? How do different ethnic, religious, urban, agrarian groups perceive and appreciate the potential of computing? If you think this isn't something for a computing professional to focus on, think again.

Or... ponder the different, surprisingly different, cultures that exist between traditional institutions of higher learning and non-traditional computing education organizations (private for-profits for example). Before you dismiss this subject for whatever reason (e.g. media reports of all the problems with for-profits) remember that just because something may not be palatable doesn't mean ignoring it is a good idea.

The more we think about it, the more I think we'll realize that culture is huge in terms of how computing "works" or "doesn't work"; collaboration with anthropologists and sociologists has enormous potential for benefiting the users, clients, customers, the public in general and for the field of computer science. And I'm talking about computer science here - the science of computation. Something to percolate on: What is the contribution that computer science can make to the study of culture?

So, I put these out there as questions: computing professionals, do you have working relationships with professionals in psychology - beyond the somewhat already trodden cognitive domain?

Computing professionals out there, do you have a working relationship with someone coming from anthropology? Sociology?

If this sounds at all appealing, and you don't have such a relationship, how could you form one?

The Computer Sand Society

2011-11-21T20:21:00.001-08:00

This week begins the holiday season for many people and often with it, unfortunately, way too much stress. Maybe that is why this week (Thanksgiving week in the US) brings out some strangeness. There was the blog post forwarded by a friend about stuffing a turkey with twinkies. It is hard not to feel fondness for something that springs back into shape when you step on it, but ... make a meat glaze out of the so-called "creme filling"? Yuck.

I also received an advertisement in the mail addressed to me at "The Computer Sand Society". Walking back from the mailbox, I thought: this could be a new interdisciplinary application! In response to this inspiration, a friend sent a lovely video link about sand animation; another friend suggested that, nice as it sounds, poolside would be much better than beachside because sand is hard on laptops. Could it be worse than three bouts of sick video cards? Perhaps, yes it could. Although I once told a cell carrier that my phone had mysteriously died when it had in fact fallen in the toilet (would you want to explain that one?), I'm not sure the computer manufacturer would buy into the notion that a gritty substance floating around the motherboard stemmed from disintegrating integrated circuits.

However, as I do believe in the power of creative thinking to spur innovation, I suspect there is opportunity for The Computer Sand Society to come into its own.

Modeling and simulation of sand castles. Has anyone developed a system, similar to those used by architectural design firms, to analyze the possibilities for ever more complex creations, factoring in the properties of sand - fineness of particles, distribution of various well crumbled crustacean shells, positioning relative to the high tide mark, mineral components?

Sand castle building is serious business for some people. The U.S. Open Sandcastle Competition bit the dust this year and its demise has many people very upset. I wonder if profits from my envisioned application might have helped hold it together? We could have perhaps drawn on the nearby expertise of the famous Scripps Institution of Oceanography, NOAA (the National Oceanographic and Atmospheric Administration) and the local surfers who are out every morning, afternoon and evening rain or shine, 365 days a year. Who understands the interactions between sand and surf better than these subject matter experts?

I have always wanted to combine my love of the outdoors with the potential of computing. A typo by some overworked marketing employee has given me the inspiration for a new hi-tech startup. All that is needed now is a really dedicated team to get it off its feet - and an angel investor.

Any takers?

Happy Thanksgiving - have some fun and forget the stressful stuff for a few days.

Interdisciplinary Computing in a Big Way: The Center for Science of Information

2011-11-15T16:42:00.001-08:00

If you followed the 3 earlier posts on An Interdisciplinary Puzzle, the Wireless Car, and finally Banana Trucks and Stock Traders, then you know that information theory was at the heart of the discussion. And if you were really curious, and followed the link hint I provided in the last of the posts, then you figured out that there is an exciting body of work in this area going on at: The Center for Science of Information. Their mission is "to advance science and technology through a new quantitative understanding of the representation, communication, and processing of information in biological, social and engineered systems". A mouthful, but a mouthful that hopefully makes sense after reading the other posts.

The Center's web pages contain an incredible amount of information about their interdisciplinary research, teaching and outreach activities. No one institution or discipline could do their work alone; through bringing experts together from across disciplines, they hope to develop new cross-cutting principles governing the storage, compression and transmission of information (examples in the earlier posts!). Nine universities participate in the Center as well as collaborators from a wide range of corporations and industries. In addition, students, undergraduate and graduate, and post-doctoral researchers have the opportunity to become immersed in this cutting edge research.

I had a fascinating conversation about the Center with Deepak Kumar of Bryn Mawr College. Deepak is the Associate Director of Diversity and Education for the Center, as well as a professor of Computer Science. Even prior to the creation of the Center, he has been teaching interesting interdisciplinary computing courses. One example is an undergraduate course on emergence. Emergent behavior appears everywhere in the natural world and is a perfect topic for demonstrating the utility of computational modeling.

For example, here in Southern California it is amazing to watch a group of Brown Pelicans cruise along in formation just over your head and then almost as one swoop down, realign into a row and ride the wind currents of ocean waves in the surf. They never touch each other or the ocean, although they can be inches from both.

Have you ever watched a flock of birds and wondered why they never crash into one another? I wonder: How do the Pelicans all know when to turn sharply, descend in unison, line up exactly the same distance from each other, and at some point, without apparent reason, rise up together again into the sky? If I watch any one bird, I can identify how it behaves. But somehow, and this is the puzzle, a group behavior emerges. Flocking birds are a classic example of emergent behavior which can be studied through computational modeling and Deepak uses this example in his course.

If birds don't suit your fancy, there are emergent behaviors to be studied computationally in linguistics, social networks, epidemiology (just for starters). Bryn Mawr is a perfect institution to be part of the Center for Information Science team not only because of courses like this, but because they have a minor in Computational Methods that actively collaborates with departments across the college.

I asked Deepak to tell me more about the role computer scientists play in advancing information theory. He obliged; here are a few things he shared. [I'm going somewhat technical for the rest of this paragraph] For starters, computer scientists understand algorithms and complexity. They know that how a problem is modeled will lead to various algorithms with different complexities. Which one(s) best fit the constraints and goals of the subject matter? A computer scientist can help determine what kind of processor to use, what algorithms to use, all the ins and outs of dynamic problems and dynamic programming. Computer scientists have an expertise in the classification of problems; they can identify a set of problems as of a certain type (e.g. NP-hard) and the relationship between how a problem is modeled and the resultant effect on the model. There is more, but you get the idea.

Next year Deepak will be teaching a course in the Science of Information. This class will bring the work and ideas behind the Center for Science of Information directly to his undergraduate population. The course, and related activities such as internships and mentoring, will provide opportunities for his students to interact with other institutions and personnel on the Center team. Deepak is very excited about running this course; in fact he told me that the most inspiring aspect of his role in Center activities is the opportunity to bring new superstar research to his computing students and to make it outward looking.

It is going to be very interesting to watch how all of this work develops over the next few years.

Interdisciplinary Computing Meeting 3: Day 2

2011-11-05T19:43:00.000-07:00

My computer screen is still on an acid trip - perhaps more so. Tonight it is purple and orange with green swirls and oozing deep amoeba-like dripping drooling things. But the keys work, so I can continue to talk about the meeting. The same caveats apply as yesterday, about typos, lack of links and copy editing. My notes from today are doubly challenged as I not only took them half blind but am now reading them back to myself more blind. However, I consider this an interesting cognitive challenge.

Onwards.

We started the morning with a faculty panel that seeded a discussion of challenges to Interdisciplinary Computing (IC) as well as interesting experiences. One particularly interesting speaker was Teresa Nakra from the Music Department at The College of New Jersey. She conducted an opera as part of her early music studies and later went to the MIT media lab where she worked with Rosalind Picard (of Affective Computing fame) on digital opera. Teresa spoke about designing a jacket for the conductor to wear which took readings of a variety of activities that were going on during the performance of the opera. Teresa spoke about the interdisciplinary nature of opera, which is probably not something many people in computing think of. This subject matter rang some bells for me, as one of my undergraduate degrees was in Drama, which field led me indirectly into the computing field. At that time everything was analog (certainly not the case now) but there were these interesting engineers in the lighting booth and one thing led to another and...

We spoke in more depth today about the various constituencies that are involved in the success or failure of IC and discussed ways to engage with them and foster a climate conducive to IC. A particularly interesting question came up:

Would it be preferable, in an ideal world, to have a greater preponderance of dual (or multi) subject matter experts or to have a greater number of computing professionals who are fluent enough in another field to hold serious conversations in that (those) field(s) without being a SME (pronounced "SMEE")?

We as a group had varied views on the matter and this led to a very productive discussion of the implications of each. What do you think? What scenario would be better for the fostering and ongoing success of Interdisciplinary Computing?

In another breakout session that I sat in on we discussed obstacles faced by industry. Interestingly enough, one of the topics that came out without my initiating it, was the very interdisciplinary nature of UX work in industry - short for User Experience if you aren't familiar with the term. Interesting to me, because I have been working on UX , and have written about UX a few times in this blog. It is clearly an interdisciplinary area of work - computing, psychology, art, design, development - depending upon one's emphasis, these and other disciplines can be central. UX is a clear point of connection between academic interdisciplinary computing work and industry. Much of Computer Science Education research work can or does fall under the UX umbrella.

In discussing the challenges faced by industry it became clear that there is no universal set of challenges and it is hard to make any generalizations that stick. Large companies may have more time to allow people to come up to speed and may have time and resources for some cross training; small companies may have to get something delivered yesterday. Traditional hi-tech companies may have one set of IC needs whereas the health care IT industry may have a vastly different set of requirements (must one have medical background? someone suggested this might well be the case). Non-profits, for-profit companies - different types of missions, thus different challenges. These discussions also led to a brief conversation about how to prepare students in very concrete ways - such as providing advice on developing resumes. Does one want to be a generalist or a specialist within the IC world? If one is working in an IC area, in other words, to what extent should one narrowly niche and to what extent should one be broad? These questions relate back to the question about whether it would be preferable to have dual SMEs or single area SMEs with a solid working knowledge in other areas.

So you see, we were beginning to pick up on patterns of issues that have to be carefully considered and addressed (and we did have discussions on these subjects). I wish I had room to delve deeply into it, but there will eventually be a formal report from the organizers of these meetings (Ursula Wolz and Boots Cassel) and some of the ideas I mention will no doubt be part of the discussion there.

Another theme that came up again and again, yesterday and today, was the need for communication strategies among people who are involved in IC. Support mechanisms to facilitate communication, formal (workshops, meetings, regional structures to support ongoing conversations) and informal (funded lunches as one idea. A little pizza can go a long way), in-service activities specifically targeted at IC collaborations, mentoring opportunities to bring in and support new colleagues.

Publicity, outreach, and awareness raising came up a lot today. If we are to affect Hearts, Minds and Culture, (a phrase from yesterday) then we must start putting the whole notion, appeal and benefits of Interdisciplinary Computing into people's minds in many different ways. If the general citizenry and youth perceive IC as interesting, and a part of the fabric of society, then we will go a long way towards achieving a major shift towards accomplishing many of the more discrete goals of IC.

Along these lines, I will conclude this once again longish post (and one that is killing my eyes!) with another amusing moment from today. Someone brought up the information that when the original Chuck E Cheese was developed it incorporated a model of exposing entire families to the "product" and thus gaining buy-in from families, and that, get this, Chuck E Cheese was THE premier place for showcasing technology to children through robotics. A member of our group personally remembered this. According to one perspective, the robotic approach didn't quite work out because it scared children (oops).

However, overall the "engage the entire family" model was successful and has continued, spreading to many other companies. Some highly creative soul in our group suggested "CyberCheese" as a name for an Interdisciplinary Computing marketing campaign. Engage the entire family in computational interaction. If the entire family is engaged, parents, kids, extended family, friends - things could take off.

After I about died laughing at the name, I realized...hey...this idea isn't so bad is it?

This post was updated on 11/10/11 to fix typos and add links.

Interdisciplinary Computing Meeting 3: Day 1

2011-11-04T21:09:00.000-07:00

This is quite the post for several reasons. I am in Washington DC attending the third Interdisciplinary Computing meeting. I posted about the previous two earlier this year [the January meeting, the April meeting] . When we were at dinner, I was sitting next to someone who is in the arts and telling him how I was very interested in finding an interesting project that crossed over computer science and the arts for a chapter in a future edition of my book. Well, I got back to my hotel room and discovered that the video card on my motherboard has gone out. So I am writing this post on a psychedelic smeary LSD reminiscent screen - and I can't really read what I'm writing. This is not exactly what I had in mind when I asked for a convergence of art and computing. Beware what you ask for! For the next two days I'll be writing this way, as a replacement part will be meeting me back in San Diego later this week. Meanwhile...have patience with the typos and lack of editing because I can't see beyond the pulsating purple and lime green.

So on to the meeting report. As always, all of the comments in this post are my interpretations and reflect my perspective on what occurred. They are not any "official" pronouncement and there may be others at the meeting who have a different set of thoughts. If that is you, please chime in!

Today was the most incredible example of synergistic conversations that can come out of putting passionate widely divergent thinkers together.

Two of our meeting goals (as laid out by our trusty leaders Boots Cassel and Ursula Wolz) are to identify the breadth that is Interdisciplinary Computing (IC) and how to Facilitate Interdisciplinary Computing. Lynn Andrea Stein from Olin College talked about the interdisciplinary nature of Olin, an engineering school that was able to design interdisciplinarity into itself in a holistic way in part because they were able to start from the ground up approximately 10 years ago. Valerie Barr from Union College, founded in 1795 and the first college in the United States to offer engineering programs, provided an interesting contrast as she spoke about her work with a large range of successful IC programs.

A common theme was the infusion of computing into courses outside the traditional curriculum as well as a major rethinking of CS coursework - both institutions are having great success, attracting more students into the CS courses and increasing diversity.

With the audience of CS faculty, arts faculty, education, math (and more) faculty chiming in and asking many questions the phrase came up: Hearts, Minds and Culture. All three must be addressed. Further discussions delved into what that means. At the faculty level, student level, institutional level.

We had two breakout sessions and in both I was extremely priviledged to sit with some of the most interesting and engaged people. We wrestled with tough questions such as:

Outcomes are important (we all agreed) as are Goals - should Goals come first, followed by Outcomes followed by metrics for assessing them, or perhaps should desired Outcomes be the starting point with the other items emerging from there? It turns out to be a fascinating way to turn your thinking on its head.

Verbs vs. Nouns. Several breakout groups (including ours) independently came up with this terminology to describe how we must stop thinking in terms of Nouns (e.g. "content") and think in terms of Verbs (what do we want to DO, to have students DO). And if we make the mistake of framing Goals in terms of Nouns instead of Verbs, we will undercut the whole purpose of trying to be innovative and creative and flexible in our approaches among different departments. Noun (content) orientation can lead to "content wars" in many cases and a lose-lose situation, as opposed to a win-win situation in which everyone can find common ground.

Very interesting idea. Think in terms of Verbs - it makes sense that this orientation would lead to a greater chance of finding mutually beneficial modern ground among widely diverse faculty. Gets us away from the dreaded "coverage debates" many of you no doubt know too well.

I'm going to short change some of the day's activities a bit in order to keep this to a reasonable length for a post, but there is one last item that energized me so much I must mention it. One participant, during a full group discussion, asked the question: should we think of Interdisciplinary Computing as "corrosive"? Corrosive in that it breaks down institutional boundaries and structures? And if so, is it corrosive by its very nature or is it something that those involved would want to specifically focus on? Corrosive. Fascinating. That is such a vivid word. Think about that will you?

The same person followed up with this thought: if Interdisciplinary Computing is indeed corrosive, then the theoreticalground of doing IC work changes.

IC is rhizomatic he posited. I know what a rhizome is (in a general sense), but I had to ask for an explanation in the context of this conversation. He explained, (and I try to closely paraphrase) – you can’t teach what youwant to teach from any one source. You break something and it will find itsway around via a different route.Wow... think on that one too won't you? This is what you get when you work with interdisicplinary minded people from different disciplines.

Finally, my vocabulary was expanded even further in the context of IC when in a breakout session we were discussing the topic of forming and sustaining IC community. One member of our group brought up this idea, which we all latched onto: the notion of the Interpersonal as equally important to the notion of the Interdisciplinary. The importance of realizing that it is relationships between people that will make or break IC and that a strong focus on developing, supporting and maintaining interpersonal relationships among *people*, not just "disciplines" is vital.

Interdisciplinaryvs. Interpersonal. Put another way: There is interdisciplinary work but there are interpersonalrelationships b/w faculty and we need to find ways to facilitate and supportthose relationships. Equally or possibly even more important.

And finally, the most mind blowing IC vocabulary expansion for my afternoon came with someone in our group suggesting we think about IC this way: as Inter-Epistemological.

What?

Inter-epistemological– theories and ways of knowing. The interconnectedness of different models of waysof working.

In digging around for some definitions of "inter-epistemological" someone found a previously published paper with an eerily provocative title:

“Moving beyondinterdisciplinarity: Academic Reflexivity in an inter-epistemological researchprogram, celebrating indigeneous knowledges: Peoples, Lands and Cultures”

Think about Interdisciplinary Computing (corrosive and rhizomatic) in terms of that phrase.

From purple smeary-land, over and out for the evening.

This post was updated on 11/10/11 to fix typos and add links.

Banana Trucks, Stock Traders, iPods and More...

2011-10-28T23:55:00.000-07:00

Information interchange is an activity shared by biological, chemical, physical, economic and social systems. As science and technology have accelerated in recent decades, we now routinely deal with enormous amounts of data that we try to model accurately in order to understand. When you think about it, these systems have a lot in common.

For example, my rudimentary understanding of how stock market trading works, leads me to understand that market traders need to get certain complex data right at the beginning of the market day. Within the first few minutes in fact. Any later, and that data is useless to them. Incomplete or inaccurate and that data is useless to them. This is essentially the same challenge faced by our wireless car which must receive all its varied sensor data properly.

Information theory provides the starting point for addressing these challenges and those of even more complex natural and artificial information interchange systems alluded to above. Claude Shannon's theorems (greatly simplified and hopefully not misrepresented as a result) assumed that data can be encoded as a string of 1s and 0s and transmitted from one point to another. Shannon's ideas enabled us to understand and address data degradation over distance traveled, effects of interference ("noise") and the recognition that when we encode, store and transmit data we can compress it to save space and reduce latency (i.e. speed things up).

An entire communications industry was spawned as a result of information theory. Among other things, we have been able to leverage our detailed understanding of the costs associated with data compression. For example, have you ever compared the sound of a song played on an iPod with a song played from a professionally mastered CD? Which has better quality? The CD of course. On the other hand, you can store far more songs on an iPod than on a CD. This difference has little to do with "old" or "new" storage media technology. If a 1 hour CD can hold approximately 12 songs, whereas your iPod can hold far more than that, it is because, in order to squeeze additional music on the iPod, you lose some digital bits that supply the greater dynamic range heard on the CD.

You probably don't care though, right? You don't expect professional quality music reproduction coming through those little ear buds. Cycling down the road, jogging along the trail, or wherever you are tearing around dangling your iPod, your primary concern is access to reasonably decent portable music. Conversely, you expect a CD playing on a multi-speaker Surround Sound home theatre system to produce pretty darned nice music, right? I certainly do. Personally, I don't know if I could handle hearing Bohemian Rhapsody in its super compressed format on an iPod. But I could definitely rock to the original Hawaii 5-O Theme Song.

How do we know how to produce just the right fidelity for MP3s, CDs, DVDs, etc? Because information theory has led to a highly accurate understanding of the tradeoffs inherent in different types and amounts of data compression as well as a host of other factors that come into play when deciding the optimal way to transmit data point to point. So we know how to model different audio/video systems and choose the compression, transmission and storage methods most appropriate for a given context. The digital data comprising a Dixie Chicks song will be treated much differently if it is to find its way onto a CD vs. an iPod or the movie theatre. Yet each scenario will be optimal and we understand how to make it so.

If only that was all there is to it. The problem is, not all data manipulation is as straightforward. This is where I want to start calling it "information" rather than "data", because much of the "data" we now study has meaning that cannot be divorced from it - hence is "information".

Consider the modeling of a system for optimal routing of commercial trucks. To keep it as simple as possible, let's say all trucks are going from Point A in San Diego, California to Point B in Chicago, Illinois. A truck full of hazardous waste and a truck full of bananas are definitely not the same animal. The optimal routing of those trucks is not the same. The hazardous waste truck must avoid certain roads and population areas, perhaps certain times of day, even if it takes longer to get from San Diego to Chicago. The bananas on the other hand, must arrive as quickly as possible or else rotten mush will show up at the grocery store. A dynamic traffic routing system must understand the semantics of the data, i.e. what is in each truck en route. In this case, semantics also affects temporal issues - timeliness of arrival. The system must be able to adjust on the fly to all the unexpected things that could happen along the way: snow storm, sink hole, holiday parade, incorrect satellite map of the road! Plus, let's complicate matters even more: if our grocery store in downtown Chicago is deluged at the same time by 50 trucks of perishable produce coming from ports on both coasts, there will be Chaos in The Loop (downtown Chicago). And more likely than not, rotten mush on the shelves and in the dumpsters.

Do you see how our wireless car system design has a lot in common with our commercial truck routing system? This is the same class of challenges that exist within a myriad of natural and human-made systems. Even if you aren't a professional in any of the fields listed in the opening paragraph, you may begin to see the commonalities within complex information interchange systems. To understand these systems we first have to try and model them, taking into consideration all the relevant variables and their interactions: syntactically, semantically, temporally.

Information theory has to be taken to the next level, to incorporate additional factors. Do you want to hear more about all this from an expert? As you wait for the next installment in these posts, consider tuning in October 31st to an interesting talk on the history and philosophy of information.

Not to mention, by doing so, you will get a head's up on the people who are working on "Shannon 2.0".

The Wireless Car Considered

2011-10-27T20:55:00.000-07:00

In order to answer the question(s) posed in my previous post, let's go back to the automobile. Your car. Unless you are into antiques, chances are that your current car is a computer on wheels (thinking from a layman's perspective). You probably know this if you ever have taken your car in for what seems like a small repair and get hit with a gigantic bill because "the chip needed to be replaced". Or, you take your car in and they tell you they will "plug it in and run diagnostics". They download some data, study it, and presto, tweak just the right part of your vehicle. You save money.

The heart of modern automobile engines is a CPU in the engine control unit which serves as a data collection hub. Approximately 150lbs of wiring runs through your car between various sensors and the engine control unit. So when something goes wrong, it might be one of the sensors, it might be a wire, or it might be the CPU. Of course, there are many many advantages to having a CPU in your car as compared to the older technology, but this isn't the right place to go into that. What is relevant however, is the fact that all those wires are MESSY. And HEAVY. And ... complex.

Imagine the advantages that could be gained if those wires could be removed and replaced with wireless broadcasting of sensor signals to the CPU.

150lbs less weight: that's about one adult, or a few kids, or many pets, or a lot of gear. Lighter car, better gas mileage.

No wires: less mess in the cars innards (think like a mechanic to fully appreciate that one).

No wires: less complexity and cost in the manufacturing process - consider the domino effect of not having to figure out placement, routing, materials use, secondary waste generation. The car should cost less to build, thus cost less to the consumer. Economies of scale can be gained if the elimination of wires in favor of wireless becomes standard.

Store the data, compress the data, transmit the data. This is where Shannon (my final hint in the last post) comes in. Claude Shannon, whose seminal work approximately 60 years ago founded what we now know of as Information Theory. Theorems about optimal point to point communication of bits. Your cell phone calls rely on application of information theory as do your Skype calls, iPod and CD storage and other applications too numerous to count. I'll come back to that later because with our automobile scenario

There Are Challenges.

For starters, we would need to make sure that my Subaru, sitting at the stoplight next to your Lexus, doesn't tell your Lexus what to do (in theory this might be fun, but I digress). Non negotiable requirement: my car's wireless transmitters need to be picked up only by my car's CPU.

In addition, my car's CPU would have to juggle incoming signals from many sensors. There are N (meaning I have no idea how many) sensors in my car, each of them likely has a different sampling rate, transmission distances vary point to point, noise is inevitable, delay is inevitable, and there are definitely other parameters that I am not thinking of. To function properly, my wireless car's CPU must receive all the encoded data in sufficiently robust form in a timely fashion.

If you are familiar with classic information theory, you know where I am going. If you aren't, then I'll point out: Shannon's seminal work on data storage, compression and transmission didn't anticipate the kind of requirements involved in developing a functional wireless network automobile.

But there is a group of people working on this exact problem and the larger class of problems of which it is a part. And the results they come up with will effect Biology, Chemistry, Economics, Social Sciences, Engineering, and more.

To Be Continued...

(I won't make you wait a week)

An Interdisciplinary Puzzle For You To Figure Out

2011-10-20T13:21:00.000-07:00

Today I am going to give you something to ponder for a few days - see if you can figure it out. Then, next week I'll tell you all about an exciting project I learned about this week.

What do biological, physical, social, engineering and financial systems have in common?

Toss in Computer Science. Computing is key to solving the puzzle of what this mystery project is.

A concrete example of where it all comes together involves one of the most prevalent objects in the developed and developing world: the automobile.

Think about how many feet of wiring runs through your car. How many feet do you think there are on average, front to back? Have you ever thought about that?

What does the wiring in your car accomplish and what are the critical factors in its proper functioning (don't forget about temporal issues)?

Wiring: kind of Old School technology don't you think?

Let's say you remove the wiring (or most of it) from your car. What advantages might you get from eliminating the wiring?

WHY DO WE CARE? (hint: economic productivity is one answer)

Hopefully some ideas are popping into your head - crazy ideas are fine. Crazy ideas are very good. Innovation comes from so-called crazy ideas and that is rarely a bad thing.

I leave you with a parting final hint: Claude Shannon.

If you come up with the solution before I post about it you gain enormous brownie points and public acknowledgement of having a highly productive brain. All ideas welcome.

Enjoy your mental percolations.

Puzzling Phone Algorithm; Virtual Reality Consumer Product Research

2011-10-12T16:40:00.000-07:00

Recently I had a conversation with Franz Dill, who maintains one of the most prolific blogs I have run into. The name of his blog is The Eponymous Pickle, and you might want to think about that name. Once you figure out what that title is all about, you'll have a window into what a conversation with Franz is like. Without letting the cat completely out of the bag I'll just say...really interesting and loaded with ideas.

Before we even got into "the real conversation" something interesting happened. We were discussing the fact that I was on Skype from my computer and he was on Skype from a mobile phone. In comparing our reception quality (which was fine) I noted that if he had another call come through that the Skype call would be dropped. The first time it happened to me it was quite puzzling. One moment the person I was talking to was there, the next moment he was gone. poof. No warning for either of us, just - gone. Franz suggested this was probably the result of call prioritization.

Hmm? Now, looking back on it I'm wondering - that seems like an odd arrangement. Who wrote the software that made the decision that a current call should drop if a new one comes in? Did anyone test that out on users? It doesn't follow usual phone protocol. It also doesn't lead to a positive interaction moment, and in the case of a critical negotiation for example, could be quite disruptive. Why do you think they (whoever "they" is) wrote the algorithm that way?

Moving on...one of the interesting things Franz and I discussed was his role in creating the first Innovation Center at Proctor & Gamble. The Center was (and still is) used to creatively experiment with the impact on consumers of various home and store environments. They took over a warehouse in the middle of a cornfield and built a house inside it (yes, you read that right) and later built a store next to the house - inside the warehouse. Apparently one reason to build a house inside a warehouse was so they could make constructive adjustments to the facility (such as punching holes in the wall :) for the purpose of improved experimentation and monitoring. Presumably, having your own house in a warehouse meant that the house could be recreated and repurposed over and over again as needed.

Franz and his colleagues performed all sorts of experiments with real consumer/users and these experiments eventually moved into the realm of virtual reality. For example, they created wall size displays that people could interact with (you can see a picture of one and read about it in detail in the Eponymous Pickle).

I wonder if the current development team is working on a 3-D virtual store yet. Imagine what it would be like not only to look at and touch the wall display but to reach out and pick up items items off a virtual shelf and put them in a virtual shopping cart. Or perhaps pick up virtual items and put them in a physical shopping cart. The technology to do this exists. I didn't ask Franz about 3-D virtual consumer experimentation and I wish I had.

What do you think the consumers/users reaction to virtual 3-D shopping would be? (That means...you!)

Ada Lovelace Day: Thank You Nell Dale

2011-10-07T22:56:00.000-07:00

Today is Ada Lovelace Day, and there was a call put out to write about someone who has made a difference in your life. After thinking it over, I decided that I want to write about someone who through a act of kindness, trust and a willingness to take a risk completely changed the course of my career.

I'm speaking of Nell Dale, who is well known to almost everyone in the ACM SIGCSE community and many people beyond it.

In the 1990s I was working full time as a computer science instructor at a wonderful community college - Chemeketa Community College in Salem, Oregon. I was in charge of all aspects of the transfer program. The position was wonderful, exciting and stimulating, with significant responsibilities - in some ways a dream job. I was developing all the transfer courses and teaching all of them, I was running around the state of Oregon creating articulation agreements with the Universities, I was doing....many things. I could see the direct results of my work on students' lives. I had an inkling that I was interested in research so I just started doing it by the seat of my pants. I certainly had no formal training in it at that time. It was exciting.

However, as not only the only woman in the department, but the only CS faculty member who had a formal computing background (I'm pretty sure) and the only one interested in research as well as in teaching, it was sometimes a bit lonely.

Along the way I heard about the ACM Special Interest Group on Computer Science Education (SIGCSE) and I joined the listserv and conversations. It was wonderful to have others to exchange ideas with.

Somehow, through that channel Nell, who was on the computer science faculty at The University of Texas at Austin, learned of my existence. One day I received an invitation to be a member of a panel she was putting together for the next SIGCSE conference. I had no idea Nell was so well known and highly regarded or that she was right smack in the center of everything SIGCSE. I had no idea that SIGCSE was a conference loaded with people who I would eventually come to think of as family. All I knew was that I received this invitation from a complete stranger, asking if I'd like to be on a conference panel and I said Yes. The panel was accepted, and the next thing you know I went to San Jose and met Nell Dale in person shortly before we gave our presentation!

I was in the "wow wow wow" stage, and showing my newbieness by trying to get my hands on every free textbook that I could and stuff them into my exploding suitcase. During one of the conference lunches, Nell and I were talking and I said something about my interest in conducting research. Nell said: "You should come to Austin. The University of Texas at Austin has a computer science education research group". I didn't know much about UT and I knew nothing about Austin - or Texas for that matter. Both are now places very dear to my heart. During and after that lunch I thought about Nell's comment. Long story short, a few years later I picked up and went back to school for my doctorate, where Nell indeed was leading a wonderful group of people all interested in computer science education. Participating in that group was a wonderful experience, full of synergy, exciting ideas, passion. I had found a home. One thing led to another and I eventually created an interdisciplinary dissertation and coursework that spanned computer science, psychology, science education and math education. My education and the supportive relationships I formed in those almost-7 years were incredible.

None of this would have happened, the snowball would never have started rolling, if Nell hadn't reached out one day over a listserv to a complete stranger and asked if she wanted to join a panel. I have always remembered those acts of generosity to a newbie and have tried to emulate her actions in my own.

Thanks Nell.

Design Studios, Studying Design

2011-09-29T19:44:00.000-07:00

Back in August, while attending the ICER conference, I discussed some work being done to incorporate the studio model into the computing classroom. Several people replied, sharing their own work in this area or knowledge of others' work. At least one person I spoke with believed the studio model was impractical. Interestingly enough, there is a discussion about the use of Design Studios within the UX (User Experience) community. In late August, the first of two articles in UX Magazine discussed the basics of Design Studio. The rationale for using Design Studios included the following:

"The reality of designing modern digital solutions is that no individual can solely capture all the complexity of creating a truly vibrant product with various customer engagement points, different usage patterns, and behaviors based on complex needs, goals, and customer backgrounds, all interwoven into an emergent, ubiquitous engagement tapestry. This is why innovation really is, and should be, a team sport."

The above quote reflects a key feature of UX work: obtaining a holistic view of the interactions, perceptions and ramifications of users interacting with digital artifacts. Beyond traditional user interface and graphical design issues (although those are relevant), to include all the complexities that people, as people, bring to the table and what that complexity means for their "experience" (hence the name User Experience). Cognition, affect, behavior, environmental and social factors.

The second of the articles, which came out today, provides resources and guidelines for how you can put Design Studios into action. Very interdisciplinary:

"Teams should be designed to have some balance representing various disciplines. Mix up key stakeholders representing various functions within the company. I have found that it’s crucial to include participants from sales and customer support. They bring a unique vision of the customer and the market to a process. Ideally, Design Studio should cut across executives, sales, customer support, product management, development, marketing, and experience design."

These articles are a great resource if you are interested in the implementation of design studios - either in the classroom or in your workplace.

If you follow the guidelines shared in these articles, ... what has your experience been?

Commonalities Among Computing Professionals Who Work for Good

2011-09-22T11:53:00.000-07:00

I am performing a final review of the the production text of my book on socially beneficial uses of computing (officially: Computers and Society: Computing For Good). The computing topics range all across the discipline of computer science (high performance computing to social media) and the non-computing topics are as diverse as saving endangered sea turtles, medical informatics and educational software for children with disabilities. Several years in the writing, I met on this journey either virtually or in person, dozens and dozens of people. Looking back on all these wonderful encounters I am struck once again by the commonalities among them.

1. Passion. More than anything else, the people who shared their stories (and those of their organizations) with me felt that their work was more than a job. Again and again I heard about how the cause they worked towards (earthquake prediction, identifying best practices recommendations for infant care, poverty alleviation) gave a sense of purpose above and beyond a paycheck. When things got tough, their passion for helping people or the environment supported them.

2. Risk Takers. As many books on innovation in business have documented, a willingness to take risks, experience setbacks or even failures, is absolutely necessary. Some people I met had abandoned secure positions to follow their dreams, or within their current careers they strategically stuck their necks out to convince others that their ideas were sound and worthy of support. Again and again. Technically and non-technically. Risk taking, dealing with the inevitable setbacks by getting up and moving forward are an ingrained trait in many of the people who are doing the greatest good with computing.

3. Curious and Open Minded. A common reaction to being a risk taker (whether in the world of computing innovation or elsewhere) is to face and go beyond those who say "it can't be done" or "this is not the time". In fact, as the interdisciplinary computing pioneers I met demonstrated, you need to let these critiques roll off. Instead, keep asking questions, gathering information and recognize there is rarely only one way to solve a problem. In fact, the more that conventional wisdom says this is so, the less likely it is to be true.

4. Keep Technically Current and Constantly Learn. Just as I had the privilege and necessity of diving deep into the world of mobile devices, computer security and other areas of computing, the people who are highly effective and innovative with their socially beneficial projects are continuously studying. Not necessarily (or usually) through formal education, but through reading, experimenting, sharing, and just plain digging into material further than they "had to".

Perhaps more than anything else, the computing and non-computing professionals knew themselves well, and knew what their dreams were. They made a personal commitment to pursue those dreams.

If you are reading this, it is likely you have a desire to "do good" with computing. Do you know what your dreams are and are you pursuing them?

Lacking an Understanding of Psychology Can Doom Your Efforts

2011-09-16T10:55:00.000-07:00

Mobile devices are inherently interdisciplinary and one would hope that the design and development of them would include a solid understanding of psychology by their creators. But it may not always be so. A few days ago I was in a car with a friend, trying to use her Android to obtain GPS coordinates to a place we wanted to go up in the mountains. If you read my earlier post that included a venture to a Verizon store, you recall that I had a fairly dismal experience trying to investigate the Android. So this was my first experience trying to use an Android in a live situation under some mild pressure (we needed to figure out where we were going before we reached the limits of cell and satellite coverage). I had a heck of a time trying to figure out the UI (User Interface) on the device. All these cool apps covering a wide range of useful tasks and I finally put down the phone in frustration and we headed up the canyon using old fashioned biological GPS (Guidance via Perceptual Sense-making)

My user experience with the Android was terrible. I wondered how the designers and developers had conducted their user research prior to developing the interface. Case in Point: The little magnifying glass on the Android does not Zoom in and out. With a magnifying glass right there in front of you, and used for zooming on other applications, who would intuitively think to do that funny expanded swooping maneuver with your fingers? Who came up with that idea? I'd be willing to bet it wasn't the potential users (someone please, correct me if you have evidence otherwise, as I'd love to hear about the origin of that particular feature of smart phones). Did the product team conduct live interviews and focus groups for example? If so, how did they pose their questions and / or perform their observations?

You have to apply some psychology to the process if you want to produce effective products. Understanding the psychology of human interaction dynamics is important when conducting any type of user, client or student interview, observation or research. It is all too easy to unintentionally lead the conversation or activities and thus bias the information you are gathering. At that point you see what you want to see, and it filters into your end product.

If you want to collect data that is as free as possible from your own perspectives, you have to be on the ball. This applies to usability work, and broader user experience investigations as well.

Human interaction dynamics will lead someone to want to agree with their conversational partner if they feel that person is of higher status or in a position of power in some way. This can happen on a subconscious level. You the interviewer or observer have to be alert to not letting on what your hopes are for what you see and hear or what your opinion is of what you see or hear. You say "What was hard about that?" and the other person will look for hard items even if they didn't experience any. Contrast that question with "How easy or difficult was that"? The latter provides no clue as to where you might stand on the ease or difficulty of an experience.
You want to appear non threatening and personable in an interview without falling into the "friend trap" of holding a conversation where you will naturally dominate the conversation because the other people view you as the dominant party. Ask their opinions and for expanded explanations and avoid sharing your own - smoothly. If asked your opinion, here is a Bad Way to do respond: "I don't want to share my opinion on the ease of use of XYZ. My opinion isn't relevant here". True, but a real put off and conversation stopper. Worse Way to Respond: "I find it easy to use." Now the user feels stupid or perhaps condescended to and is likely to change their responses to not look stupid, or change their responses by simply giving up on sharing with you on that topic. Better Way to respond and redirect: "I am still forming opinions on that subject. Could you tell me more about what you think (feel) about XYZ?" This approach is accurate (you are forming opinions as you gather data) and redirects the conversation back to them and their experience.

You can try out your use of psychology in a computing context: pick a device or system you own, give it to someone else to use and see how much information you can obtain from them without dominating the conversation or guiding their answers them with your opinions. The person doesn't have to be brand new to using the device or system. although that can make your job easier.

Creating an Interdisciplinary Profile: Interview Style and Your Written Presence

2011-09-12T10:57:00.000-07:00

Writing a profile about someone who is interdisciplinary can be challenging but is a lot of fun and an incredible learning experience. Recently, after several people asked me how I go about it I stopped to think about the process. I write these types of profiles in several venues so there isn't a one size fits all answer. No question: there is always lot of data gathering. For every line written, many lines go unwritten and you have to decide what to put in and what to leave out. However, the starting point always includes knowing who your audience is and what their expectations are. Audience understanding leads to what questions to ask in an interview, how you ask them, and then as you write, and those all-important decisions about tone, depth, and overall profile structure. Compare the approach in two very different outlets: a blog post and a book.

Blog Profile Guiding Principle: Be part of the process and keep the information to one, or at most two, points. When I write a blog post I assume my audience expects a fairly short, punchy profile. I have to get to the point rapidly. There will be a computing component and another field (discipline) component. I assume a broad computing audience that may or may not have experience in the non-computing field. When I conduct the interview (and there is usually only one interview) I can share related experiences as I strive to learn about the other person's work as rapidly as possible. You can only keep someone on a Skype call for so long before everyone's brain wears out. When I write the blog post I can share my own insights from the interview which helps the audience relate to what I am writing about. In fact, they expect to hear my voice and thoughts – both directly and indirectly. In a sense, my audience and I learn together.

Book Chapter Profile Guiding Principle: Step back and tell a story with many related topics under one major theme. The profiles in my upcoming book on socially beneficial computing are chapter length so you know there is going to be a lot of information which has to be spread out and logically tied together. As in a blog post, there will be a computing component and another field component; my audience is highly unlikely to have experience in the non-computing material. Therefore I know that unless I want to lose my readers at the starting gate I have to provide an engaging yet structured presentation with a clear set of goals. There is time to deepen and broaden the material. My readers do not expect to hear my opinions and insights. Thus when I conduct the interviews (usually there are many interviews extending over many months) I have to pay particular attention to not interjecting my experience and perspective into the conversation. If I don't stick to this interview approach, we will never get to all the complex technical and non-technical information about their work and how it has evolved. Given how often I talk to each person who is part of one of these extended profiles, and the time they make in their crammed schedules to speak with me, I must make every minute count. It's not about me, it's about them.

You can try something I periodically do to keep on my toes: read a profile someone wrote and try to figure out how they structured the interview(s).

Here are links to some of my prior profile posts. What do you think I did to prepare for each interview and what questions did I ask?

http://computing4society.blogspot.com/2011/08/things-to-think-with-crochet-hyperbolic.html

http://computing4society.blogspot.com/2011/05/journalism-meets-computing-in-big-way.html

http://computing4society.blogspot.com/2011/01/unusual-computational-science-educator.html

How To (and How Not To) Hear What Someone is Telling You

2011-09-05T15:34:00.000-07:00

A few days ago I was standing at a store counter and fell into conversation with a programmer who was feeling on top of the world and wanted to talk about his accomplishments. I had never met this guy. When he asked what I do, I decided to share how much I enjoy working with people and discovering what they want, need, or perhaps are stuck on with regards to computing and technology. These discoveries can lead to innovative, or more importantly, truly helpful solutions.

I had barely uttered a sentence when the guy enthusiastically told me that he "does that all the time" and launched into a monologue about how he conducts the entire software engineering life-cyle and in particular, knows all about requirements gathering and specification development. I could hardly get a word in edgewise, but tried to tell him that I was talking about something more holistic than "reqs and specs" - I was talking about a bigger picture that involves much deeper work. No such luck - he repeated that yes, yes, he worked with customers regularly. I have no doubt he was sincere in his belief that he interacts effectively with users.

Nonetheless, as he continued to talk a mile a minute it dawned on me that here was a perfect example of missing the boat. His overly assertive interaction style caused me to rapidly lose interest in the conversation and revert to a surface level discussion - after all it was clear he wasn't really hearing me. He was completely unaware of the dampening effect he was having on his listener. Unless he undergoes a personality change at work, he probably interacts similarly with customers and clients. Will the code he develops be well targeted to address their unique needs? Will it be innovative in a way that is meaningful to them?

If you want to really understand a customer, a client, a student (current or potential) you have to stop talking and listen with more than your ears. This is sometimes called "active listening". A contradiction? Not at all - you can be incredibly active without moving, without talking, without forming premature conclusions or judgements. Active listening is how you find out what is really going on - critical subtext, or something that takes a while to rise to the surface, shows up through words, body language, intonations, and many other clues.

Active listening is a way of being - it is not something you turn on or off "when needed". Interesting and important information doesn't appear on cue or when you will it. Human psychology doesn't work like that. There are many skills and techniques you can develop to facilitate meaningful insights, but the moment you stop listening actively something critical will fly by and you'll never know it.

Test out active listening with a small experiment. The next time you interact with someone you don't know such as the guy behind the deli counter, your hair dresser, the woman whose dog wants to play with your dog at the park:

1. Talk less - let them do more of the talking. You don't have to pull a silent routine, but subtly encourage them to talk while holding back on directing the conversation as much as you can.

2. Resist coming to premature conclusions or drifting off on mental tangents ("What a boring job...why don't they use more modern cash registers?...I wonder how much money s/he makes?...did I remember to lock the car?...do those receipts really contain dangerous chemicals on them?). Just take it all in.

3. Listen with more than your ears. Be alert to any little voice inside that wants to point something out to you about this person's motivations and perspective. Register the information for later and keep listening.

What do you hear when you actively listen? Based upon your interaction, what have you learned about this person's perceptions and what is important to them?

Fun and Weird For Friday

2011-09-02T15:52:00.000-07:00

It's Friday, it is the start of a holiday weekend in the US, so I thought I'd share some fun things I found. Way back in the Dark Ages when robots first hit the commercial scene I was entranced by a review of one home robot that had a built-in set of sensors to detect life forms. The robot had a limited speech capability to make it friendly. The early models had some slight glitches; apparently one robot snuggled up to a toilet bowl (the size and shape somehow registered as sentient) and talked to it. Another robot used a heat sensor to get just a little too close to the fireplace, again thinking it was alive. But oh, I wanted one.

We have come a long way. I have eyed a Roomba, not necessarily because I need a robot vacuum cleaner but because I wanted to watch it interact with my cat. But now, things have gotten even better. Check these out:

RoboKing Triple Eye vacuum cleaner - it can spy on people, scope for dirt and you can control it via Smart Phone when you are stuck in a traffic jam and are bored to tears breathing exhaust fumes.

Bakebot: Plans for a robot to cook for you...this one needs some work before it goes commercial. I happen to prefer to be my own mad scientist in the kitchen. Especially while this device is still in the oven.

Play Rock Paper Scissors against a computer. You can play against a Novice or a Veteran. Then you can read what the computer is thinking. You will get sucked right into this one...really. When I played against a novice computer my results were: Win, Win, Tie, Lose, Tie, Tie. When I played against a veteran, my results were: Lose, Lose, Tie, Lose, Lose. The computer performed a complex seeming analysis of what I was thinking and then told me what 20,000 (or so) other people did that was similar to my strategy . When I played the Novice, I was actually trying to outwit it. When I played the Veteran I just decided to randomly wing it and it was quite engaging to see how the computer analyzed my winging strategy. You see...you can get sucked in. Look how much I wrote about Rock Paper Scissors! So if you have no plans for the evening...

I really dislike mushrooms but I had a lovely time growing little yellow mushrooms with Mushroom Life and listening to them go "eep" "eep" "eep"; the faster I clicked the faster went the "eeps" and the faster the little yellow things popped up on the grid. More smiles on your face.

You can play Mushroom Life seriously of course. But after the spy vacuum, the half-baked robot cook, and doing battle with the computer over RPS, it seems fitting to work on making music out of popping mushrooms.

Have a nice weekend ("eep").

Things to Think With: Crochet Hyperbolic Planes and Computing

2011-08-25T22:38:00.000-07:00

Do you sew? Knit? Weave? Crochet? Personally, I have rarely ventured beyond replacing buttons on shirts, but Sarah Kuhn, Professor in the Psychology Department at the University of Massachusetts Lowell, taught herself to crochet after being inspired to create hyperbolic planes by Daina Taimina's book "Crocheting Adventures with Hyperbolic Planes".

Sarah has been working for years at the intersection of art, sociology, computing and engineering education. This latest project is part of a new research area, part of her evolving investigation of ways to bring mathematics and computational concepts to life. When she first saw some of these crocheted hyperbolic planes she asked herself: are they more than models? Can these objects be used to discover things? To her, that is a key point for a successful learning environment.

The answer is yes. Creating a hyperbolic plane crochet 'object' (the best word I can think of, although it feels insufficient) provides opportunities to explore algorithms, patterns, emergent properties, and programming - for starters. How?

I asked Sarah to explain how it all works, and asked her to assume she was speaking to a completely clueless crocheter (as I am, having never even touched a pair of needles). She patiently stepped me through the "single crochet stitch", the basic stitch in crochet. She explained the ways this stitch can be used, with no other more complex stitches, to create an object such as the gray spherical object pictured above or the colorful object below. The process is indeed algorithmic. You start with a circle out of yarn and move outwards in a spiral one stitch at a time. There is also something called "increasing". I won't try to replicate the explanation for fear of completely butchering it, but suffice it to say, every creation is different because of variables (computing concept!) including how often you increase, the type of yarn, the quality of the yarn, the color, and the composition of the yarn.

Crochet hyperbolic planes provide a simple entry into the worlds of mathematics, computing, and analytical thinking in general. They are easy to make, fun, and small changes result in sometimes surprising outcomes. A little crochet tweak here and you have a different form of ruffle; another crochet tweak and the shape shifts. Another topic: Design patterns and the implementation decisions they lead to.

Highly portable, crochet hyperbolic planes are excellent conversation starters. Sarah summarizes a typical conversation:

Scene: The doctor's office. Personae Dramatae: Sarah in chair, Person Nearby in chair (perhaps bored).
Person Nearby: "What is that?"
Sarah: "This is a hyperbolic plane"
Person: "What's that?"
Sarah: "It is math"
Person: "Really? That's math! If someone had presented that to me as math in high school I would have liked it".
[Conversation continues....]

Voila. An aesthetic entrance into the world of the formerly abstract. More complex concepts wait to be tackled by progressing to a discussion of weaving; weaving has far greater complexity than crochet and an interesting history that we know includes the computational (ahem...Jacquard Loom?).

Fiber arts (which encompass sewing, knitting, weaving, crochet) cross cultural, age, geographic and social boundaries. In some societies they are associated with women's activities, in other societies with men's activities. As Sarah says "a STEM opportunity hiding in plain sight". Not surprisingly, she is developing several ambitious project ideas that will integrate fiber arts into a variety of classes and programs with the explicit goal of encouraging interest in STEM disciplines - computing included.

Sign me up. I wanted to reach out and grab one of these crocheted hyperbolic planes the moment I saw their pictures. Wouldn't it be fascinating and fun to explore the world of computing while creating one's own personal weird masterpieces of yarn? Stepping stones to complexity. Sarah Kuhn is demonstrating that the arts and computing have a lot in common.

Internet Voting Revisited: It Could Go Viral

2011-08-23T12:35:00.000-07:00

Quite some time ago I wrote a post on internet voting and it generated quite a bit of impassioned response, in great part on some of the computing discussion groups I cross-posted to. Computer scientists have some very strong opinions on internet voting.

Whatever you think of it personally or technologically, it looks like internet voting is coming. There is a really interesting new grassroots movement afoot. It reminds me (and probably will you too) of how the internet was first used to make one primary political campaign go viral (Howard Dean anyone?) - and now virtually all serious politicians recognize that the internet cannot be ignored if they want to win an election. Some use it more effectively than others, but no one brushes it off anymore as only for the "fringe".

There is a group called Americans Elect 2012 that is setting up an online voting system for the 2012 presidential primary so that people across the United States can pick the issues that matter to them and the people they wish to nominate. I heard an interview last night on the PBS NewsHour with 2 of the principals and it is very interesting - non partisan, and sounds like they are going full steam ahead with harnessing computing and the internet to get around the gridlock of our current political election system.

The group already has a presence in all 50 states and is working through the complex process, that varies state by state, of when and how they are legally permitted to operate.

Their system is in Beta, and you can check it out. The site I'm about to link you to includes, among other things, interview snippets with people from 5 states - people on the streets.

Technologically, what is cool about this is that it could very well work. They have apparently thought out how to harness the internet and to address what people are really upset about (according to national polls that were discussed on the news spot last night). The organization is not letting itself get tangled up in theoretical or philosophical or technical discussions about whether or not internet based voting is feasible, or a good idea - they are doing it.

Here they are: Americans Elect 2012.

If this effort takes off, it could radically change politics as we know it. What do you think????

Science is Rock and Roll

2011-08-18T22:22:00.000-07:00

I almost missed this, by not keeping up with NPR Science Friday. Last week there was a short spot on ... get this... rock and roll musicians plugging science. And not just on an NPR blurb but they are doing it on TV in order to hit a huge audience. The web page (below) says in big letters on it: "Who is Your Favorite Geek"? and I don't know how many times I heard, to the sound of background music "My Robot is Better Than Your Robot". And yes they say "programming" is a cool thing - science includes computing for sure and it gets you hopping...you can't help it.

This is so cool, I shall say no more, but send you to this web site to check it out yourself. Woo hoo!

Science is Rock and Roll

Computing and Studio Based Design in Industry, Fine Arts and Architecture

2011-08-09T19:46:00.000-07:00

One of today's most food for thought-ish ideas at the ICER conference (from my pov) started with the presentation of a paper by Chris Hundhausen from Washington State University entitled "Prototype Walkthrough: A Studio-Based Learning Activity for Human-Computer Interaction Courses" (HCI). Chris pointed out that studio models have been used for years in Architecture (of buildings and other structures) and Fine Art. The idea of experimenting with a studio model in computing courses is not in itself new. Studio courses have been tried in lower division computing courses and a few other places in the curriculum.

What really got my attention was when Chris, who worked for a few years at Microsoft Corporation as a Useability Engineer, claimed that industry uses a design model very much like the studio model and thus there was an added reason to teach computing in this way. His belief is that we should be able to take ideas from Architecture and Fine Arts pedagogy and apply them to the design phases of HCI pedagogy. My ears perked up. Another possible bridge point between industry and academia (the topic of several of my recent posts)? Architecture, Fine Art, Computing, Hi-tech industry...?

Chris broke down his study into great detail about the stages of design and how stakeholders talk to one another about design and several times referred back to industry practices.Very interesting and well grounded in details that sounded like they came straight from his industry experience.

Someone I was sitting with at my table referred me to another member of the audience who had experience in the studio model and a significant knowledge of design and Architecture and so, for another perspective, I went and spoke with this person. I asked her for ideas about how the pedagogical studio model techniques could be transferred from Architecture and/or Fine Arts to computing. To my surprise she told me in no uncertain terms that the studio model would *not* work in computing. She told me that the way a true studio model works is that the classroom is handed over to a professional who brings in a real project s/he is working on and the students work on it under the direction of the professional. The inverse I note, of sending students out to a client on a service project. In the studio model, according to my conversant, the professional comes to the students and the professor steps out of the way.

She claims this model will not work in computing because the cultures are very different between Archtecture and Fine Arts and that "you can't stand around a compiler and critique it". Is this true?

What do you think? A very thought provoking question. If yes, how? If not, why not?

Chris appears to believe (I'm doing some extrapolation here) that you can - or at least that there are significant fundamental tenets of the professional studio model that can be used in the design of HCI software.

Stretch your mind - can you bring a professional from the high tech industry into the classroom with a real project that they are working on and have them lead the class in a studio model inspired design process?

Programming, Body Language and Poetry

2011-08-08T16:15:00.000-07:00

I had the most interesting discussion (here at the ICER conference) today with a doctoral student from the University of California Berkeley: Colleen Lewis. She gave an overview of her dissertation work called: "Integrating Prior Knowledge Into Pedagogy". As part of her work Colleen provides students with code and asks them to talk aloud about the code. Colleen believes that successful students are integrating non programming knowledge from other fields into their programming. Her mention of the humanities got my attention so I went over and spoke with her and asked for some detailed examples of what she has observed.

Critical Reading Skills. Most of you have likely been involved in discussions of code or sat in when someone was describing code. Colleen told me she hears students not simply saying what the line of code is or what it does, but explaining it in terms of what it means in a greater context. She told me when she listens to successful students she hears a story. She used the words "narration" or "narrative" repeatedly. Although she didn't say it in so many words, what I was hearing / interpreting from Colleen's narrative was that as she listens to successful students she hears a story much like the one I am writing here. Not just a sequence of statements, or an algorithmic description, but a more holistic contextualized explanation. Interesting.....Have you ever thought about code as a story?

Gestures and Body Language. Colleen took American Sign Language in college and perhaps this is what disposed her to notice that when she asks students to trace code aloud, some students actively use their body as part of the description. For example they might speak like this: "n equals 1; ok, now n equals 2; now n equals three..." while using their arms to show the movement. Colleen demonstrated by starting with her right arm out, palm up on "n equals 1", then placed her left arm inside her right arm, palm up, then moved her right arm inside her left arm, then the left inside the right again, while explaining "they are saying and showing: 'the code moves from here [right arm/palm], to here [left arm/palm] to here [right arm/palm] to here [left arm/palm]' ". These students not only narrate with words, they narrate with physical movement.

The discussion of movement caused us to look up. There were several of us standing together; Colleen and I were in motion and two others were standing, listening, with arms crossed. We then observed how some people are more physically demonstrative than others. Colleen and I for example use our bodies a lot (even while furiously taking notes, I was not standing still). Two other people commented that they tend not to use their limbs as much when they talk...what might this mean for coding?

Watch people in action as they talk or listen - it is very interesting to tune into. Psychologists know about the messages body language sends - it isn't something we talk about as much in computing.

Poetry. This is where conferences are such wonderful synergistic experiences. I asked Colleen for yet another example and she started describing a process she observes where programming students read a challenging chunk of code, rephrase it in their head, re-read it, and re-read it, and think it through some more. At that moment another conference participant, Nanette Vielleux from Simmons College, spoke up to say that the process sounded like studying poetry when you are having trouble with a poem. She suggested that perhaps some techniques used to teach poetry could be used to teach programming. Now that is a fascinating idea.

I got an immediate visual of a page of code in a language I don't know well sitting next to a page of poetry from a writer whose style is alien to me (I often find poetry challenging). I have found that if I read poetry aloud several times and roll it around in my head I have a greater chance of making personal sense of it. If some students successfully use the same process with challenging code....wow. Cool idea. I have no idea how poetry is "taught" in the classroom. Wouldn't it be interesting to apply selected poetry pedagogy to the study of existing code and see what happens?

Off to ICER - What Shall I Find?

2011-08-05T17:20:00.000-07:00

Saturday I take a red-eye to Providence, Rhode Island (east coast USA) for the ICER conference. This is a small, intimate, very interesting conference focused on computing education research. The papers are generally quite interesting, have been through a blind peer review, and are eventually published in the ACM Digital Library. There is a doctoral consortium to encourage up and coming researchers in the field. Quite a few years ago I was a participant in the doctoral consortium (several times) and I remember it fondly - although some of those faculty discussants did their best to politely but firmly pin us to the wall until we answered their questions!

There appears to be plenty of work being presented related to my professional work in assessment/evaluation and in learner misconceptions. Beyond looking at that work, this year I am more than ever interested in ferreting out any active research involving interdisciplinary and social issues in computing. So far, I see in the abstracts a lightening talk about work in the HFOSS Project (the Humanitarian FOSS Project: Building Free Open Source Software for Society).

None of the full length papers jump out at me just from the titles (I have not yet obtained access to them because of a s/w glitch) however I know that several of the authors are involved in socially relevant work and are quite innovative people.

I intend to go on the hunt and track down all the interesting work and incubating ideas I can find and report on them here.

Stay tuned!

Efforts on Behalf of K-12 CS Emphasize Interdisciplinary Nature of Computing

2011-08-01T21:58:00.000-07:00

Speaking of innovation and social impact, it all starts young - what you learn as a child influences your lifelong interests and attitudes. We know that. That means that if we want computing to be used in creative, innovative, socially beneficial ways, then computer science has to become an integral part of the public education system. We need more of the types of people and organizations I periodically profile here who combine their personal passions with their profession to use computing for good.

In case you don't follow the news about the ongoing efforts to obtain inclusion of computer science in the K-12 science education core curriculum nationwide, I'd like to excerpt a few sections of a letter sent by the ACM, CSTA, CRA and NCWIT to the National Research Council (NRC) in response to NRC's draft release of "Framework for Science Education". This framework provides a strong policy statement about what K-12 students should study in high school and has a strong influence on curriculum development and priorities in high schools across the country. As you may well know, computer science has long been neglected, misinterpreted or misplaced in K-12 education. Those of you familiar with the tough battle being waged to obtain acknowledgement of the importance of studying computer science in high school know just how hard many people are working on this issue in Washington DC and elsewhere. The authors of the letter to the NRC state "We recommend the Framework for Science Education be amended to include computer science as a fifth major disciplinary area".

I cannot recap the whole story here, but I want to pull out some excerpts that make it clear how well the above authors understand the interdisciplinary and socially important nature of computer science. I was very glad to see these included in the letter to the NRC. Brackets contain explanatory text added by me. Bolded text was added by me for emphasis.

"Taken together, the Framework and the CCSSI [Common Core State Standards Initiative] arguably represent the "core" of what students need to know in the science, technology, engineering and mathematics (STEM) fields. Considering the tremendous influence that computer science has on worldwide economic growth, as well as its effects on modern culture and innovation in all areas of science, it is troubling that neither of these standards-setting initiatives view computer science as a critical and necessary element of STEM education in the 21st Century"

".. computer science...is a discipline that not only stands on its own, but also contributes innovation to all of them [mathematics, engineering and the sciences]".

"Ultimately, no other field is more central to the digital revolution that is sweeping commerce, society and all fields of science. And no other field will give students the critical computational problem solving knowledge and practices they will need to be college- or career- ready, regardless of their ultimate occupation."

"An engineer using a computer to design a bridge must understand how the maximum capacity estimates were computed and their reliability. An educated citizen using a voting machine or bidding in an eBay auction should have a basic understanding of the underlying algorithms supporting such conveniences, as well as the security and privacy issues that arise..."

"Computational approaches are essential to the discovery and understanding of the fundamental rules that govern a wide variety of systems - from how ants behave to how stock markets behave"

"..computer science is increasingly driving discovery in all areas of science."

and here is the kicker:

"If the final Framework does not encourage students to study computer science or understand its core ideas, who will...lead the way to addressing the fundamental challenges we as a society are facing, such as chronic disease, an over-extended energy grid, and a struggling aviation system running on 1970s technologies?"

followed a bit later by:

"...the failure to recognize, define and support computer science as its own field and content area within STEM education will exacerbate an already growing workforce and innovation crisis..."

Computing is as important to society and has the power to benefit society in an incredibly powerful way as any other field someone could point to. In many cases more so. Many of us, especially in the computing field, "get it".

A continuing question is: how can we help everyone else to "get it"?

Useful Link Not Already Listed:
The ACM response

Computing Technology in My Courtroom

2011-07-28T13:02:00.000-07:00

Many people have been asking me about the jury trial I spent most of the last two weeks on. Two weeks of being able to say only "I'm on a jury trial", especially as the trial was pretty intense, was challenging. Interestingly enough, this particular trial was trying out the use of computing technology in a way they hadn't done before so we were guinea pigs. What was most interesting to me was that the technology itself wasn't particularly unusual or radical, but the people in the court were using it for the first time and I got to see how they chose to use it, what worked and didn't work, how it contributed (or not) to the trial process, and how everyone (jurors, judge, lawyers, witnesses, plaintiffs, defendant) reacted to it. There was a tech guy in charge and I wasn't supposed to talk to him (or anyone else). I wanted to find him after the trial was over and pick his brains but he had vanished by the time we were out of deliberations. Too bad.

The trial was a messy complex personal injury lawsuit (now I am allowed to say anything I want). The "facts" were not at all clear. Enormous sums of money were at stake and people's lives on all sides hung in part, in great part, on the credibility of witnesses and the technology they worked with.

A key issue was whether or not one of the plaintiffs had suffered a particular back injury, and what options (surgical or otherwise) were warranted if he had. Spinal injuries are very complex, more than I ever could have imagined. Surgery can involve pulling out all your innards and laying them...somewhere... in order to get access to the spine. Ew. We the jury heard DAYS of testimony from doctors and surgeons about the spine and soft tissue injuries and viewed shot after shot of digital imaging tests including MRIs, X-Rays, Discograms... The courtroom set up a system whereby there was a giant screen TV in front of the jury box; the judge had a monitor, the witness on the stand had a monitor, the plaintiff and lawyer tables had their own monitors and there was a tech guy in the back controlling who could see what and when. Sometimes control was given over to either of the lawyers. Cables ran around across the floor.

Sometimes they wanted all of us to see a Discogram image for example (a somewhat controversial procedure where they stick 8 inch long needles into your spine and ask if it hurts). Other times they wanted all of us to watch a 3D MRI or a simple document display (usually of endless spreadsheets of mind numbing medical or financial data). The images were pretty interesting actually, especially as I have done research into digital image use in medicine and now got to see it put to use in a legal setting. Other times they wanted the witness to see something along with the judge and lawyers but not the jury. Basically, pick your combination, and at some point in the trial any given subset of people were supposed to see it.

Sounds easy right? By the end of the trial they more or less had it down. Here are some interesting highlights of their learning curve from a usability perspective in the juror box.

The giant TV was on a stand about 6 feet high. Hard to move, trailed a long cable and had to be shoved around the room without tripping over other cables. One of the lawyers tripped on a cable early on. (not badly, but it threw him momentarily off stride). The TV blocked some of the jury from seeing the witnesses (not good) and blocked the judge from seeing some of the jurors (not good). We paused while they figured out where to best put the TV. The lawyers and judge could not see what displayed on the juror TV without walking around in front of it. This led to some early significant "oops" moments. For example, one witness was looking at his screen (along with the lawyers and judge at theirs) describing in great detail something about the spine and we jurors were completely in the dark about what was being referred to. Eventually they figured this out and some time was taken to figure out why the connection wasn't working. We started over again.

In another case, the plaintiffs' lawyer thought we were all looking at some emotionally laden photographs the witness was describing, however we couldn't see them. There were quite a few photographs and it went on a while. It turned out that our not being able to see the photographs was a good thing because the lawyer hadn't requested and obtained permission to show them as exhibits (not good). Near the end one picture momentarily flashed on the screen. Our generally genial judge looked rather annoyed when all this came to light moments later. A backroom huddle between the judge and the lawyers took place and I suspect some strong words were exchanged. In the end we saw none of the photographs and ignored the one we had seen. Had we been shown all those photos which were eventually ruled as inadmissible I suspect there would have been some truly severe backroom lecturing by the judge. As it was, both lawyers were pissed off from what I could tell from their faces, though nary another word was spoken on the matter.

Then there was the witness whose monitor on the stand stopped working and was asked to come down to the big TV. He stood smack in front of it, back to the audience (ever had a teacher do that? :) and had to be gently and repeatedly asked by the lawyer to move out of the way so we could see what he was talking about. The lawyer actually helped him move at one point.

One time the judge's monitor stopped working and they tried to swap it out with the witness monitor which was a few feet away. The cord wasn't long enough. Our very cheerful and friendly judge disappeared under his bench - one moment he was there and the next moment he was gone. I had glanced away at the tech guy and when I looked back - no judge. Huh? Moments later he popped up, in black robe, happily holding a cable and cheerfully announcing he had figured it out. It was an amusing moment in another wise not at all happy trial situation. We appreciated every rare light moment that came our way.

There was the first tech guy (not the one referred to above) who fell asleep sitting at his little table at the back of the courtroom. The lawyers had been in the habit of requesting him to do something without turning around and it was only when there was no response that we all noticed the poor guy snoozing. Probably bored to tears by all the talk of the T4, L4-L5 spinal disks, protuding jelly globs of spinal material, endless lists of complicated drugs that I had never heard of (and hope to heck never to have to take after hearing about their side effects) and the gorey details of spinal disk replacement vs. disk fusion vs. inserting tubes around the spine full of pain medication....(there was more but I'll stop). After that we got the second tech guy.

I was pleasantly impressed with the grace and patience with which all the court personnel handled the technical experiment. It must have interfered with their usual mode of doing business and caused them to do some cognitive context switching when they least wanted to. From a juror perspective I wonder how they conducted such a trial before? All those complex digital images, some rotating and zooming. The computing setup was very effective in presenting the information under discussion and made it quite clear why there was lack of medical agreement on various procedures and possible outcomes. One variable at least was made less abstract and easier to evaluate in our deliberations.

As a passing note, I want to comment that this experience, in spite of the time it took up and the emotional stress it induced for all the jurors (we compared notes extensively afterwards) was absolutely worth it. My perspective on our trial system has risen significantly - everyone took it very seriously, worked hard together and we did our very best in deliberations. It was a fair process. If you haven't been on a jury trial I suggest you take advantage of it when given the opportunity.

A Tale of Two Valuations: Academia Next

2011-07-24T15:22:00.000-07:00

I initially thought this post would be a piece of cake compared to the previous post about the corporate perspective. Not so. Perhaps because of my extensive academic experience I am far more aware of the variance of how professionals are valued in the world of higher education. So I have been looking for points of common ground within academia...I am almost afraid someone will throw a rotten tomato at me because I know too much (I've been reading a murder mystery, where the person who knows too much often comes to a messy end).

To state the obvious (to academics at least) there are the three classic areas of valuation for faculty: Teaching, Research and Service. Service (pretty much anything not teaching or research related such as committee work, performing outreach or being a student adviser) can safely be said to come last in the pile. Do no committee work and you will get dinged; do too much and you will get dinged (I know someone who was denied tenure because he was told he performed too much service work). So the trick is to find the middle ground according to the culture of your department and institution.

From there is gets murkier.

Teaching: In some institutions this is virtually all that counts. But how it is measured varies widely. In some cases, it is all about teaching evaluations. Period. Get those numbers up and get them high or else. The pressure can be intense, and in extreme examples there can be a completely predictable desperation to "please" students above all else. In my experience, this is not the norm, and is incredibly destructive to the learning process. More often, in a teaching oriented institution, evaluations are important, but only one indicator of how a faculty is evaluated. More sophisticated methods of assessing effective learning are used. And by effective I'm not talking statistical evaluation; I'm talking qualitative evaluations. That is healthy imo. Institutions with a well rounded process for evaluating teaching can produce amazing students who go on to do amazing things inside and outside the classroom and after graduation. And the faculty feels professionally successful and appreciated.

Research: In some institutions this is virtually all that counts. Again, the worst case scenario is where not only are publications counted (literally) but the venues for publication are ranked. If you don't get into "the top" pubs, forget it. You are toast. Even within computing, there are disagreements as to what counts as a quality publication venue. Then there are grants. Worst case scenario, you need a fixed number of grants and big dollars - millions would be nice. Not healthy, as there is only so much money to go around and that sets up a system of guaranteed winners and losers regardless of quality. Very much like using a normalization curve in grading. Something I never used and never will because it has all sorts of negative side effects that many educators are well enough aware of that I won't repeat them here.

Quite a bit of gloom up in those paragraphs. Now to inject a positive perspective. BALANCE. It is all about balance. The original idea behind Teaching, Research and Service was to promote balance. Some of all three are needed from every faculty. Many institutions, although they do by design weight teaching and research differently, maintain a healthy balance. What are the factors that indicate successful teaching in such situations? Each professional is evaluated in the context of both institutional need and known pedagogical / cognitive learning understandings. Other factors come into play to varying degrees depending upon the context: local needs, student needs, etc. What are the factors that indicate successful research? Very similar actually. The institutional needs and established understandings of rigor in scientific research lead to an evaluation of individual contributions (reminder here that we are talking computing and related areas. I can't speak to areas such as the arts and humanities). Grants in these institutions aren't just about how much money is brought in, but about the effect the work is likely to have on science, or in the case of educational research such as computer science education research on the discovery and dissemination of improved teaching and learning theory and application.

It feels like I've short circuited my comments, but that comes from knowing too much.

A summation might be: for faculty in academia professional valuation is based on teaching, research and service, and in a healthy environment there is a contextually appropriate and healthy balance. Value is not just numbers, nor is it vague and undefinable.

I feel like I'm stating the obvious, but that is only the case if you are an academic reading this. Based upon some of the comments I received to my last post about valuation in the corporate world, there are many to whom this post will be news.

One of my next tasks will be to see where I can locate opportunities for common ground.

But first, I'll ask you to graciously do what you did before, and provide your perspective on:

1) What can you add about how academics in higher education are judged to provide value to their organizations? What can you add that is concrete - i.e. can be said in very concise form?

2) Where do you see common ground between between corporate and academic valuation of professional contribution to their organizations?

(I think we have all heard about the areas where there is supposedly no common ground. Let's look for the positive now).

A Tale of Two Valuations: Hi-tech Corporations First

2011-07-17T14:53:00.000-07:00

Sometimes you have to hit a problem head on and just lay it out there. I've been thinking about the best way to discuss some of what I've been hearing and learning on and offline, in public and private communications, as I tackle this question of corporate and academic valuation of a professional's contribution. As I stated earlier, I believe there is more in common than may appear on the surface, but as I discuss this topic with people, I am not yet finding the concrete information I want to ferret out. I'm not ready by a long shot to give up. We need this information to be able to bridge the cultural divides and learn from each other. So I have been debating how to get away from the more abstract and/or philosophical discussions and into the reality of day to day existence.

I am going to write some of what I have heard and do it from two angles. First from a corporate angle, and second, from an academic angle. And both, I might add, based also upon my experience in both arenas.

First, perhaps the more challenging for me: the corporate angle. Although I have worked in the hi-tech world, more of my career has been in academia. Let's stick to the realm of hi-tech and management level positions - here you are likely to find more interdisciplinary activity, however defined, and innovative companies recognize that. Here goes...

I have been told that, from an American corporate perspective, a person is valued primarily on their monetary contributions. Irregardless of where they are coming from (professionally). To be more precise, here is a close paraphrase of what someone said to me:

"you have to show quantitatively how much $$$ you have brought the organization; you have to show how much $$$ you saved the organization; you have to show the resources (physical) you obtained for the organization. That is what they expect. That is what they want to see. That is what they care about. That is what matters".

Is that IT?
Is that ALL?
Is that REALLY the only thing that counts or the thing that weighs far heavier than anything else?

Is it a fact that no matter what else one may have accomplished, that if one can't show precise fiscal contributions one is not highly valued?

This question is burning at me when I look at the question of professional value from the corporate angle. If the answer is yes, I'm feeling rather uneasy. The implications for bridging a cultural divide with academia become more daunting (but still not impossible my optimistic side says).

So let me put it out there to those of you in corporate hi-tech, especially if you have held or currently hold, a management level position of any sort.

Do you agree with the above statements about how you and your peers are valued? If you agree, are you ok with this or how are you trying to change it? If you do not agree, or if there is more to it, then what else in your experience really counts?

Random Weekend Thoughts About Creative Computer Use

2011-07-10T22:33:00.000-07:00

I'm going to lay off the super serious stuff this evening as I have a little list of "items" ripe for a creative computer scientist to evaluate.

A GPS system might have been useful for the small child I saw this afternoon on the beach who was happily walking about a mile away from his parents. My friend followed the toddler, who was totally unconcerned, and with the aid of a lifeguard got him back to his mother. Her only comment about how far away her kid had wandered on the packed beach was an unconcerned "there are a lot of people around". Who do you think most needs the GPS system? a) the child b) the mother c) the lifeguard d) all of the above e) none of the above ?
I have jury duty next week and San Diego Mass Transit's software connection to Google Maps is determined to route me to either Tijuana Mexico, Monterrey Mexico, or Paraguay. Where do you think the problem lies? (I truly believe I will not be crossing the international border tomorrow, regardless of what the software system insists)
A friend was very concerned about the fact that software was not being used to more efficiently assist in food redistribution to the homeless. He described in great detail what such software would look like and asked why no one had created it. I realized as he spoke that the software to do what he says does exist, but is used in other applications. Last week I spent a good hour with a visiting family member at the harbor watching a Dole (as in bananas and pineapples) tanker unload box after box of food and load them onto trucks off to destinations all over the western US. The plaque on the harbor walkway briefly described the complex distribution system used to get those bananas I eat every morning from Central America effectively and efficiently and in just the right state of green to all the places they have to go. What would it take to get such a system into the hands of large scale non profits doing essentially the same thing?
While I am sitting in the stuffy courthouse waiting room (NOT in Paraguay) I am going to be on the lookout for just how computerization is or isn't being used...and how it could be. I might even get a bit inquisitive and ask questions. This would not be unusual behavior for me. As long as it doesn't result in my landing on the other side of the court system than was intended.

Have a nice Monday everyone. Think creatively about good things.

Computing and the Reduction of Global Conflict

2011-07-06T16:32:00.000-07:00

I came across some creative examples of university faculty who are using computing for societal benefit. I located these faculty through podcasts produced out of New Zealand by "The Sustainable Lens". One faculty member is taking an empirical approach to studying factors that promote peace.

A broadcast from 5/13/11 profiles the work of Juan Pablo Hourcade at the University of Iowa. Hourcade earned his doctorate in Computer Science with a focus in HCI. One of his goals is to convince people in the computing field that computing technologies can be used to reduce global conflict. He recognizes that a key to making the study of peace acceptable is to apply empirical scientific methodologies to the research. There are many aspects of this work. One of the most fascinating is the mining of masses of data to identify factors that increase or decrease the chances of conflict. These data are drawn from a myriad of sources including: demographic, historic, financial and economic, supply chain analysis, social and human condition, gender and inequality, environmental stress, social stress, and consumer behavior data. The power of computing is also leveraged to provide transparency of connections between individuals and transactions.

Computing is used to identify the factor(s) that matter the most in supporting or reducing conflict and are drawn from contemporary and historic sources - some going back several thousand years. Predictive modeling has a role as well. Visualization renders complex results easier to understand (there is a small pun in there by the way). The precision of computing provides the ability to zero in on the interaction of critical factors, providing the all important empirical (rather than philosophical) basis for making large scale policy decisions. Hourcade also discusses at some length implications for personal decision making.

Using known information about human psychology, Hourcade talks about how social media can be actively used to promote compassion - which he claims psychology has shown is key to reducing or altogether avoiding conflict. Social media can be used to bring together people who might see things from different perspectives. Psychology refers to this as reducing personal distance, a proven highly effective method of promoting the "humanization" of those who appear threatening but do not necessarily need to be so.

Although he only touched on the topic in one sentence during the interview, my ears perked up when Hourcade said he saw a role in conflict reduction for electronic voting systems. As I have learned through researching this topic for my book project (here is an earlier post I wrote about internet voting), electronic voting is incredibly controversial and often promotes passionate conflict! I wish there had been more time in the interview to pursue Hourcade's view on the role of electronic voting.

Hourcade made the interesting observation that there has been a significant amount of research in the computing field into ways to improve warfare and very little research aimed at reducing it. Good point.

Why not put the power of computing to work for the cause of global conflict reduction?

Is there any plausible reason not to pursue this line of research?

What ideas do you have about why computing research for peace has not been explored as much as say...economics? (Much of the data comes from the same sources.)

Assessing Value in the Corporate and Academic Worlds: An Interdisciplinary Problem?

2011-06-30T20:45:00.000-07:00

During all of these ponderings about innovation and interdisciplinary computing I have been working with the question of where interesting ideas coming from the corporate world can (should? do?) apply in the academic world. Sometimes the cross over seems quite reasonable with a little twist in thinking, as in this, a summative statement from The Innovator's Dilemma book (the past 5 or so posts, in case you haven't been following the conversation):

"...historically, disruptive technologies involve no new technologies - rather they consist of components built around proven technology (ies) and put together in a novel product architecture that offers a set of attributes never before available".

It only takes a few word changes to see how this applies to interdisciplinary computing. I bet you can figure it out if you have been following this conversation (can you?).

A larger question that looms over me now, is - just how far and in how many directions, can experiences of successful or unsuccessful processes in the business world be applied in academia? And conversely, what can the corporate world learn from successful and unsuccessful processes in academia?

On the one hand the cultures are vastly different. On the other hand, I am becoming convinced that there is a lot that can transfer from one to the other. Because my reading came from a book about the corporate world, I was looking at how the academic world sometimes fits the author's theories of successful "product" innovation.

I am equally curious about how understandings of success and failure in academia can be useful to corporate success.

There are a lot of hard questions when you start from scratch. I'll start with a very basic one: the concept of "value".

The corporate world often places value upon monetary contributions (Person X saved the corporation $Y by doing XYZ, or Person X brought in $Y dollars or Z physical resources to the corporation). Lately, I have been asking some professional acquaintances how they would place "value" upon academic contributions quantitatively.

I was not surprised by the reactions I have been receiving, which show just how differently "value" is determined in higher education and in corporate America. The more difficult I find it to try and bridge this cultural divide, (I'm starting to think of it as an interdisciplinary computing problem of a new sort) the more I want to do it.

How can the academic and corporate worlds arrive at a common understanding of value that does not involve one unilaterally imposing its "definitions" on the other?

How is VALUE going to be defined?

If you are an academic and you had to express your "value" to a corporate executive in a way they would appreciate, what would you say?

If you are in the corporate world and you had to find "value" in an academic's career in a way that acknowledged their worth honestly, what would you say?

Ideas about these questions could lead to a really productive conversation.

What is Innovative Interdisciplinary Computing Anyway?

2011-06-23T19:54:00.000-07:00

So I promised to write about innovation - what it is, how to identify it. In particular, with regards to interdisciplinary computing. The more I have pondered this issue, the more it feels like a trick question.

Innovation is something unusual, different, new - pick your vocabulary, but the basic idea is that it is something no one has thought of before. Now there is successful innovation and unsuccessful innovation, a distinction that sometimes gets forgotten. After all, there are plenty of innovative ideas that don't gather traction. Purple star shaped twinkies anyone? Some ideas are unique, but unlikely to gather a following.

It is easy to identify an innovative idea in retrospect. Interdisciplinary computing programs and activities such as I have discussed across many blog posts provide some excellent examples. Pattern recognition and computational emotion, computational journalism, bio-informatics, Charles Babbage in the front seat of your car. Successful innovations eventually mainstream themselves. For example, Bio-Informatics as an interdisciplinary field is becoming perceived as mainstream. But it wasn't originally - not when I was in grad school not tooo many years ago. Conversely, the talking Babbage GPS has a ways to go before we all have one in the passenger seat. Assuming we ever do.

When each of these areas of innovative computing appeared they were probably only recognized as interesting by a limited number of people. That is the nature of true innovation - if everyone could think of it then it wouldn't be innovative. It is easier to discuss what successful innovation is using past examples than it is to identify it at the moment of inception. (hence the feeling of a trick question)

For quite a while interdisciplinary computing as a concept didn't exist. It was (and in ground breaking areas arguably still is) considered a strange term. Before we recognized the idea of equal contribution of two fields to create a new creative field, we tended to think in terms of: computing; other field; applications of computing in other field.

The whole idea of interdisciplinary computing was very innovative. It was disruptive to traditional computing as evidenced by objections, denials, ignoring, "it isn't real computer science" types of reactions. The Innovator's Dilemma book I have been jumping off from for the past several posts calls this being "trapped in reactivity" - perfectly normal, predictable, human, and a great way to miss the boat. To not recognize the force of merging fields until they are upon us.

Interdisciplinary computing on a high level is becoming mainstream and the innovations are occurring within the divisions - what new fields will emerge and gain traction? What do we need to be on the look out for?

We can't rely on psychic powers to spot significant innovative potential in interdisciplinary computing. However, there are a few guidelines to identifying these ideas if we continue to follow the theory presented in The Innovator's Dilemma. As we cruise along in our professional lives, we can keep alert to changes around us and ask questions.

1. Is there a problem? In other words, is something not right? For example, there has been a "problem" for many years with declining interest in studying computing in school (at any level) and an increase in computing savvy students choosing to study other fields. We knew that a long time ago. It can take a while, and it did I believe, for the severity of the problem to be acknowledged - and this is "the real problem". Seemingly logical hypotheses occupied our energies: "enrollments are down because of the booming economy and thus students don't need a computing degree to get a job in a computing field" or "enrollments are down because of the poor economy and the perception that all the computing jobs are going overseas". The economy definitely has an effect on computing enrollment - no argument there. However it can't always be the economy! If that were the case, we could all throw in the towel, because the economy will ALWAYS be either good or bad or heading between one and the other!

So. First: recognize a problem. Second, recognize when the common responses may be reactive and not fully understanding the problem.

2. Do I understand the problem? Really understand the problem? If you aren't sure, how do you come to understand it? You don't run a lot of surveys and focus groups (so goes the theory) and ask people what they think or want. Instead you watch what they do. In our example, we would have watched and seen that students were going to study biology/law/engineering/economics (whatever) and learning the computing they needed for that field through those studies, or on the job. Taking it one step further, watching many of those people would have shown that many of them *enjoy* computing though they might have said otherwise if you asked the question. This is still the case: many of the cross over people don't consider themselves computer scientists but they thoroughly enjoy computational thinking and using sophisticated computing skills. Hmm.... Realizing that early on might have triggered a different way of thinking about how to tackle computing enrollment challenges. Many in the computing community are now understanding the problem and taking action. The truly innovative ones recognized it early and jumped on the opportunity.

3. How can I view the problem as an opportunity? Once you understand, really understand the problem, look at it as a chance to think outside the box, take risks and do something really different in response. Be prepared to learn as you go - as many successful interdisciplinary computing programs have in fact done (here was one nice example I profiled a few months ago). The challenge/opportunity includes searching out the market (substitute: students) for your new idea rather than trying to convert the existing market (substitute: students who have expressed interest in computing but not followed up). In our example, that might mean looking for the students who demonstrate through their actions that they are multi-disciplinary by nature and interested in the intersection of fields. Many successful interdisciplinary programs have done just that: attract people who are deeply interested in subjects that appear unrelated to computing.

In other words: look for the direction that people are already going (into biology/law etc) and aim your program or project at them. They might very well love your idea. And if you don't succeed the first time, try again - plan for this. Keep it simple. Assume you won't get your program or project right the first time and reserve resources (people, time, energy, money etc) for re-tooling and re-tooling. Acknowledge you don't know where you will end up other than that you will end up somewhere new where there is a need now. Not sometime in the future.

4. How can I view the plan's so-called weaknesses as strengths? There will be doubters and the weaknesses of your interdisciplinary efforts will be pointed out to you. Turn it around. Because the weaknesses may well be unrecognized strengths - that is part of what makes the plan innovative!

Reading The Innovator's Dilemma has been one of the more fascinating and eye opening ways to look at computing, whether in industry or academia. Interdisciplinary computing is a perfect ongoing case study to test the book's ideas and perhaps move computing forward in new ways.

Might "Silo-ing" Be a Good Thing for Interdisciplinary Computing?

2011-06-20T21:07:00.000-07:00

Two questions about innovation and interdisciplinary computing are on my mind at the moment (continuing my conversation from the last 3 posts). One question is "what is innovation"/"how does one identify innovation" and the second is "How does one support innovation"?

I'm going to tackle the second question this time, and the first question in the next post. In a comment to my last post Jim L. spoke about the changes that have taken place at RIT over the last decade, and as I replied, I see a lot of innovation at work in the diversifying and splitting off of related computing degree programs.

The approach that RIT appears to have taken (not being privy to internal institutional decisions) in some ways fits with one of the primary tenets of how to nurture and succeed with truly innovative change (the book refers to these changes and technological advances as "disruptive"). The claim is that in order to succeed, an organization must branch off into a separate organization the process, resources and values needed to make the change fly. Sometimes the change is geographic but whether physically remote or not, there are firmly established boundaries drawn between existing institutional culture and the development of a new culture for the innovation to flourish. So when RIT (and I again emphasize that I am speculating here) broke off its computing programs into different areas run by different faculty, I would hazard to guess they were in effect creating new cultural structures. The fact that the programs were very successful, and "students are pouring in the door" reflects doing something seriously right - the Innovator's Dilemma (ID) book is littered with examples of organizations that attempted to create innovative change and failed because the prevailing cultural norms of doing business impeded the change.

Now, where I am particularly curious is Jim's comment that the groups are silo-ing - and that this is a problem. We traditionally view silo-ing as negative. However, from the theoretical stance of the ID book as I interpret it, this behavior may be a positive. Research and case studies in the book point to example after example where initially separate organizational boundaries were initially successful but flopped when forced by external pressures to re-merge into a larger or pre-existing organizational structure.

Let me be heretical for a moment: Is "silo-ing" in fact a way to maintain healthy boundaries for innovation?

BUT, and I just throw this out there - intended as a thought that applies well beyond any one school - can silo-ing be viewed as something different? What if we alter our assumptions of what is "good" and "bad"? Just as "traditional ways of doing business" sometimes fail at supporting innovation, and thus one has to re-evaluate what is "good management" in those contexts, is it possible that "silo-ing" or the separation of innovative interdisciplinary groups is a productive thing to maintain?

Following that thought, if successful separate organizations (in the academic departmental/major lingo this would mean degree programs) succeed because they split off and form their own values, processes, resources => culture, is maintaining that separation perhaps a positive event?

There is a wonderful table on page 177 of the ID book, that I don't dare scan in, for fear of copyright violation, but it lays out really nicely the ways to fit the requirements of an innovation to an organization's capabilities (note: not the same as the people's capabilities who work in that organization). It is worth looking at, because there have been other educational institutions that have succeeded (and failed) in similar innovations and I found the insight gained from studying this table fascinating.

Before I leave off on this post, I want to point to two other educational organizations that are following the most important approach to supporting innovation laid out in The Innovator's Dilemma: creation of a separate protected organization.

One is well established, one is just getting off the ground.

The Rose-Hulman Institute of Technology created a separate entity called Rose-Hulman Ventures, a think tank and incubator of sorts that involves students and industry in collaborative efforts to spark innovation and entrepreneurship (disclosure: I used to work at Rose-Hulman). Ventures, as it is called locally, is in a physically separate location from the main campus, and operates on a very different model than the academic programs. They have had some noteworthy successes.

A very new venture, in the early stages of development is the creation of graduate studies in Wireless Health through the school of Engineering by Case Western Reserve. Case Western is located in Ohio. This program is being set-up in San Diego. You might say (devil's advocate speaking here): "what? a whole program in wireless health?". That would be a typical response from an establishment pov to a radical risky venture - according to the theories of why innovation sometimes gets shut down. On the other hand, they are creating a clear boundary (at least geographically) between the main campus and the location of this program. Now, whether this program succeeds will depend upon many other factors besides location - as we have been discussing. But it is a very interesting example to watch develop and see what happens.

Did Academic Computing Overlook a Big Threat to Its Sustainability?

2011-06-15T23:52:00.000-07:00

I'm going to go out on a limb and field an idea for your consideration. It may be provocative but I'm going for it because it is worth serious evaluation.

Take 2 related and heavily discussed issues:

1. What "is" computer science? The verbal wars that have been waged over this question.....yikes. Especially every time a new set of ACM/IEEE curricular guidelines are developed. I (and possibly you) have heard people publicly go for the jugular defending one point of view or another.

2. Why do enrollments in computing programs continue to have high attrition, and a problem attracting students in the first place - especially so-called "under-represented" students? By the way, to state the (hopefully) obvious, computing students overall are under-represented from the pov of numbers in program compared to any one of a large number of other fields.

As I continue to barrel through the book The Innovator's Dilemma (see last two posts) I wonder:

Is it possible that part of the reason computing struggles for legitimacy among students is because the faculty did not recognize soon enough an increased use of computer science in other fields?

Is it possible that computing faculty did not recognize the deeper and deeper incursion of computing into other fields for what it was to become - a serious curricular challenge?

Is it possible that faculty were focusing so heavily on what they had been doing all along, and focusing innovation on traditional areas within the discipline, that they simply were unable to recognize a need to embrace radical curricular and research change and maybe (out on my limb here for sure) a radical re-evaluation of the definition of computer science?

These ideas cross my mind because:

The Innovator's Dilemma demonstrates case after case where established companies (substitute "academic departments") steadfastly focus their innovations on existing customers (substitute "traditional ideas of what a computing student should be interested in and good at"), such that they do not recognize "entrant" companies (substitute "other departments that increasingly rely on computing to support their cutting edge advances") as threats until it is too late and they lose most of their business (substitute "students").

Anecdotal Evidence: I have heard many discussions (as I suspect have you) where the claim is made that computing used in another discipline is "not real computer science". Hence not to be seriously worried about.

Is it possible that computing programs got into the position they are in with regards to enrollment problems because they did not recognize the nature of future competition?

Maybe yes, maybe no. I'm not going to step into that tar pit.

More important: The historical answer becomes moot if current reality is that other disciplines attract more students than computing attracts, and students find those other disciplines more tractable, and if along the way students acquire enough computer science skills such that they go on to successful careers where computational thinking is required. Minus a degree in computing and all the critical skills and experience brought with it.

If you have not read the The Innovator's Dilemma and know this already, I want to strongly point out that in no way does the above imply companies/departments were doing anything "wrong". In fact, the theory goes out of its way to show how successful corporations that were eventually over-run were following well accepted good management practices and "doing all the right things". That is much of what makes the whole notion of good management missing the boat so fascinating.

To transpose the situation onto computing departments would mean that computing departments were playing to their strengths, following established understandings of what success in computer science teaching and research entailed, and working very hard at attracting those students who had historically been successful. In point of fact, there is a lot (a LOT) of pressure on successful corporations (and by extension disciplines) to keep doing what they have expertise in. And a lot of pressure not to branch out in other risky directions.

I'd sure like to know what computing faculty think about these ideas.

So? What do you think?

The Tricky Problem of Anticipating the Future

2011-06-10T14:34:00.000-07:00

I am full of questions today about how innovation and innovative thinking can be encouraged. I have more questions than answers so far. The issue applies equally to academia and to industry. Although the details of an approach to fostering innovative thinking may well differ, my gut tells me that the process is likely to be very similar. If this is true, there is a lot that industry and academia can learn from each other and as a result become closer allies. Interdisciplinary computing is a great example.

Here is the fundamental problem (as in the last post I am pulling my initial thoughts from reading The Innovator's Dilemma). One of the threats to ongoing success is an inability to anticipate new technology (broadly defined) and to switch to it in a timely manner. "Timely manner" as presented in the book means before the technology is widely accepted and in demand.

Let's talk Interdisciplinary Computing (IC). I recall, some 10 years ago, when the term first started to be widely used the many computer scientists I spoke with about the subject interpreted IC as one branch of computing working in synch with another; networking and AI for example. Perhaps, at a stretch, the definition of IC might include computing and a form of engineering, usually electrical or computer engineering. The notion of IC as bringing computing together with an entirely different field was not something people were ready to embrace.

Today, when I speak of IC to people, there is a far greater recognition that computing expertise can work with expertise in other fields. There still tends to be a comfort zone containing the natural sciences, engineering and math, but as I have written about elsewhere, other fields are entering the picture.

Right now we are on the cutting edge of IC and exciting synergies are occurring. But history tells us that even if we embrace every conceivable field as one that can play ball in the IC world, that will not be the end of the story.

Something will change, if only because we will eventually run out of other disciplines to partner with. It may be sooner than you think. The problem is of course that we don't know.

So here come my questions:

What will the next big wave be?

How do we spot it while it is in its infancy, so we can grab hold of it and run with it?

Why do some people seem to "see" these things (the innovators)?

Do we have to just rely on these visionary innovators to appear? (I hope not - that is a passive waiting game full of risks)

What can be done to encourage more people to "see" or anticipate the future direction of IC?

What ideas do you have about these questions?

Can We Surf the Wave of Innovation Without Falling Off?

2011-06-08T22:13:00.000-07:00

I am thinking about interdisciplinary computing and the innovation involved with pulling it off as akin to surfing (Southern California is growing on me). The people who cross traditional disciplinary boundaries to create interdisciplinary programs or projects tend to be innovators. They are also skilled surfers. This is especially true in academia where the institutional culture supports specialization within one discipline. It takes a certain amount of guts and a balancing act to propose, plan and carry out a synthesis of very different fields.

What makes a new program or project successful? Many interdisciplinary innovators are what I'd call "think outside the box" people. Or, as one person I know recently described himself and how he runs his business compared to many of his competitors, contrarians. Whatever your word choice, in my experience innovators have some serious personal drive and are less concerned with following the establishment than are non-innovators. Academic or corporate. At the same time they have to understand the establishment and be able to function successfully within it.

What is bothering me is an idea I am kicking around about the future of interdisciplinary computing in academia. I only just started reading The Innovator's Dilemma and am already wondering what it will take for academia not to fall prey to the problem outlined in this book. Sure, the book discusses the corporate world, but the idea that innovators can get so good at implementing their vision that they completely miss or refuse to see the next wave until it rolls over them and they drown, is completely relevant. It takes a long time to get a new academic program up and off the ground. When you have a great idea that may not be welcomed with open arms by the institution, you may have to develop tunnel vision to keep afloat.

All that work, all that expended political capital, all that time and sacrifice. Eventually an amazing interdisciplinary program is created and virtually everyone finally acknowledges just how great it is. Then the pressure, direct or indirect, self imposed or external: just keep doing what you are doing. Don't make any radical changes to what is working.

That terrible phrase "if it ain't broke don't fix it". A path to stagnation.

It was spotting the need for a radical change and making change happen that led to success. More radical changes will be needed in the future. The advance of computing technology makes it inevitable. Who will be watching for the next wave, the next incarnation of interdisciplinary computing while the initial creators are keeping it all together and running smoothly?

This concerns me. Innovators are by definition not in the majority. Interdisciplinary computing in academia requires insight, innovation, passion and dedication. Given competing demands and extended implementation times, there is a real possibility of running out of innovators. How does interdisciplinary computing development maintain an influx of new insight, new eyes, new energy? We need it, if for no other reason than to keep the original innovators from burning out or simply getting too tied up in day to day planning to catch that next wave.

Pattern Matching and Information Discovery in Professional Journalism

2011-06-03T23:13:00.000-07:00

My day might have been called Tangled in Twitter. It morphed into a Recursion that spiraled inwards but then morphed again, this time into clusters and patterns that caused seemingly unrelated events to make a lot of sense. In some ways a typical day, but in the end, not really. Jonathan Stray, a journalist at the Associated Press (see my last post if you want a full introduction), is part of a team working to use search engine technology to cluster and categorize "big nasty document sets" such that information emerges that would probably otherwise never have been found. When you are dealing with millions of data points, you could use some algorithmic help.

Tonight a light bulb went off in my head about the important social potential of computationally driven pattern matching when applied to enormous linguistic data sets. Without my own almost overwhelming set of seemingly unrelated activities today, I don't know if I would have made the connection quite so solidly. So I'll fill you in. I'll also point out the globally significant ways computing is starting to be used in Journalism and where Artificial Intelligence could be used in the future if people like Jonathan keep doing what they are doing.

It all starts with data points. Lots and lots and lots of data that initially seem unrelated. My day's data points included: a morning Skype call that left my brain a bit sore; literally minutes later, before I could even make it 5 feet to the caffeine, an unplanned Skype call from a colleague who wanted to discuss project paperwork issues (groan); a tear up and down the freeway to run an important errand; within seconds of walking in the door a request for another unscheduled Skype call to discuss, among other things, "bandwidth issues" (in retrospect I find this really amusing); a round of phone calls to a clinic about a topic I have been trying to make sense of for 6 weeks; the next unscheduled Skype call; at one point I got annoyed at Twitter for being dense and impenetrable when I least wanted it to be; woven around all of this I was getting lost in journalism-related website after website, trying to figure out where all the behind the scenes computing technology was located, what it was doing and how it was constructed (that was fun). Last but not least this evening I had yet another mind stretching Skype call, this time to Africa, so part of the day was spent on logistical planning for that.

The cool moment, when the patterns of my day fell into place, came in the evening after I bailed for a while, went to a yoga class and worked on getting my legs around behind my head (very non cognitive, thus freeing the mind up to become receptive to new things). I came home and listened to a recording of Jonathan giving a talk about the infinite number of ways in which documents (with all their text data) can be arranged; he reminded his audience that the algorithm we choose for any analysis is based upon preconceptions we hold about the end results; those preconceptions impose a framework which in turn affect the results. Stop and think about that for a few minutes.

[pause...]

The group Jonathan works with isn't concerned about my preconceptions, personal bandwidth or discoveries about how I allocate my time, who I choose to allocate it to, and what communication methods I use. Yet thinking about the personal internal "algorithms" I use to structure my actions and make my choices, as well as what I bring to that analysis, led to a mental reorganization of my day. The light bulb turned fully on after I listened to Jonathan's talk (filled with absolutely nifty visuals of course) about mining information from Iraq and Afghanistan war logs for previously unknown patterns of casualties - and other information, really, you just have to watch the video - AND after I thought about the conversation we had a few days ago about the potential of Artificial Intelligence to aid the process of rapid discovery and dissemination of information to the public.

Jonathan is active in the machine learning and semantic web communities. Where he finds the time to read all the reports he reads, I don't know, but he follows the latest advances from academia, industry and the government, including DARPA reports (which, if you have read any official government reports, you know are sometimes tortuous). He follows twitter feeds, open publications by the intelligence community, reports and advances in the fields of law and finance. Well, I guess the ability to suck up and absorb information like an industrial vacuum cleaner is part of what makes a successful journalist. But it makes even more sense to me now why a computer scientist/journalist would see the enormous potential in harnessing AI to mine for information, scrape all the social media outlets, suck up data in real time and dynamically transform it into useful public information.

This is what Jonathan wants to do more of in Journalism. Get those tech savvy journalists and set them to work analyzing the gobs and gobs (my word choice) of data out there that has been (and is being) collected - data that is only going to increase exponentially. And why not? Suddenly this whole idea of "computational journalism" which two months ago seemed a puzzling term makes a whole lot of sense. As I see it, incorporating AI into document analysis is a logical, practical and viable way to go. For example, what do you think an artificial neural network might make of some of these data sets?

The video you must watch that shows clustering at work on big nasty document sets (and explains how it works too).

Journalism Meets Computing - In A Big Way

2011-05-31T18:58:00.000-07:00

"You should go talk to that guy over there, Jonathan Stray, he is really interesting". That was all I needed to hear to set my feet zipping across the room where I plunked myself down on the floor next to Jonathan and, telling him he came highly recommended, asked if I could interview him for my blog. A momentary look of surprise crossed his face but he said yes. That was in March, during the Interdisciplinary Computing meeting I wrote about. Computational journalism was a hot topic and my source had told me Jonathan was a computer scientist who had entered the field of journalism. Cool. Very cool. So with little ado, we exchanged contact information and I happily planned for our conversation. We had that conversation a few days ago. Surprises awaited me.

I had a fairly standard set of "get to know you" questions lined up until I started doing a little background investigation. I tossed out my original questions. I hadn't really paid attention to the affiliation on his name badge, but at some point it dawned on me (duh) that "ap" stood for Associated Press. Small moment of anxiety as I realized I had asked a Journalist (note the capital J) if I could interview him. I got over it. I started reading Jonathan's blog (link at end of this post) and realized this guy really is a computer scientist too. On one end of the spectrum he writes about such things as experimenting with putting his iPhone in the freezer to reset the WiFi (it worked - sort of) complete with technical explanation. I was right with him through the whole fascinating story. How often does someone write well enough to suck you into wanting to know the nitty gritty details of how to ice a phone? On the other hand, Jonathan also writes in his blog about about some pretty deep and serious cultural issues, describing what he sees so realistically that is almost creepy. I can't shake off one entry from Jakarta that juxtaposed prostitutes, people digging through garbage and blow dart sellers (blow dart sellers???) against fast paced sales of skin whitening creme by those (presumably with income) who wish they were White. I have traveled a lot, yet I was still stopped in my tracks several times by the implications of Jonathan's blog entries.

I guess I neglected to mention that Jonathan oversees a group of developers (yes, as in computer programming developers) at the AP who produce "interactives". I went and took a look and found the AP Economic Stress Index for the US. I was able to zero right in on San Diego County. This month, the Overall Stress Index is 13.79, the Unemployment Rate is 10.2% (ow!), Foreclosure Rate is 2.2% and the Bankruptcy Rate is 1.84%. At least it is worse in Los Angeles: Stress Index is 15.93%. The oveall rate in California is 16.9%. The only state to have it worse is Nevada, at a crushing stress index of 20.67%.

You can zoom all around the country and check out what is going on back to 2007 when the recession began. There is information to explain what it all means if you want to read it. What a way to tell a story.

How did this all come to be?

It all started out like a "typical" computer kid story: the movie Tron was a pivotal moment, reading computer graphics textbooks in high school for fun, getting a degree in CS and Physics....an MS in CS...a developer job at Adobe....challenging, cutting edge technological work. Good money, good hours, good exposure.

Then Jonathan took some time off and went backpacking in Asia. He described to me that it seemed an "almost impossibly different reality" - how could such different cultures exist on the same planet? He started writing.

Came back to Adobe...then went backpacking overseas again. More writing ensued. It turned out that at the time, at the University of Hong Kong Rebecca MacKinnon was on the journalism faculty studying global online media policy, specifically, Chinese censorship of the Internet. That was too good to pass up: Jonathan enrolled in an MA program.

Cultural study, writing and developing information for the public good, technology.....

As if on cue, a job almost tailor made for him appeared at the Associated Press. What does Jonathan like best about his job? The job requires he be right on the edge of what is possible in the constant evolution of technology and journalism.

There is a lot more to say about this. So I'm going to pause here, and pick up in the next post. Even if I did not feel compelled to share more about what I learned from speaking with Jonathan about the integration of computing and journalism, he himself said something that tells me I must. Sound bites. We live in a world of soundbites and too often all we get are soundbites. Not the full story. So... to be continued.

Jonathan Stray's Personal Blog

Surviving the Challenges of Personal and Professional Volunteering

2011-05-25T21:05:00.000-07:00

I volunteer for a few organizations, one of which allows me to get into the mountains on a regular basis. I am a weekend host at a mountain lodge. Absolutely lovely and worth the occasional hassle. This past weekend I had hassle in larger numbers than usual. Dead mice played a part as did several people who felt they did not have to pay to use the facilities. We are not talking big bucks here. In fact, "extremely inexpensive" would be most accurate.

Spending several days in the woods, even when unexpectedly called upon to become a plumber, electrician, random trouble shooter or occasional Tough Guy (Gal), leads to regular introspection. This weekend I found myself thinking about the process we use to choose to take on "extra" activities, and how we decide when we have achieved a good balance. Taking on innovative professional projects often starts off as "volunteer service". We come up with an idea we just can't put down and we run with it. Eventually, if all goes well, the project blossoms, and becomes part of our portfolio of acknowledged and rewarded activities.

Many of the interesting interdisciplinary computing projects I come across start off as an idea that pops into someone's head and they run with it. The projects I hear about are usually the successful ones - difficult people were dealt with, project goals were achieved, peers, subordinates and supervisors are enthusiastically on board, and academic or business objectives are aligned.

But there are great projects that never gain traction. In several recent cases I heard about, a critical reason for failure was "volunteer overload and burnout". You have probably noticed that some of the most creative people take on more than their share of projects - because they have the ideas and energy. There is a delicate balance needed between taking on many exciting projects and not being driven to pull your hair out all at once.

Successful entrepreneurial and adventuresome types know their personal limitations: physical and emotional. They know when enough is enough and how to say "no more". They know how to deal with annoying people who want to suck the lifeblood out of them. They have patience and are able to emotionally let go of the annoying lifeblood sucking people. They know when to ask for help: we can't simultaneously be spontaneous plumbers, electricians, maintenance personnel, stackers of wood, and gatherers of litter. We know when to call in reinforcements, or at least someone who knows how to stop the mystery leak.

Sometimes we have to catch mice. I had to remove 4 dead mice upon my arrival in the mountains this weekend, and do it before the guests arrived. Then I had to listen to the "snap" in the middle of the night as the mousetraps caught more mice - which I had to get rid of before everyone got up in the morning. I'm not a big fan of killing mice. In fact I'd rather not. This weekend, with the large number of dead rodents to deal with, and the couple of people who were determined to take advantage of my being a "volunteer", I thought about the importance of setting scope, fixing boundaries, goal setting and knowing when to let go of what is not really that important for the sake of the bigger picture. Just like my professional projects. No different.

Genetic Sequencing, Bio-Informatics and Computing

2011-05-19T12:06:00.000-07:00

Today I obtained a new view into the world of bio-informatics when I had a chance to speak with someone who works in the field. This person is not a computing professional but was able to explain to me some of the interesting work in the field that relies on computing. With her assistance I located a company that does some of this work (link coming below). I gathered much of this information over a breakfast meeting and sometimes my coffee, granola parfait and egg (separate plate) got cold as I scribbled notes like mad on the seat next to me. On the other hand my freezing orange juice warmed up while I was writing chewing and talking.

There are many different areas of bio-informatics - huge field. Interestingly (perhaps not surprising) the medium to large sized companies employ many computing professionals who are cross-over people. For example, in one major company my breakfast colleague knows about there are three computing groups under the umbrella of a Vice President: "traditional" IS/IT support, a bio-informatics group and a software development group.

For a company that studies or supports the study of genomes, there are lots and lots of data to manipulate and crunch. Typical customers of such a company are academic researchers in a hospital setting, researchers in federal agencies such as the CDC or NIH, and corporate entities including pharmaceutical companies, bio-tech companies and diagnostic companies.

What do they want to accomplish? One angle is to study a gene, or a biomarker, to try and understand better how it works. The researchers may want to cause a particular gene to do more of what it naturally does or to turn off a particular gene (cause it to stop doing its job). The term used a lot in this type of work is Polymerase Chain Reaction (PCR) which, very simply put, means to amplify a region of a genetic sequence so that it can be detected and manipulated. Another angle of research has as its goal to figure out if a specific gene has an error in a particular (living) population - related to a pathology perhaps. Cancer is a classic example. There is a lot of bio-informatics terminology that I am trying to avoid using, but to use the official terminology as it was explained to me in this instance, people in the line of work we are discussing are trying to identify what the nucleotides are in a particular region of a gene, which will then be used as primers in sequencing. Yes, a mouthful if that isn't your field. If you are still with me you get brownie points.

Computing is the backbone that allows this kind of work to take place, because the clients referred to above want to order specific sequences of DNA for analysis. A company such as Integrated DNA Technologies (the example company I located) supports researchers who are studying genomes by (among other things) providing the genetic sequences needed by those researchers. It has been a loooong time since this was done by hand - with what we know now and the data volume we have it is unimaginable. Forget the row of people in white suits pouring things in and out of test tubes (they may exist, but not for this task). There is an entire computer driven manufacturing process to synthesize desired genetic sequences in the most efficient manner possible. These sequences may need to be highly customized.

Let's say an order comes in for 100 oligonucleotides (a short sequence of nucleotides, which are the basic building blocks of DNA and RNA). Each of the 100 requested oligonucleotides is 20-200 nucleotides long and each one is different. There are banks of computers that have programs to synthesize (create) these oligonucleotides. Not only must the software determine the correct chemicals, the timing of their use and the stability of the result, but the software must also recognize that load balancing is required; the heavily customized sequences slow down the process and are generally forked off to another process along with other similar desired sequences. This can lead to orders from several clients being created together on one "plate". There might be 5 orders of 100 oligonucleotides that are distributed across the system at the same time in order to provide accurate and timely creation.

Eventually the software must take the end results and regroup them for the appropriate customer. Every step of the process involves complex algorithms, timing, QA checking, load balancing and rebalancing and did I say LOTS of quality control? Heaven forbid a customer received a different genetic sequence than they asked for. Someone (lots of someones) has to know their software system optimization techniques as well as their chemistry.

A different computing dependent activity IDT is involved in is providing the software to help customers design the oligonuclotides they want. Double stranded DNA can be several thousand base pairs long and the customer wants to determine where in that genetic sequence is the best place to make and attach (or detach) an oligonucletide. Software provides the ability to evaluate the characteristics of a given oligonucleotide (there are many factors involved). The software can predict the specificity, the stability and the cross-reactivity / structure of potential candidates (I'm getting tired of typing out the "o" word - I'm bound to mis-type it if I haven't already). The customers can use IDT's SciTools to help them decide what request to submit for manufacture.

These tools have to have all the hallmarks of any well designed and constructed s/w application - an easy to use UI for the target customer, efficient processing and logical functionality. The inner guts have to have the usual features including: bug free, flexible, sufficient, robust and responsive. Who is most qualified to design these applications? You guessed it - (interdisciplinary) computer scientists.

Challenges That Should Not Be Challenges

2011-05-13T13:53:00.000-07:00

An interlude....

Earlier this week, I dropped in on someone I know well who, along with another person, was using a business application. Both are "typical" users in the sense that they use software to accomplish business tasks and that is the extent of their interaction with the computer.

As I walked in the room, one of them pointed in the general direction of the printer and told me they had been having trouble getting "that" back in place - I couldn't quite see what they were pointing at and in a light hearted way I said "Have you tried closing your eyes, giving it a kick and hoping that nothing snaps?". The reply was an amused comment about how that just might have to be the next step. But there was an underlying frustration there. A short while later they finished up their work and took off. After taking care of what I needed to do I took a look and the problem was that the top cover of the printer paper feed was out of the printer and they were having trouble putting it back in place. It was a matter of a second or two and I popped it back in. That same day I was labeled the "go-to" person.

This got me thinking...we have been having some serious conversations here about interdisciplinary applications of computing, yet there remains a huge gap of basic .... something. I'm not sure it is knowledge. I'm not sure what exactly it is...I have been searching for the right phrase. I'm still working on it.

But there is a connection here and I'm grasping for it. I'm thinking....when we talk about interdisciplinary computing...when we talk about helping people...I'm wondering....what can we do in an interdisciplinary collaboration that will make computer systems and their basic (to many of us) operation less confusing to those who live in very different worlds? Popping the paper feed cover on was trivial to me; I knew instinctively the angle and direction to hold it. The operation was certainly not trivial for them - and they run a very successful business - smart, educated, thoughtful, savvy people.

First we (I) need to get a handle on how to describe the issue. It isn't "computer literacy" or "digital literacy". I think it is something different. But I'm convinced there is something here, very fundamental, that needs to be tackled - for adults. Adults who have their productivity disrupted by challenges that should not be challenges.

My antennae are vibrating all over the place that there is something important ...

Interdisciplinary Computing Meeting Number 2: Day 2, Part 2

2011-05-09T22:23:00.000-07:00

This is my last direct report post about the meeting, although I hope to follow up with some interesting related posts that came out of this meeting. In this post I'm going to list some of the "hard questions" that stakeholders could ask about Interdisciplinary Computing (IC) development. These questions came out of one of our breakout sessions. I have several pages of questions, so I'll pick some representative interesting, challenging or just plain important ones.

Our group was trying to come up with the toughest questions that anyone considering IC development should be prepared to answer. In a few cases I will suggest starting points for answers, but in most cases I leave it to you to ponder. The answers will need to be tailored to who is asking the question and in what type of institution the IC program/course is being considered. I hope that if you grapple with these questions you will be inspired to think outside the box and feel inspired.

I will end with a few reading recommendations given to me at the meeting. I have not read these books yet, but they are high up there on the list; I'll share them now and we'll see how they turn out. If anyone has read these books and has comments, I'd love to hear them.

First. Who are those IC stakeholders? They include: Administrators (of various types), Industry, Parents, Faculty, Students, Alumni, Governance agencies (Legislators, Accreditors)

Possible Questions From Administration:

Question: What is the impact on the department(s), major(s), what is the cost for equipment, resources of developing an IC course (not even a program)? Multiple questions rolled into one....

[Answer could center on this point (and data will need to be assembled to back it up): We will increase the enrollment to the institution. We will not just shift students from one area to another. This statement can then be expanded upon to address all the sub-questions (impact, costs etc)]

Question: How does IC fit into high stakes testing? How does it fit into existing standards, mandated or currently culturally accepted?

Question / Problem From Industry: What happens if an industry panel gets together and says "no, we aren't going to hire your students, we don't like what you are doing".

[The response would involve improved communication between those developing the program and industry and getting a handle on where this statement was coming from.]

Question from Parents: What is the ROI (Return On Investment)? What exactly is my child going to be when they graduate? What kind of job are they going to get? What is the time to graduation? [more multiple questions coming back to back but all centering on the first piece - ROI]

Question from new Faculty: How am I going to get tenure? Where will I publish?

Question that could come from a variety of sources: How does this contribute to workforce development? Prove it (the economic development the IC course/program will produce).

Problem / Question: IC programs are for people who can't hack it in either discipline.

[I personally have heard this one said. It represents an entrenched pov based not so much in any factual evidence but on personal opinion. That makes it challenging to address. But addressed it must be]

Things to chew on.

Now for the book recommendations. Uplifting, gets my intellectual bookworm instincts going full steam and a good way to finish this post:

"Innovator's Dilemma". Looks really interesting. There are two follow up books that look interesting as well: "Innovator's Solution" and "Crossing the Chasm". I'm looking forward to sinking my teeth into these. The orientation appears to be towards business rather than academia, but from perusing the first book quite a bit online, it looks like the principles could well be transferable. And check out the TOC - definitely not dull.

"Creating Interdisciplinary Campus Cultures". Now this one is definitely aimed at academia and looks like it might have some very practical suggestions. I can see reading Innovator's Dilemma and then this one. A possible interdisciplinary synthesis of perspectives and ideas.

Have a nice Tuesday.

Interdisciplinary Computing Meeting Number 2: Day 2, Part 1

2011-05-05T16:43:00.000-07:00

The second (and final) day of our meeting was jam packed. I need a giant suitcase to contain all the notes I could write about our discussions. So... I'll start again with some of the items that jumped out at me from the day.

Interdisciplinary need not be (as some have feared) a zero sum game. In fact, Interdisciplinary Computing (IC) can change the zero sum game (either you go into field X or field Y). With IC, one department does not lose students to another department ("student stealing"). Quite the opposite. Programs that implement IC programs, minors, (or the variety of forms I have discussed previously) often result in students having a foot in multiple departments. Depending upon how an institution calculates FTE a student may be counted towards FTE in more than one department, thus giving "credit" to both departments - a good thing. (FTE = Full Time Equivalence, or to the layperson: a calculation of how many students are considered to be in class/department/division/school. FTE numbers often have a powerful effect on fund distribution, hiring etc.).

Here is an interesting observation: look at the National Science Foundation Discoveries site. This is a site where the NSF highlights innovation; most of the featured projects are IC - computing and another science.

Big Science and Small Science. These terms were introduced and there was a bit of a discussion about what they mean and the implications. One table (I was not sitting there) later spent time discussing the topic in detail. But from the more general discussion, here is the gist I came away with. It started when someone posited the idea that computer science projects would more likely be "small science", i.e. local projects that produce a lot of data; "large science" (aka "long tail science") projects are large multi-institutional / multi-group / multi-person projects such as those conducted by NOAA (National Oceanic and Atmospheric Administration). The "problem" would be that larger projects are more likely to get large funding, and thus dissemination. What to do?

I'm not sure I totally buy this definition and the gloomy conclusion. There are certainly computing projects that obtain multi-million dollar funding - when I was working on my PhD some faculty I knew received that kind of funding. And even if we are talking smaller funding levels, I think multi-institutional grants of $500,000 or $1,000,000 are nothing to be sneezed at and can certainly produce results and wide dissemination. Those are available. I was recently one of several PIs on a grant in the first category. Sure it helps to be a government agency, but one does not have to be one in order to get your results "out there". You may have to work a little harder at dissemination, but there are channels. And in fact, sometimes, you know exactly who the groups are that have an interest in your type of work and can target them in a direct semi - personalized manner. And we haven't even mentioned the fact that Industry is working on IC projects and they have their own mechanisms for dissemination, sometimes working with academia, and other times going it alone.

But really, the question is: Why is "small" vs. "large" important for a discussion of IC? Our conversation turned to how small science (let's say 2 departments such as CS and History working together) can leverage large science. NASA, Historical Archives and a variety of organizations make large amounts of data publicly available; these data can be used and added to at the local level. Perceptions of both fields can be changed and information made available that otherwise might gather dust. Here is a great example: check out this project, which one of the meeting participants is working on: Digital Durham, a fascinating integration of computing and history.

Arg. I'm out of space (assuming the general protocol of not making a post tooooo long). To be continued...

Interdisciplinary Computing Meeting Number 2: Day 1, Part 2

2011-05-02T18:05:00.000-07:00

In our afternoon discussion of faculty motivation for interdisciplinary computing (IC) I learned several interesting things. First the small but amusing: we had been flinging acronyms around quite a bit, and at one point someone used UTA right in the middle of a sentence. No one asked what this meant so I was brave. UTA: Undefined Three Letter Acronym. Cute.

Some food for thought items came out of the motivation conversation that addressed the questions (what is motivating about IC, how to support it) in a memorable way. I'll start with those.

- "The transaction between 2 people in different domains is what makes each one better informed and knowledgeable." This might be taken as a a given, but it is interesting to consider it under the realm of "motivation". The affective side our reactions is often as or more motivating than the cognitive side of our reactions. If a synergy develops between two people discussing, brainstorming, and creating, then yes, this can be exciting (an affective response) - hence motivating.

- "It's data; it's representation. The domain doesn't matter". There were some interesting examples of this, such as all the ways to represent data in a form other than rows and columns or bar graphs. We saw a magnificent and beautiful simulation of what happens when people get into an elevator. Apparently this has been studied quite a bit. There are definable patterns of behavior that have a very mathematical predictability. The more data (people) you add, the more interesting the scenario gets. The collaboration was between CS and Art. We watched a colorful square show how people realign themselves as more people enter the elevator. For example, at first one or two or three (ish) people arrange themselves equidistant to one another. Then as more people enter, people spread out towards the walls, leaving a central open space. As more people enter, there is a shuffling around until everyone has almost exactly the same amount of space between them and are fully distributed through the elevator.

Now here is the even cooler part. If you REALLY want to make someone uncomfortable, move over next to them - we watched this on the simulation as the little colored dots shifted around. If you do this, the other person will immediately try to reposition to regain their equidistant space. This can set off a domino effect of the entire elevator realigning itself.

Later on, a friend and I got in the elevator and watched people's behavior and yes, all of this was absolutely true. It all seemed to happen without anyone consciously thinking about it. We had a little conversation about whether or not we should test out the last part of the theory by engaging in conversation while casually moving closer and closer to someone. But we didn't carry through on that.

The elevator simulation was just one engaging example resulting from close collaboration and the synergy it produced. It could not have been developed without the art and cs faculty in close communication.

Originality: One of the meeting participants gave us a short demo about teaching algebra using a rope. Someone suggested obtaining a video of the performance and posting it on YouTube. I sure hope that happens; I'll link to it. Hard to describe but the basic idea is that knot tying can demonstrate algebraic concepts e.g. "single instruction, multiple data = sheep shank". The premise is that math can be mapped onto many different systems; in this case the system was a rope. I'm telling you, the math concepts stuck in my head better than I ever remember from dragging my way through theoretical descriptions and chunking through example after example of plugging in numbers. We, the group, were transfixed and the presenter was clearly enjoying himself - very motivated.

We focused much of our conversation about Action Items (to support motivation for IC) in breakout groups. There are far far more than I can list here; some of them made it into my previous post. Many of the ideas related to putting in place support mechanisms to ease logistical hurdles (geographic, fiscal, advancement/promotion, departmental assessment/accreditation mechanisms, etc). The list was long. The ideas varied from top down to bottom up. Just to give you a flavor, here is one top-down item: Because they have clout, organizations, leaders, funders should voice public support for IC; people who otherwise might not listen, will often listen if the message comes from someone in a position of respect and authority. One bottom-up item: hold a mashup of people who come together to discuss and address an issue: get them all in the same room to attack a given problem. (Sort of like what all of us were doing)

To try to sum up (a difficult task): An overarching action item: Develop a Framework of how to solve IC problems.

Interdisciplinary Computing Meeting Number 2: Day 1, Part 1

2011-04-29T21:38:00.000-07:00

Back in January I reported on a meeting on Interdisciplinary Computing I attended in San Diego. I am at a followup meeting in Tucson - we had our first jam packed mind stretching day today.

The group of people attending this meeting is extremely diverse which makes things interesting. We started off the day with an entire table full of people involved with creating a new area called computational journalism, and we have quite a few people at the intersection of physics and computer science. There are other interdisciplinary areas represented here as well, but perhaps one of most interesting observations I made today is that we have such a strong contingent from the arts and humanities.This has injected some fascinating perspectives into the conversation. They all soon split up and spread around, but it was impressive to walk in the door and see all the journalists and media people! I new this was going to get interesting.

We covered a lot of ground. Here are a few of the highlights from today - things that really jumped out at me:

We had several breakout sessions to discuss topics including exemplars of Interdisciplinary Computing (IC), lessons learned, what is it that motivates faculty (and industry professionals as well) to pursue IC, and given what we revealed among ourselves, what are effective supports for faculty to pursue IC? Action Items in other words.

One of the surprises for me right off the bat, was to learn that the field of Journalism (not "Computational Journalism", but "Journalism") is currently having serious discussions within the community about how to define themselves. Now, in CS, we have been having this discussion for a long time and the discussion evolves about as fast as the field. But Journalism - I would not have guessed. It is not a new field; it was an eye opener for me, and others I believe, to hear that another field is wrestling with the same question: "what does it mean to be a journalist?" ("what does it mean to be a computer scientist?"). There is something to be learned from this shared definitional wrestling for meaning.

After pondering the issue all day I asked a question about it at our end of afternoon discussion. The most interesting part of the response, for me, was when one of the faculty heavily involved in developing the area of computational journalism opined that this common "problem" was one of the reasons he felt his field and computer science were able to work together. Because (I'm paraphrasing here) both fields are working to define an identity (or redefine, or refine, choose your pov), they are able to come together and form something new and original. I took that to mean there was a fluidity and flexibility supporting interdisciplinary collaboration, in part because the disciplinary boundaries were not so rigid; those in each field who were interested in IC used the identity challenge as an opportunity to break new ground.

In another breakout session (discussing what motivates the faculty who are already doing IC) the table I was sitting at spoke about how for many people "it is in our blood" and those people will do IC whether they are new faculty, established faculty or somewhere in between. Our table at least, had universal agreement on this point, countering the point I have heard (and others have often made) that the people who do IC are either 1) those who are brand new and have nothing to lose - i.e. they want to break new ground and are full of enthusiasm or 2) those who are secure in tenured positions and feel that it is now "safe" to pursue this passion.

It was interesting to hear a table full of people focus not on funding as a primary motivator (although everyone agrees that funding is needed and critical) but on personality - passion, interest, determination, being a maverick (someone tossed out that phrase). It was nice, I have to admit, to be surrounded by a table full of people who felt as I do, that it is "in our blood" (I was not the one who popped out with that phrase but it certainly feels accurate to me).

A question of course comes from this last point: how to support those who want to pursue IC but who are not in either of the three categories: new and fearless, established and "safe", or ordained by virtue of personality. How to support those who will perform IC given an conducive environment? Because it became clear to all of us I would hazard to say, that a conducive supportive environment is absolutely vital for achieving critical mass and developing self sustaining IC initiatives and programs.

These are some of the strong impressions that lept out at me today as I left the indoors for the first time at 5:30 pm to unwind some kinks in the outdoor hotel pool. A good place to let things soak. In my next post, tomorrow hopefully, I'll talk about some of the actionable ideas we came up with.

Succeeding in Socially Beneficial Activities Requires Some Special Qualities

2011-04-25T23:13:00.000-07:00

As I work my way through the final edits of my book on socially beneficial uses of computing I have been reviewing chapters one after another. Some of these chapters I had not looked at for several months. Reading them back to back like this I am struck by some common themes - technical and not technical.

First perhaps the least surprising: passion. Computing professionals working for social and environmental causes (and by no means assume none of these people are in traditional profit seeking corporations) are passionate about what they do. They get up in the morning ready to apply their computer science experience to something they truly care about beyond themselves.

Second: Many work on problems where there will never be (or is highly unlikely to ever be) "THE solution" or indisputable "proof" about the data and results they work with every day. These computing professionals have a flexibility and tolerance for ambiguity not often sufficiently lauded in curriculum I have experienced. When there is a monocular focus on proving things, using the scientific method to accept or reject hypotheses, it is possible to lose sight of the impact we can have on seemingly intractable real-world problems.

Third: I would be remiss not to include a technical / process issue. Perhaps this one will not surprise you so much; it didn't surprise me. However it did surprise me to learn, to experience, just how much achieving successful impact relies on this: not cutting corners. There are a million ways to cut corners in hardware, software and system development. It is true the culture of many institutions of learning doesn't sufficiently reward validation and verification. However, learning just how much it matters tells me we need to work harder at instilling the importance of these activities when future and new computer scientists are in their most formative stages.

These are just a few of the themes I have encountered; any one of them could make for a lengthy discussion. I must point out that the many projects I have investigated and researched all embody these themes; else they would not have succeeded in their socially beneficial activities and thus attracted my attention.

I don't know what you think but I feel honored to have had the opportunity to meet (sometimes only over the phone, Skype or email) the people who have taught me so much about computing "doing good".

IFF Computing == Cabbage

2011-04-19T23:13:00.000-07:00

I am periodically asked "what is it like to write a book?" If you have written a book you may be having a small laugh to yourself all of a sudden. A sort of evil chuckle. Because you know, .... well, I don't need to tell you. It takes you over in strange and wonderful and unexpected ways.

You probably also know that no matter what you say it may not convince the conversant that conceiving cognitively comprehensible and convivial concepts takes considered concentration. Even if you say "it is Computer Science!" (people often assume fiction for reasons I know not why) there is ofttimes a clinging to the concept that you must spend much of your time continuously cavorting. Come again? If we waited to compose for when we felt suitably inspired by The Muse ... my Editor could conceivably consider calling out the Costa Nostra (uh, just kidding...right, Randi and John?)

Perhaps my more-often-than-usual far away look, prompted not by my new glasses so much as by a looming deadline, brings on the question with greater frequency lately. However, I find myself contemplating a different question: "How do you know when you are really and truly becoming one with interdisciplinary computing?" (with which topic my book most certainly is concerned).

I have the answer. It came to me this evening as I took a break and sat looking out over a neighborhood canyon just breathing calmly. Even in stillness, everywhere I looked I saw things that reminded me of a computer. "Canyon - how lovely...oh, Canyon starts with the same letter as Computer." "Critter poo on the sidewalk leading up to the bench....Critter reminds me of Computer". "I Cannot see the stars because there are Clouds in the sky. Clouds? Computer!" "Concentrate on your breathing ...Concentrate. Concentrate. Computer Computer Computer".

A Colleague gave me a red Cabbage from their garden. Oh my gosh that was good - a fresh Cabbage tastes like Candy Compared to Cabbage from the grocery store". Candy? Compared? More "C" words! Cabbage. Is an excellent source of Vitamin C and beta-Carotene. Consuming large amounts of Cabbage reduces the Chances of getting Colon Cancer because it Contains Chemicals that protect Cells against free radicals. All those words Commence with the same letter as COMPUTER! Perhaps I have passed the threshold and am now officially (Crazy?) Coalescing with interdisciplinary Computing and Computer science and Computational thinking.

The Cabbage Convinced me. Computers are truly everywhere. All you have to do is Consider it.

Computing and Helping Sea Turtles with Social Media

2011-04-15T12:08:00.000-07:00

The Annual Symposium on Sea Turtle Biology and Conservation was held here in San Diego this week. I was fortunate enough to be able to spend a few hours speaking with someone attending the conference. I have been doing research into computing used in sea turtle conservation work for some time as part of my book project so this was a really nice opportunity to share ideas and compare notes in person.

One of the messages that comes through loud and clear: there is an enormous opportunity for the computing discipline to work hand in hand with environmental groups. There are highly technical computing activities such as the use of GPS technology (tracking animal movement for example) and modeling (projections of complex scenarios and how different factors might affect outcomes) and then there is a sometimes overlooked opportunity for the effective use of social media. We hear about social media playing a critical role in reporting international political events, but we do not hear so much about leveraging social media as a serious and ongoing computing career option.

When the Deep Horizon oil spill occurred last spring, how did the public get their information? Some people listened to television and traditional media. However, many went elsewhere. Scientists of all kinds and other content experts, working round the clock, who had more to say than what fit in a 30 second sound bite used: social networking outlets. For example, last summer a blog maintained by the Sea Turtle Conservancy posted statistics about turtles impacted by the oil spill; the same organization used their website, Facebook and other online venues to distribute solid data-supported information.

Professional computing skills can contribute enormously to the effective use of social networking. When to post, what to post, how to target the post. In the case of reporting on sea turtle issues this means computer science personnel can use their software engineering skills. These skills include principles of good UI design, and requirements gathering to provide a target audience the information they are interested in, in the most effective way online.

Additional computing skills are needed to build an effective public education and outreach website. html? cascading style sheets? content management system? sharepoint pages? Connections to databases of organized information - how should all that data be stored and revealed to the users through different media? ... There are many ways to build a site and it is critical to understand what approach makes the most sense and how to leverage technical capabilities in alignment with content goals. The biologists know their sea turtles. They know what the critical information is and what actions need to be done, be it with the public, government entities, other organizations and stakeholders.

There is another item worth mentioning. A computer scientist who works with an environmental group such as those supporting sea turtle conservation is most definitely not going to spend her or his life sitting in a cubicle all alone. She (or he) might well find herself (or himself) on a remote beach late at night watching for rare migrating turtles looking to crawl up on a beach to lay eggs. So I learned from my research - travel to interesting locations around the world and immersion in the natural environment come with the job.

Are you a computer scientist who wants to work for an environmental cause? Do you like to travel? Does the idea of getting dirty, muddy or bug bitten sound like not a big deal? This could be your calling.

Security Mechanism Can Enhance Historical Record Keeping

2011-04-10T17:08:00.000-07:00

Recently a friend showed me an incredibly creative application of computing technology with all sorts of possible uses. I am a language buff (that means Big Fan) so I immediately grabbed onto historical language issues. Now, this technology project has been around a little while so it isn't completely hot off the press. But I didn't know about it so you may not either.

The reCAPTCHA project. You probably (?) know what a CAPTCHA is: those squiggly tortured hard to read words you have to type in sometimes to gain access to a site, sign up for an online account or post a comment on a blog. If you don't type the word correctly you don't get in. Fortunately you get additional chances with new words. This technology exists because people can usually read the words but computers cannot. This keeps automated spamming out.

Here's the cool upgrade. Have you seen one of those where you have to type in TWO words next to one another? Why two? Isn't one enough? Well, this is what is going on. There are projects underway (which you probably *are* familiar with) to digitize books, newspapers, archival texts. The really old ones, the hand written ones, the faded or slightly crumpled ones - the OCR (Optical Character Recognition) software being used to scan and translate those texts cannot read many of the words.

Fortunately the computer identifies words it doesn't understand. Many of those words are being placed into those CAPTCHA screens. So you get two words: one is a known word, made to look hard to read, and the second is a word that was hard to read to start with (perhaps made more so, just to be safe :). That same unknown word is paired off and given to many many many people in CAPTCHA boxes. If you get the known word right, you get in (at least that is my understanding). If the vast majority of people get the known word right AND provide the unknown word with the same answer, the odds are the unknown word has been correctly identified and it is plugged into its spot in the original scanned text.

I realize the book scanning projects are controversial in some spheres, especially in regard to recent works. What captures (oh ow ow pun) my imagination is the thought of ancient Medieval texts written by monks with all those flourishes being scanned and translated. Ok, they are usually in Latin. Providing a Latin word in a CAPTCHA screen might be a giveaway, but the idea of being able to digitize previously inaccessible texts by harnessing the power of millions of people passing through online security checks is impressive. For now we may have to stick with Victorian English or Elizabethan English or whatever the native language is of the country where a site exists is, but eventually I suspect, computer scientists will find a way to put this to work with languages that are no longer in common use.

Meanwhile, and this might already be in the works, languages like Latin or other special-use languages might be applied to sub-populations of sites where they make sense. To get into a repository of ancient Sanskrit resources you have to type a two word Sanskrit CAPTCHA for example? Ancient texts can be made publicly accessible much faster than they would have been otherwise.

More information about the project: http://www.google.com/recaptcha/learnmore

Internet Voting: Security, Networking, Politics and Some Heat

2011-04-03T11:59:00.000-07:00

With social upheavals happening in countries across the middle east and northern Africa, the media and politicians have been talking a lot about democracy and the rights of individuals to freely express themselves politically. Although we are not in a similar situation here in the US - we are not risking civil war or overturning the government - we do have an issue that provokes heated debate and widely divergent perspectives among computer scientists: Internet Voting. The US Constitution guarantees the right to vote for its citizens. Most of us take this right for granted I suspect, whether we act on it or not. It amazes me when I hear how many people do not vote regularly, given that we can do so safely and without worrying about repercussions, but that is another issue.

For the past several years various groups and organizations have been debating, proposing legislation for, and running pilot projects using the Internet to vote. Why? A big motivator is to increase access. American citizens living overseas (civilian, military, government employees) often want to vote but if they have to rely on the postal services of several countries for ballot requests and return, or if they have to travel great distances to get to an approved polling place it can be a significant burden. State and county agencies in this country wonder if they can improve reliability and efficiency while reducing costs by implementing online voting. Given the current fiscal situation in this country that is a huge motivator. The problems of access, reliability and budgetary pressures just scream for consideration of a computing based solution. Maybe it will work, maybe it won't, but if it is going to happen it is going to be computer scientists who make it so (A Captain Picard reference in case you didn't pick up on it).

There are pros and cons and this is where opinions run hot. Let's take just one example: the need to guarantee the security and privacy of such sensitive data if it is sent over the Internet.

Why is a "guarantee" of correctness on the Internet so difficult? As many of you know, the Internet was originally designed by the US Department of Defense for use by a select number of trusted sites for the purpose of guaranteeing communications in the event of a national emergency such as a nuclear attack. Therefore, redundancy of data was the primary concern, not security of data. If Washington DC was attacked, multiple copies of sensitive data would be accessible in repositories across the country. This legacy lives on today, as the Internet has grown into a global network of diverse systems connected with everything from telephone lines to satellites, connecting state of the art computers and mobile devices to 25 year old legacy mainframes. As a result, it seems that we can communicate with almost anyone anywhere at anytime and because of built-in redundancy systems, data almost always gets through - unless someone intentionally interferes. And therein lies the problem. There will always be people who try to steal, or at least read and exploit, data that is not "theirs". Although not unique to electronic voting systems, the vulnerabilities of the Internet bring added attention to this old problem. We do *not* want anyone intercepting electronic ballots, or compromising a voting web site. How good is "good enough" when it comes to accountability and reliability?

How are these issues currently being tackled? I'm going to get technical for two paragraphs in order to provide a flavor of what computer scientists are currently doing in the realm of computer security for sensitive data.

The focus of much data security work is at the application and system levels. Onion routing is an interesting technique that supports anonymity across complex networks. As data is passed from an original source to a final destination it passes through many intermediate nodes (which may reach into the hundreds). Data that is “onion routed” has layers of encryption that are successively “peeled off” at each node, assuming the node in question has the correct cryptographic technique and knowledge to do so. Thus many successive security checks take place and a suspicious event at any node along the path will raise a warning flag. The action then taken is application dependent, and can include halting the process, rerouting the data or other customized response. Two other well known network level security technologies include strategic placement of firewalls and the use of Virtual Private Networks (VPNs). Various methods of authentication, encryption, verification, digital signature and hash functions find their way into this work. How well do state of the art data security efforts protect data and provide an audit trail?

Although the answer to that question invites a range of answers, computer security experts will generally agree that software alone will never be sufficient to detect or prevent tampering. Hardware level security checks are also needed. It is common practice in security intensive systems to include a Tamper Proof Module (TPM). This non-rewriteable chip contains check code to search for tampering. First the boot loader is checked, which then checks the Operating System, which then checks the application(s) for an integrity breach

There are high level issues to be addressed as well. Equally important requirements. An Internet voting system for US voters needs flexibility (to accommodate different state requirements), convenience for the user, training and education of both staff workers and voters. Particularly important is timeliness – the most flexible, friendly, convenient electronic voting system is pointless if the ballot arrives too late to be counted or has to be discarded due to suspicions of fraud.

There are always tricky issues when science and public policy intersect. Computing is particularly complicated because the field is so new, and technology changes so quickly. By the time consensus is reached on a contentious issue, the point may be moot. The technical issues alone for Internet voting are complex, but often come down to one issue: risk assessment. What degree of risk is tolerable in order to achieve a societal right guaranteed by the Constitution? In some cases entrenched opinion comes from holding a philosophical stance about whether or not the Internet can ever be an acceptable medium for any voting, overseas or otherwise. Proponents argue that it is only a matter of time until Internet voting becomes reality, and also that the subject is a matter of morals, so we must address the problem directly. Critics counter that it is not possible with current technology to implement Internet voting at an acceptable level of security and privacy, so the risks of trying it outweigh the potential benefits.

If we can be successful, the payoffs are tangible: morally, ethically, fiscally. If we don't succeed the risks are serious: from disenfranchisement of citizens to interference with our democratic process in the worst case scenario.

What do we do? Move forward (how?), or sit it out and accept the current situation as good enough for now. What do you think?

Computing and a Toothbrush?

2011-03-28T22:44:00.000-07:00

I was hunting for something quite different (and far more serious) when I found this unusual toothbrush and it was just too intriguing to pass up. There exists this computer scientist and inventor who got into toothbrushes (among other things). I just had to read on. The CS inventor, Richard Trocino, lives in Austin, Texas one of my favorite cities and former home. That clinched it. My textbook writing project was temporarily diverted.

This toothbrush is pretty slick if you are into gadgets. A gift for the person who has it all (make a note on your holiday or birthday list). Called the OHSO, it is a refillable toothbrush with an oxygen intrusion prevention setup so that the toothpaste will never gum up (so go the marketing materials). You can put your favorite toothpaste in - I wonder if that includes a homeopathic paste made from baking soda and water."Suction technology" makes it easy to fill. That makes me want to see just how much sucking is done and what else could get sucked in.

It self dispenses in different ways depending upon if you twist the little knob or if you tilt it a certain way. There is a little window where you can peer in at the stuff to see how much paste is left. No leaking, airtight all around and with replaceable parts. I am dying to play with one of these.

I have read everything I can find and I don't see where computing technology comes into the OHSO. Unless there is a little microchip hidden in there somewhere. But you'd think they'd advertise it. I would like to take it apart and find out.

Maybe the computer science only comes in via the fact that they don't do formal advertising but rely on word of mouth and social media to generate sales.

Is this a socially useful device? There are testimonials on the site from business travelers to active duty military personnel and everyone in between swearing how much they love this toothbrush. Clean teeth, the prevention of cavities and recessing gum lines are definitely a good thing. Keeping one's teeth is a good thing. There is something perhaps "green" in a toothbrush that might last for years. I can't tell if it is made primarily from plastic or metal. That would add or subtract from the beneficial environmental aspects. But you have to be the judge on this one.

What I really want is to approach it as a technological device and test it in every way possible, including taking it apart and putting it back together. I know I could put my research design skills to work on coming up with some very creative experiments.

Hopefully I would have better luck than the time back in my 20s when out of curiosity I took the front passenger door off my 1969 Dodge Dart and couldn't put it back on. (the door was too heavy - those wonderful cars were tanks) I drove 20+ miles down the highway at full highway speeds without a door in order to find another pair of arms. But a toothbrush is a far cry from a solid steel car door. What could possibly go wrong? There is that suction aspect to consider I suppose. Unlike a garbage disposal however I wouldn't have to stick my hand into a dark place full of nasty sharp blades.

But really, the scientist in me hears about something this unusual and drives me to want to take an OHSO toothbrush and put it through some serious paces. Then I can find out or infer if computing plays a role in the device and if the device is socially beneficial.

If someone will provide me an OHSO I promise to take it traveling on business, into the mountains on retreat, to the dentist (just have to see what she'd say about this) and in fact I'd stick it in my pocket, take it everywhere, and brush at random intervals wherever I happened to be. I might even alternate between randomness and statistically planned brushing events.

In between taking it apart and putting it back together.

I'll devote the full range of my assessment and evaluator experience to the task.

How about it OHSO - want to send me one? Consider it free product testing.

A Day Without Computer Scientists Just Wouldn't Be The Same

2011-03-24T16:12:00.000-07:00

Today I send out a thank you to the people I don't know in the computer science world who led to my having a successful day. Sometimes you just have to look at the big picture and be grateful.

I'm writing a textbook and it is deadline time. Big Deadline Time. So there have been some very long days and nights lately, and I want to thank:

The computer scientists who created word processors so that I was able to write until 4:30am last night and still have the results be legible.

The computer scientists who created Quicken so that I could fly through it early this morning and pull out the information I needed for my lunchtime meeting with my accountant even though I was a few neurons short of a full brain.

The computer scientists who created spreadsheets so that I could fly through one of mine and extract lots more data to bring with me to my accountant meeting even though I had forgotten to eat due to the missing neurons.

The computer scientists who created whatever software my accountant was using such that she was able to cheerfully do her job even though she was talking to a zombie.

The computer scientists who created the Internet and email so that I could send off my latest book chapter to my editor, after I got back from the accountant meeting, without having to try and navigate my way to a post office.

The computer scientists who invented external devices so that I can be creating a backup of all those files even as I write this.

The computer scientists who invented the computer that made all of this possible!

What would a day be like without computer science? I shudder at the thought.

Computing has an Important Role to Play in Earthquake Preparedness and Response

2011-03-17T20:16:00.000-07:00

When devastation as large as that currently happening in Japan occurs, it can be hard to know what to say or do. If you are like me, you have been reading the news daily (or more often), caught up in a mix of complicated reactions. This morning for example I watched computer generated weather simulations of possible flow patterns of radioactive contamination (via the BBC). As the simulation looped over and over I couldn't help but be transfixed by one large multicolored plume as it slid like a mutant amoeba over Southern California. Right here in other words. The colors registered different levels of radiation. Computers generated those simulations and unsettling as they were, I'm glad to be able to see them. It is better to have knowledge from a reliable source than no knowledge, even when that knowledge is based on probabilities and a great deal of the unknown.

I was very grateful for computer science when the recent earthquake struck New Zealand. A friend lives in Christchurch and it was only a matter of a few nerve wracking days before a brief post appeared on Facebook telling all of us that she was ok - no doubt considerably freaked out, but ok. Thank you to the computer scientist creators of social networking.

The situation was very different in 2004 when the tsunami hit Sri Lanka and someone I know was very near the coast. It was over a week before we learned that he and his family were alive. There was no email access, no smart phones, no Facebook page, nothing but waiting and telephone calls to the US State Department (who were terrific by the way). The computing communication infrastructure either was not there to start with or had been completely disabled by the dual natural disasters of earthquake and tsunami.

Watching the developing situation in Japan, the triple disasters unfolding as nuclear contamination possibilities are added to realities of earthquake and tsumani, watching the weather models, I was reminded of the researchers around the world who work full time developing models of earthquake simulation and who perform seismic hazard analysis. They work on these models so that we can know as much as possible about what can happen, how it can happen, how we can best prepare, where to erect buildings and other structures and how to protect them as best we can.

Developing 3-D and 4-D maps and models are classic computing problems of large scale data analysis: selecting and applying the "best" constraints, knowing that the model you develop will depend upon choices about possible epicenter (location of the earth directly above the underground origin of the earthquake), focal depth (how deep the origin is), magnitude (amount of energy released) and possible paths the seismic waves may follow. There are innumerable factors to include or leave out of this type of model such as local and regional variations, ground type, land masses, rock type...just for starters. It is all about improving probabilities and predictions.

The paths of seismic waves are not always what one might expect. For example, one reason Los Angeles gets hit so hard by some earthquakes on the famous San Andreas fault is because there is a natural "funnel" that directs ground motion directly into the city from a section of the fault well east of the city. Complex modeling and a solid knowledge of the land revealed this important information.

You have to know your hardware, firmware and software; you have to know how to work with the latest and most sophisticated networks of high performance computing. Operating system, algorithm and programming language optimization. Databases to hold all those data and sophisticated networks to link the distributed grids of computers.

If you have an interest in earth science and scientific computing (you don't need expertise in both - this is where collaboration between fields comes in) then here is an area where you can work to make a difference in people's lives.

Cultural Anthropology Meets Computing

2011-03-14T18:12:00.000-07:00

Often we think about Interdisciplinary Computer Science (or in a broader context Computing) as involving another science, mathematics or engineering. This makes sense as a starting point because the commonalities between fields are most obvious and it is easier to envision a true partnership where each field contributes equally to an activity.

However we need to go beyond the STEM disciplines and bravely consider the relationships that can be formed with the arts, humanities, social sciences. These areas are beginning to be considered. There are interesting explorations underway such as a recently completed NSF funded project bringing together journalism and computational thinking in K-12.

What about Anthropology? Not long ago I started a conversation with a cultural anthropologist who has been working at the intersection of computing and anthropology for many years. Arlene Atherton works in an area she calls Visual Linguistics. Many of her projects over the past two decades have involved evaluation of internet media (for example web pages, educational materials) from a perspective of different cultural perceptions. She takes into consideration two areas: what she calls the "human universal", i.e. those things that cognitively and physically we can all do as human beings, and "the unique" those aspects outside of intelligence or cognition, human aspects that derive from culture and manifest themselves in visual perception. Arlene has studied "traditional" anthropological groups, meaning from an outsiders perspective (mine in this case) ethnic, racial, stage of development. In addition she has looked at differences in other areas such as generational: Gen X, Gen Y, Boomers etc.

Arlene got me thinking about the role of interdisciplinary computing and anthroplogy and I want to try and lay out some ideas of what each field has to offer the other using her work as a jumping off point.

When I first heard the term "visual linguistics" the definition that popped to mind was: "what my eyes tell my ears". In other words what I see leads to what I *hear* i.e. perceive. When I shared my phrase with her, Arlene suggested this wording: "Visual Translations of Image Language".

Cultural Anthropology (CA for short) can offer Computing: a new way of thinking about the design and evaluation of online anything. CA can bring to the table differences in how cultures (traditionally defined or otherwise) choose to use text and graphics - percentages of each, placement, meaning of text and graphics relative to one another in different placements. What messages are sent and perceived to different groups by the same page? User Interface design can become more explicitly culturally aware, especially as advances in technology lead to the greater embedding of text, graphics, and live media. These perspectives will benefit education, marketing, global politics and communication and much more.

Computer Science (computing) can offer Cultural Anthropology: the knowledge of how to make real the desired effects for online media. We have the knowledge of how to bring complex graphics to life in the most efficient, resource saving, and robust way. We can determine or discover the best structural designs and algorithms to take advantage of complex data streaming and networking technology even as we develop it. We can develop the tools and artifacts to leverage culturally different needs such that they will be effective yet transparent to the user. We can address the inevitable new needs for online security and privacy that arise in sensitive environments. I could go on. But what I am proposing is that in addition to the items listed above and others that you can think of, we can pull it all together technically, make all the pieces fit seamlessly, taking advantage of the latest advances across our field.

What other non STEM fields can you think of where we can work together like this?

International Women's Day Spawns Important "Science Magazine" Post

2011-03-10T23:51:00.000-08:00

I have a "new and different" blog post in the wings that I hope to post tomorrow - I am waiting for confirmation of some information I'm very excited about.

Meanwhile, I want to reference an interesting blog entry in the Science Careers Blog (part of Science Magazine online) posted yesterday as part of acknowledgment of International Women's Day.

The post discusses the significant positive improvement in retention of women when applied contexts, in particular real world social contexts are presented as an integral part of computer science coursework. Given that this is Science Magazine, there is more to the post than unsupported opinion and commentary. I quote a few lines:

" "The faculty initially did not think that the students who dropped out could hack it," Huang said. "But, on closer examination... they found that women had lost interest because they did not see what algorithms were good for or why they needed to learn how to design a variety of complicated algorithms." The faculty decided to focus the first session of the course on how algorithms may be used to help social causes. [my added emphasis]" Once this began, the retention rate for women increased so much so that now all professors spend the first class introducing their courses by discussing the applied relevance of the material that will be presented," she added. "I admit, I was really relieved to find that the women could hack it." "

(I wonder if there was an intended play on words there. Probably not.)

The post goes on to report that the male students did not respond in the same way. Interesting, however a very intelligent response followed:

"Assuming that men and women continue to have predominantly different interests in how their research is applied later in life, here's my thought: There are differences between individuals of the same gender of course, but couldn't women scientists use these differences to find a niche for themselves that their male colleagues may not necessarily have thought of? It is still difficult for women to work in male-dominated fields in many ways, but the culture has changed drastically in the last several decades and there is now more space for new ideas and individuality."

All I can say is YES. There is space. There will continue to be more space. I happen to think that there may have always been space for new ideas and individuality but that it was not sufficiently recognized or acknowledged or supported. I am so glad to see this recognition coming along. I am even more glad to see research in support of the notion that including social relevance in computing coursework is good for the computing field itself.

Computing faculty, what do you think in reaction to this?

Full Science Careers Blog Post: http://blogs.sciencemag.org/sciencecareers/2011/03/a-genderbiased.html

Zen and the Art of CT Scan Investigation

2011-03-04T19:28:00.000-08:00

"Because we put emphasis on some particular point, we always have trouble. We should accept things just as they are". (Zen Mind, Beginner's Mind p. 120)

Yesterday I described my "plan" for learning first hand about the digital imaging equipment I have been studying for one of my projects. My plan turned out to be easier said than done - this was definitely not Grey's Anatomy. The staff were politely but determinedly cycling people in and out of the CT room as fast as they possibly could. Before I even had my bag picked up off the counter and had found my necklace they had wheeled the next guy in.

My attempts to be politely inquisitive met with only modest success. I started with a simple question "Is it blue?" Ok, probably not quite so inane (I hope), but the idea was to ask a very friendly and innocent sounding question (although a real question) about whether or not the contrast IV liquid was colored. How else might one get contrast? I was imagining all these colorful images on the imaging machines, because I have seen so many of them in my research. Very high resolution pictures of multicolored body parts with swoops and curves. Sometimes rotatable in 3D and able to be zoomed in and out and entered and exited in fly-by mode. So I figured blue was a likely color, not occurring naturally in the body - at least as far as I know.

The tech looked at me like I was a bit loony and I had to explain that I wanted to know how this liquid was going to provide the contrast to enable the CT scan to better read my head. I said I had an interest in digital imaging equipment in medicine - now trying another approach. She still wasn't interested in my line of inquiry. Eventually I managed to get the information that no, it was not colored, it worked by expanding the blood vessels so that they would stand out better. By the time I had gotten that far I had been jabbed and was being injected and she was out of there. So much for asking about the CT machine. It was 4:45 pm on a Friday and they probably just wanted to go home.

When I first walked in the room I had realized the people (at least 3) sitting behind the glass wall were back there to protect themselves from the radiation I was about to get blasted with and it was going to be impossible to ask them about their viewing equipment and software or to ask to see my scan. Rats. Foiled again.

However, another opportunity presented itself. Shortly after the first tech left, another one came in and said he was there to check the IV because sometimes it didn't ... do something or other right. Whatever it was, it sounded a bit fishy to me. Anyway, he was a bit more talkative and didn't give me any funny looks. He stood there for a minute or two seeming to stare at nothing much and suddenly ... I started getting really warm and it felt like liquid was flowing all over starting at shoulder level and migrating all the way down to my toes. Not only that, it felt like a lot of liquid was pooling in all sorts of strange places. So I said "What is it doing?" And he asked if I was getting warm, said that was normal, did I feel ok otherwise and that's all he said. He continued staring calmly at apparently nothing for another few moments. So I contemplated warmness and expanding blood vessels and wondered if I'd soon be leaking out of previously unknown pores. Then they told me (for the second time) I had to close my eyes. Darn it. No more watching what was going on.

Not long after, a bit of whirring and movement later, we were finished. The second guy came back and told me he had also been out there to make sure I didn't start vomiting! Now that explained all the questions about food and drug allergies and the "no eating for 4 hours prior" requirement and why he had so quietly stood there and asked me ever so casually if I felt ok!

"When we inhale the air comes into the inner world, when we exhale the air goes to the outer world...actually there is just one world...our throat is like a swinging door" (p. 29)

So while I felt like I might be developing new porousness I also concentrated on not moving my head because I had been told that if I moved my head or opened my eyes we'd have to do it all over again (meaning I get zapped with lots more x-rays). This was a hard task being the patient/researcher!

More so because I have a head cold and my sinuses are blocked and my nose wants to run and I periodically want to sneeze and...you know...all those things that go with having a nasty head cold and are exaggerated when lying on your back where it can all congeal into one gloppy spot in your head.

So I breathed...in...out...in......out......do not sniffle......in.......out.....do not worry about what is going on in your nose.... or the back of your throat...in...out... zen. Getting into the zen of it all. Or as Spock would have said "I became one with the CT machine". In goes the breath, out goes the breath.

I do have one clear success to report from the original "plan". It was very very easy to ask for a copy of my scan. Back at the front desk I checked off about 3 boxes on a sheet of paper and was told I could either wait 30 minutes or they'd mail it to me. Figuring it would be more than 30 minutes I opted for the mail route. They said it would go out Monday! No one batted an eye at my request! So, hopefully soon, I will have my own digital copy of my head scan.

Wait a minute. Not "hopefully".

"Perhaps". Non-attachment.

A CT Scan as an Opportunity to Get Personal

2011-03-03T15:40:00.000-08:00

As those of you know who have been following these postings regularly, I have written frequently about issues related to medicine - from medical informatics to digital imaging. I am working on several projects in this arena and sucking up as much information as I can get. There will be more to come because recently I have been digging into issues related to electronic health records. Fascinating stuff - although reading congressional legislation as officially posted in the Federal Register and elsewhere takes stamina and many lattes.

Tomorrow I am going to conduct a little investigation / experiment because an opportunity fell into my lap. This experiment relates to digital imaging and medical records.

I am going to have a CT scan. Nothing serious (unless they find a screw loose in my head) but they will be injecting me with dye to get a better view of my head - the object of interest. Not one to miss out on an opportunity, I am going to do several things:

I am going to see how much I can talk to the radiology techs about their equipment. Let's hope I get a happy chatty tech.

I am going to see if I can convince them (perhaps by tossing around well placed vocabulary they would not expect your typical patient to have) to let me in on some of their experiences with the imaging and storage systems.

I am going to try and get them to let me look at my scan, although I know from experience that they will clam up completely if I ask any questions about what I'm looking at. Nonetheless I will see how far I can get.

Finally, I am going to ask at the front desk what the procedure is for obtaining a digital copy of my scan. I know that legally my records are mine to ask for. I also know from a few experiences in the past that for some reason it can be very hard to get records. One gets run around in circles and stalled in all sorts of ways. In case any of my current medical personnel are reading this, I rush to note that these previous experiences were at a different medical facility in a different state.

Stay tuned. This could be interesting

The Pledge of the Computing Professional

2011-02-23T15:20:00.000-08:00

There is a movement afoot to form something known as The Pledge of the Computing Professional. There is a web site and an article appeared in the CACM Virtual Extension about it. I found the CACM blurb, followed it to the VE and then to my friend and colleague Anne Applin who is involved with developing the project. To quote Anne,

"The idea is fairly simple, to acknowledge that the computing professional has an obligation to use their specialized knowledge for the good of society and do no purposeful harm. It's for every graduate, not just those with the best grades (UPE) or those who join ACM."

I had not heard of this idea before so off and running I was asking questions and digging for information. I learned that the idea of the Pledge came from the Order of the Engineer, which in turn was inspired by the Canadian "Ritual of the Calling of the Engineer" which in turn draws inspiration (as I see it) from organizations going back in time to the Middle Ages when apprentices were formally inducted into trade guilds; all manner of secret or exclusive societies developed.

In truth, one can go back even further to the Romans and the Greeks who had formal associations for various craftsmen (I suspect no women were involved but I defer to the historians among you to confirm that). Or perhaps earlier - the Freemasons have very early historical origins. To make sure we are not being Eurocentric note that there were similar organizations in early India and China.

These societies always embodied a practical and a mystical side. The mystical side imbued them with something special and sometimes secret, while the practical side conferred some obligation or responsibility. Upholding values and traditions of integrity and honesty - the Hippocratic Oath comes to mind.

So I wonder...if computer science is to follow in this tradition that may be as old as civilization there are clear areas for developing an ethical and moral stance. What would be the mystical side? What mystical properties does computer science embody?

Healthy Mouse Batteries?

2011-02-21T17:42:00.000-08:00

My mouse has been bothering me. I persist in using a mouse tethered to my computer via the umbilical cord because I try not to use batteries. Batteries are just plain toxic. But, I confess, the tail of my mouse gets in the way. It gets tangled up and sometimes it has to be shoved out of the way or the mouse runs over its own tail. Poor thing.

I know, small potatoes in the name of being Green. Everywhere I look we are switching to wireless mice so the time may come soon when my mouse dies with a small squeak (or not) and I cannot replace it with anything but the tail-less version. So I have been researching batteries. In general, throughout my living space I use rechargeable batteries. Fewer heavy metals and other noxious chemicals go in the landfills. But eventually they do go in the landfills. And as the following site describes, though they beat normal batteries hands down, even a rechargeable battery is on some level bad news:

http://www.greenbatteries.com/aa-battery-faqs.html

The page claims that NiMH (Nickel-Metal Hydride) rechargeable batteries are environmentally friendly but this is true only by comparison to the other rechargeables. Although the disposal hazard is reduced because there is no (highly toxic) Cadmium in NiMH batteries, the site neglects to mention that there can be significant environmental degradation from current mining practices and processing of the base components.

What is a mouse user to do...

I found something really cool... How about a living mouse! No, I'm not suggesting you train a furry creature to let you hold it and scoot it around on the table with an antennae of some sort attached to it. PETA would probably be on *my* tail really fast - with justification. (Besides, you know what mice like to do besides eat)

Not yet ready for prime time, but MIT is at work on a virus-driven battery! What a totally cool idea. The viruses "create a cathode by coating themselves with iron phosphate and then grabbing hold of carbon nanotubes" (full article below). Cool. I think. It gives new meaning to "reach out and touch someone". Now if we all had these little critters powering our mice just think of the good it would do for the environment. I could get rid of my umbilical tail. And then maybe we could replace the battery in my laptop as well?

I wonder what viruses they use...

In the interests of science I am currently looking for a friend who would like to test one under my supervision as soon as they become available.

Article:
http://www.businessgreen.com/bg/news/1802467/mit-team-touts-sci-style-virus-battery

Publications page: http://belcher10.mit.edu/publications/

A New Spin on "Should I get a smart phone?"

2011-02-15T10:48:00.000-08:00

An article in yesterday's New York Times (link below) discussed advances in artificial intelligence, the future of AI and what it means to be human. As a computer scientist, many of the questions and topics posed were the same ones we have discussed for decades such as:

What are the possibilities and implications of using AI to augment human capability (i.e. help humans do better at what we already do well, or could do well) vs using AI to replace humans? The former has always been a goal with positive implications for most people and the latter has always been a goal that provokes uneasy, mixed reactions. That duality has not changed, although the article makes the point that the lines are blurring between the two.

An interesting example is the pervasive use of smart phones. No argument: they augment human capabilities: find information faster, sooner, in more detail, add to it, pass it on, discuss it, disseminate. Provoke thought, enlightening discussion, be "on" whenever we want.

I don't have a smart phone and people sometimes say to me: "Lisa, you of all people? No smart phone?". It isn't that I don't want one. My gadget nerd side wants one - bad. On the other hand, there is the issue of the blurring line between my human self and, dare I call it, my technology self. Something there says: maybe not a good idea?

I am already mainlined into my computer almost 24/7 and I when I think about the withdrawal symptoms that occur when I am off for very long...hmmm. Is my computer a part of my bloodstream and nervous system? When did that happen anyway? If we agree that yes, my computer is an extension of me, what happens if I get a smart phone and it never leaves my pocket. I have friends (you know who you are :) who post from their smart phones wherever they are (the library, the donut shop, the laundromat, 15 feet away from the parking lot) and I wonder what would happen if they were forced to stop? Could they do it without becoming as grouchy as a caffeine addict (of which I am one) who misses their morning coffee? Not a pretty sight.

The very last line in the NYT article is a quote that really bothered me: “The essence of being human involves asking questions, not answering them,” he [John Seely Brown] said.

Say what???????? Evolution would argue otherwise. Besides which, life would be SO BORING if I didn't spend time seeking answers to the endless barrage of questions my mind comes up with.

So...as we become more and more connected, and the lines blur between augmentation of human abilities and the replacement of human requirements to actually do things for ourselves ("hey, if I can have the computer take care of it, why should I do it?" goes the refrain) do I want a smart phone really?

Yes.
No.
Yes.
NO.
YES.
NES, YO.

This is why I have not bought one yet. I need to work this out - am I enhancing myself in a beneficial way or am I creating a part of myself that will supplant myself while I'm obliviously typing away?

I want to be the one answering the question. I don't want a computer to answer it for me. Much as I love them.

NYT Article that inspired this post (and discusses many topics that have nothing to do with what I discussed here): http://www.nytimes.com/2011/02/15/science/15essay.html?pagewanted=1&_r=1&nl=todaysheadlines&emc=tha26

Writing well about computing - What does it take?

2011-02-10T11:53:00.000-08:00

For the past 10 days or so I have been following a conversation in the LinkedIn group Science Writers. The conversation started when someone asked for opinions about whether or not it was necessary to have a science background to succeed as a science journalist. Her exact words were "to be a good science journalist". Oddly enough, the woman who asked the question has had a successful career as a science journalist for 20 years. The question turned out to be more about whether or not people felt that she should follow her interest in gaining additional education in environmental journalism. By most standards she would no doubt be considered "good" already as she is publishing in widely read science magazines.

The comments back to her were interesting though from the point of view of perceptions and marketing of computer science. Many of the respondents were people without a science background so they predictably replied that no, you don't need a science background. Yes, it was a self selected respondent group. However, they had some points worth considering. One that stood out was the claim that it was more important to be a good writer than to have a science background and that it was easier to obtain "scientific literacy" than the "fundamental craft of writing".

Now, I would take some issue with that comment. I do believe that at least in computer science, given the widespread misconceptions about what we are, what we do, what we don't do, and the frequency of journalism articles that are off target in one area or another - it IS important to have a background in some area closely related to computing if you want to tackle head on the public perceptions of what who how etc. That takes more than "scientific literacy" or in this case the more narrow "digital or computing literacy", terms that we are currently wrestling to define.

There are no doubt writers who are so darned good that they can do the background research, talk to the computer scientists and write an article that is accurate, digestible, interesting and has solid content for public consumption. But as with any other interdisciplinary situation those cross over professionals are a rare breed.

That said, I agree that a writer has to be a "good" writer to get across the computing points so that the general public is interested and gets the correct information. An academic writing style flops with the general public. Writing well is as much a creative and technical endeavor as computing. Thus I would argue that neither the computing background nor the writing background trumps the other.

Medical Informatics Musing

2011-02-03T15:13:00.000-08:00

Not for the first time, I am thinking about the complex world of health care informatics. At the moment I am studying efforts underway to standardize and put into electronic form medical data from personal health records, laboratory and research centers, existing specialized databases and archival hard copy. There are people devoting hundreds of hours to this effort, sometimes on a volunteer basis. And you want to talk about opportunity to do cool things...

Several organizations promote standards for medical terminology and for the most part they are complementary. They have their own histories and apply themselves to different subsets of data. In the United States several federal agencies manage data (in addition to many private and non profit organizations too numerous to list). Examples include the National Library of Medicine, The National Cancer Institute, the Centers for Disease Control and Prevention, The Agency for Healthcare Research and Quality, The Office of the National Coordinator for Health Information Technology. Different data sets, different functions, different structures. Medical clinicians I have recently spoken to tell me the data gathered, maintained and disseminated by government, non profit and private groups have played an incredibly positive role in improving patient care nationally and internationally.

However, there is still a lot of work to do and much of it hinges around harmonizing data standards and developing the most effective ways to computerize these data as we move forward.

The most widely used international medical terminology set is SNOMED-CT, shorthand for Systemized Nomenclature of Medicine - Clinical Terms. In addition to providing detailed terminology definitions in machine readable form, SNOMED (as it is often called for short) provides a logical structure of relationships between concepts that covers virtually all areas of medicine.

Another large internationally accepted set of medical terminology and structure is LOINC, acronym for Logical Observation Identifiers Names and Codes. The data maintained in LOINC format comes primarily from research labs and is available for use by hospitals, physicians and others.

The third large and highly visible standardization effort is RxNorm, terminology and relationship structure for clinical drugs (to most of us that means prescription drugs) approved for use in the US. As with SNOMED and LOINC, RxNorm defines terms in machine readable format.

These are just the 3 biggest names associated with computerized standardization efforts. And if you think there are a lot of acronyms here, that is just the beginning. I suppose there may be no more acronyms in the medical world than in the computer science world. Just as non computer scientists often find our discussions puzzling and difficult to comprehend, non medical personnel may initially find it eye boggling to wrap their head around medical terminology and standards documents.

I'm in neck deep reading about these standardization efforts right now and it IS fascinating. There is a real coming together of two fields and two worlds here and a huge opportunity for computing and medicine. I am impressed with the enormity of the task needed to bring all these data into harmony with one another. Advances in computing technology and in medicine are each advancing so fast ... cutting edge on both sides.

Questions from an Industry Point of View

2011-01-28T11:43:00.000-08:00

Yesterday I had another conversation with an industry acquaintance about interdisciplinary computing. Once again the conversation drained my latte but left my head full of interesting ideas. Part of our conversation was intentionally oriented towards what a large corporation might want to know about interdisciplinary computing initiatives. It is always refreshing to look at things from new perspectives and ask the tough questions. I'd like to share some of the questions that arose and my initial thoughts on them.

For fun, I'm going to pose them in the form of a fictional conversation between myself and a CEO. I'll call her CEO C (for computing :) . This is *not* a report of an actual conversation with a CEO.

What might CEO C want to know?

CEO C asks: From having discussions of the benefits and challenges of interdisciplinary computer science initiatives (see Lisa's posts going back to Jan 7th in particular) how can you then create action? Cynical CEO C says she has seen many great ideas that don't make it past the idea or prototype stage.

My Thoughts: There are examples of success out there (see my post on the 10 year track record of an IC program in Missouri). We need to ferret out as many examples of success as we can find and look carefully at what made them succeed. The people involved in the Missouri program have a wealth of information to share. There are other programs out there in academia - we need to do our research and look for patterns. We also need to nail down what did not work and why. We don't need to stick to Computer Science. We can learn a lot from other disciplines that have a record of interdisciplinary integration. Two areas come to mind. The Physics Education community has done an excellent job of gaining acceptance and respect for education research from with Physics departments. Math Education has also done well. These are examples of interdisciplinary success of a particular type - we can learn from them how they got there.

Bottom Line: We do not have to reinvent all the wheels. We can learn from others.

CEO C then asks: How will you get measurable results?

My Thoughts: This sounds like a classic Goals, Outcomes, Measurables discussion that needs to take place. Given that this is an area I consult in, I could go on for a long time about the topic. But I'll keep it brief and just say that if the time is put in up front to develop these items clearly and concretely and in the proper order, understanding what each term means, then we will be in a position to obtain those measurables.

CEO C then asks: Ok, are you gaining a better workforce out of these initiatives? Global competitiveness is very important.

My Thoughts: I'm sure that others will have excellent ideas to add, but my thoughts on this are that one way to answer the question is to build it into the development of Goals/Outcomes/Measurables. Ask the right questions, develop the right assessment mechanisms and follow up longitudinally. Include industry deeply in the conversation.

CEO C says as a comment: If you accomplish all of the above, we will spur the economy and overall economic growth.

I respond: Yes :)

An Interesting Interdisciplinary Computing Program With a Solid Track Record

2011-01-21T22:43:00.000-08:00

When I take a look at the list of items that our interdisciplinary computing group brainstormed for an ideal environment I immediately think of a really interesting academic program at Northwest Missouri State University called Interactive Digital Media. This 10 year old program is truly interdisciplinary and one of the original developers was at our meeting: Carol Spradling. So I had to ask Carol (who I have known for many years) if she would sacrifice one of our snack breaks to tell me more so that I could share it here.

The final and perhaps most agreed upon criteria for success listed in the previous post was the following:

"Intellectual content from all represented fields are equally present. ...

Having intellectual content from each discipline is critical if we want to avoid the perception that interdisciplinary computer science is the application of computing to another field and nothing more."

The Interactive Digital Media (IDM) major brings together 6 faculty, 2 each from the Computer Science / Information Systems department, the Art department and the Mass Communications department. This unique major has three concentrations to choose from: Computer Science, New Media, Visual Imaging. Local industry has been involved from the inception of the program as a multimedia minor within Computer Science.

The development of the IDM program was a lot of hard work, but the trust that is so important was built by dedication and constant communication that continues today. Faculty meet regularly to adapt what each teaches based upon what the others are teaching. Only the capstone course is team taught. As a result, the faculty have to be committed to working as equal contributors and to developing creative ways of achieving synthesis. The necessary communication is a non trivial time investment, one of the challenges to interdisciplinary work. When new faculty come on board, there can be a need to go back and revisit issues to bring that person up to speed. Finally, as we all know, technology advances wait for no one. Courses have to be continually updated and new technology always has to be learned, considered and bounced off their industry partners - and tried out. Ideas have not always gone as planned, but they have adjusted and moved forward. Team work makes this possible.

The incremental and inclusive development of this program is a great example of how many of the hurdles facing interdisciplinary computing can be overcome. In the late 1990s, Carol told me, they realized just how much there was a need for people with cross disciplinary skills. Specifically, they saw the need for design, technology, social and communication skills. They had done their homework, interviewing industry and gathering statistics on jobs available to graduates. They decided to partner with Mass Communication. Soon they realized that bringing the Art department into the team was important. Together the 3 departments (without an influx of funding and no ability at the time to create an independent major) developed course ideas and asked local industry for feedback and suggestions about those courses and their syllabi.

Over the last ten years Carol has watched the program develop from a minor to a major program of study. She related how she now sees students go out and get exciting jobs; jobs they are passionate about. Carol is particularly pleased to report that there is a high percentage of women in the program. In fact she said the influx of women "thrills" her. She is thrilled to see young women feeling that they can get into a technical field. "There are so many fields that have technical components. Social media [for example]...[These fields] require the technical knowledge".

Where do students go and what kinds of jobs do they take after graduation? In answering my question I believe that Carol might have used the phrase "all over the place". Large companies, small companies, broad work, niche work. Programming, database work, combined database and programming, technical project management, graphic design that requires fluent programming - to list just a few examples. There have been some truly unexpected employment stories such as the student who became an instructional designer for a dairy association. The student trains corporate personnel how to integrate technology into their jobs.

Another student is employed in a school of nursing, working with a course management system, addressing curriculum issues and in depth multimedia use in general. This student has tapped into the national need for nurses and the trend that more nursing programs are going on-line, thus needing assistance delivering instructional materials. Coincidentally, I had been talking the week before to the wife of a friend who is nearing completion of an online nursing program here in the San Diego area. The availability of this program has been the only way that she, as a non traditional student ("older" meaning in her 30s, and an immigrant), can make the career change she desires. So when Carol spoke about the excitement many students (and faculty) feel about the opportunities opened up by the Interactive Digital Media program, I understood the importance of her program from several perspectives.

The vision and dedication of the faculty Carol works with has brought the type of success in enrollments, job placement and other factors that allowed the program to be elevated from a the minor to a major program of study. The successes of the program sounded to me like they have been quantifiable; not only has Carol published on the program (there is a paper written in 2008 in the ACM Digital Library) but they have used a university wide Total Quality Management process to ensure continual improvement. TQM is itself an interdisciplinary process, thus complementing the goals of the IDM program.

Establishing and maintaining trust. Overcoming vocabulary and perspective differences. Ensuring depth of content and equality of content across disciplines. These were the major issues listed in the "challenges" discussion and the Interactive Digital Media program has tackled them well.

The program has achieved gains for Computer Science and the partner disciplines, including increased student diversity and overall numbers, new and broader job placements and excellent relationships with local and regional industry. As Carol put it, the program has opened up a new world for students. She was also pleased to tell me students in all three concentrations (not just the Computer Science concentration) are embracing technology and moving on to use it in other ways after completing their technical coursework. Something for any computing faculty to be proud of.

An Ideal Environment for Interdisciplinary Computing

2011-01-18T17:24:00.000-08:00

After discussing the benefits of engaging in interdisciplinary computing and the challenges we face we considered what an ideal climate for fostering interdisciplinary computing efforts might look like. If you recall from the earlier posts about this meeting, these conversations took place our first morning, as a sort of "lay it all out on the table" exercise. The intent at this stage was not to eliminate ideas that might be arguably "impossible or impractical", nor to come to a consensus or final list.

I found it very productive to go beyond the initial benefits and challenges conversations to a discussion that drew upon those ideas. This was where some real sizzle came into the conversation. By this point people were ready to rock and roll* with their visions. Some ideas were familiar and some were not; sometimes one idea might appear to contradict another idea. But it was all material to sink one's teeth into.

I'd like to share some of these brainstormed ideas; they provide food for thought and are a pre-requisite to the inevitable "what next and how do we get there" questions.

Hopefully they will pique your imagination as they did mine.

- The vertical school based system is eliminated i.e. topics are not rigidly identified as belonging in a specific year.
- Coursework at the college level is not limited to people who already have "the background" (this phrase is in quotes because defining it is a very interesting discussion in itself!)
- There exists a highly supportive environment for people to build bridges between disciplines, share perspectives and talk. This will produce greater trust, competence and value.
- At the college level each department creates two endowed chairs whose focus is on the support and development of interdisciplinary computer science / computing.
- Budgets include a guaranteed line item dedicated to interdisciplinary computer science / computing.
- People on campus who are dedicated to interdisciplinary efforts are actively located and supported at all levels (administration, staff, faculty).
- We locate other models outside of computer science where interdisciplinary collaborations already work, we study and learn from them.
- Colleges and universities reward interdisciplinary work with tenure.
- Recognition that the issues and focus are different at the K-12 (pre-college) and college level.
- Recognition that there is more to computer science than programming and we model that recognition in the classroom.
- We include more visualization (through any of a number of mechanisms) in computer science coursework.
- Vertical communication within a university is smooth.
- Peer reviewed journals that cross disciplinary boundaries are highly valued.
- Workload assignments recognize that interdisciplinary computer science / computing teaching and research may take extra time and workloads are adjusted accordingly.
- There exist more social venues for informal but critically important interactions in interdisciplinary computer science / computing work - conferences, workshops. Increase those "water cooler conversations".

- Intellectual content from all represented fields are equally present. This point came up often, in various guises, during the two days we met.

Having intellectual content from each discipline is critical if we want to avoid the perception that interdisciplinary computer science is the application of computing to another field and nothing more.

* We were staying at the Hard Rock Hotel, which in addition to providing all the meeting facilities and services of a more traditional hotel, was another "think outside the box" experience.

An Unusual Computational Science Educator

2011-01-12T22:21:00.000-08:00

Sometimes crisis propels an existing passion to the forefront of someone's life. This is the one line explanation of how Shodor was founded 15 years ago to advance science education via computational modeling and simulation.

When I first posted about the Interdisciplinary Computing meeting I attended last week, I made a point of mentioning Bob Panoff. Bob is not only a truly interdisciplinary individual but a great person to talk to. So as soon as I could I pried him away from others so that he could speak to me for this report.

If you haven't already looked at his company web site, before you do so, think about what his company name might mean and why he chose it. Don't peek. We'll come back to that. It says a lot about Bob's attitude towards life and work.

You never know where a conversation with Bob will go. It starts at point X and the next thing you know you are somewhere else entirely. But it all makes sense.

It often starts with some interesting comment or question. He asked me: Do you know what "Quantitative Emotion" is? Given my background, I started thinking about AI. But that was not what he had in mind. He teaches the answer this way: by sending 8th grade students (approx age 13) out into shopping malls to ask people one of two questions.

"is 40% large or small?" Most people respond "it is large".

"is 2/5 large or small?" Most people respond "it is small".

Hmm.... Changing the representation of data makes people feel differently about what something means. Quantitative Emotion. Interesting....

A post-mall conversation with the students (and me!) leads to discussion of multiple representations, and how to present data in different ways - generally through computation and simulation of that data. Bob is all about computational simulation.

One of Bob's very favorite questions, which he also sprung on me, is: "How do I know that it is true?"

What? Know what is true? Answer: most anything. How do you know that it is true?

This question underpins much of Shodor's work in developing science education materials. "How do you know?" Computation and simulation provide the means to analyse and answer the question. How did Bob arrive at this central question? While in graduate school he taught himself how to use computational simulations to analyse the interactions between pieces of physics problems and to measure the validity of calculations.

Although not a computer science student, he read as many numerical methods books as he could find, most of which had been written in the pre-computer era. (Part of me wondered just where he found these ancient dusty texts, but we were racing the clock against lunch break so I didn't ask). He taught himself to use computing to apply those numerical methods and solve the physics problems.

Pattern recognition and pattern characterization then fueled his interest in simulations. The more he created simulations the more convinced he became that science education in general could be improved through creating effective simulations. How to choose between different approaches in the lab for example, how to compute the properties of materials such as liquid helium, deuterium and solids with impurities. He refers to himself at that period of his life, when he worked in academia, as a computational physicist. Along the way he worked in a supercomputing center. He spent time looking for commonalities between disciplines and how they did use or could use computing, and he worked to share those ideas with other disciplines. In his spare time he started a group to improve science education. He started by delivering workshops.

Crisis struck in 1994 when he was told he had a kidney tumor and 6 months to live. At this point he decided to follow his true passion with what time he had left. Abandoning formal academia, he incorporated Shodor and went full steam ahead with computational science simulation with the mission of improving science education at all levels.

Short and Dorky. Bob was once called "SHOrt and DORky" by a student, hence the company name. Of course. Creative and humorous and ready to use whatever comes his way.

15 years later Bob Panoff and Shodor are still at it and highly successful. Bob works full time following his passion for computation in the service of science education. As important, his desire to share his work and ideas land him in places like our meeting. Go Bob.

Interdisciplinary Computing: Bumps and Holes in the Road

2011-01-09T18:00:00.000-08:00

There are of course setbacks and challenges to implementing interdisciplinary computing and our group discussed those as well (if you haven't read the previous two posts, this is the third in the thread). As we had people with backgrounds past and present in biology, computer science, math, physics, music - performance and theory, architecture (not the computer kind), healthcare, there were lots of angles.

In our first morning discussion of these challenges, some themes popped out, just as they had with our discussion of positive experiences. Here is some of what arose for consideration:

Lack of common vocabulary. Specialties have their own lingo, buzzwords, abbreviations, and sometimes the words are the same words used by another field but with different meanings. Engaging in conversation with a specialist in another field can be an instant reminder about how much we have internalized and take for granted when we talk among ourselves.

Different perspectives on appropriate methodologies for research, assessment, reporting, project development. This is a huge topic. Simple to explain and discuss (but not necessarily resolve): is first person or third person expected in a formal write up? Not at all simple to resolve: is statistical or qualitative research desired or valid...what type of statistical or qualitative...how is rigor agreed upon? Really difficult: what does the other field actually *do* when they design and implement a program or project and can it be (should it be) fully understood by the participant from another discipline who works on the project?

Application level skill issues. This point follows up on the last point in the previous paragraph. One example: Discipline X wants to use software A; Discipline Y wants to use software B. Both have their well supported reasons. How to resolve the question to everyone's satisfaction? Similarly, programming and programming language issues can be "exhausting" as one person put it so well. What to use, how many to use, does it have to be a specific language? You know, we have these conversations even within computing; we exhaust ourselves talking about languages. When interdisciplinary teams tackle the language questions the discussion increases in complexity several orders of magnitude.

Trust. This is perhaps one of the biggies. Perhaps the biggest. People related experiences about the need to build trust between disciplines, between people at different levels of an organization, between people with different responsibilities.

Even when there is abundant goodwill on all sides trust has to be earned. It cannot be taken for granted or else some innocent blunder may set back or seriously damage a project. Sometimes, there are large silos that people work in and these have to be bridged. Note: lots of words were used, and I'm not sure which I prefer - bridging seems to convey the positive intentions of everyone in the meeting.

What is computing and/or computer science anyway? This is another topic where even within our own computing discipline(s) we do not always agree. Exhausting. Another exhausting topic. Members of our meeting related experiences about perceptions and mis-perceptions of what "it" is, and in particular how the word "technology" fits in. Similar stories have appeared on the SIGCSE list and many other forums.

I'm intentionally not repeating specific examples of the setbacks we discussed because I don't want to unintentionally embarrass anyone nor imo is it relevant for this post that is trying (with questionable success) to stay manageable in length. I want to focus on the high level issues.

A few summative related issues that lead to setbacks for interdisciplinary initiatives: the tension b/w tools and theory; specialists vs. generalists vs. interdisciplinarians (blogger thinks that is not a word... how timely!); pure vs. applied; student majors vs. student non-majors. And the notable point that silos can occur within a department - not just between departments.

Challenges that were phrased as questions included:

How to help people in a partner discipline continue to use mutually agreed upon / developed concepts as their students move up within their curriculum? Problematic.

How to keep an interdisciplinary course from turning "light and fluffy" or just an exercise in tool use? If students don't have a quantitative background for example, how do you give them that background sufficiently to proceed with the course? Just adding a prerequisite or two or three doesn't address the problem head on.

Computer science as a discipline has our set of "big ideas". We can abstract them, but how do we then help other people to understand and want to work with them? (this harks back to the vocabulary, method and perspective challenges)

And to end on a LARGE note: there are a whole set of different challenges for the interdisciplinary team that is starting a program from the ground up vs. the team that is working within existing programs and major fields of study. Even more so when the collaborators consist of computer scientists and experts from the non sciences.

phew! Much of the above will not be news if you have been involved in interdisciplinary efforts. However! that is one reason why I chose to start the conversation several posts ago with the upbeat and positive side of this work. No problem is impossible to address in one way or another. But to do so we had to first lay them out and lay them out we did!