Computational Information Design

December 12, 2008
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Tonight I had the good fortune to attend a talk by Ben Fry on Computational Information Design at the Broad Institute of MIT and Harvard. Ben Fry is one of those rare human beings whose work spans from the heart of academia (he’s worked with Eric Lander on visualizing genetic data)  to popular culture (he work appears in Minority Report and The Hulk). And he’s an outstanding speaker.

The content of his talk reflected his dissertation work at the

Tonight I had the good fortune to attend a talk by Ben Fry on Computational Information Design at the Broad Institute of MIT and Harvard. Ben Fry is one of those rare human beings whose work spans from the heart of academia (he’s worked with Eric Lander on visualizing genetic data)  to popular culture (he work appears in Minority Report and The Hulk). And he’s an outstanding speaker.

The content of his talk reflected his dissertation work at the MIT Media Laboratory, his postdoc work the Broad Institute, and some of his more recent work  as a designer and consultant. I can’t do justice to the talk, which unfortunately is not available in any recorded form. But I do suggest you seize the opportunity to hear him speak, should it come your way. He communicates the power of visualization through examples, in a way that conveys both their practical value and their beauty.

The Q&A session was almost as long as the talk, and probably could have gone on indefinitely if the organizers hadn’t finally cut it off. Suspecting that I was one of the few non-academics in the audience, I asked two eminently practical questions: how do you know that a visualization is effective, and how d you guard against a visualization skewing your perception of the data?

Fry’s answers were incisive. He judges the effectiveness of a visualization based on whether people give up their previous tools to use it. And he selects problem areas where he sees a significant opportunity to improve the state of the art. That way, the difference in adoption is so obvious that you don’t need to perform user studies to observe it.

As for concern with visualization skewing perception of the data, he acknowledges it as a valid concern but points out that we don’t seem to raise the same concern with non-visual (e.g., textual) data presentation. Somehow we are especially suspcious of aesthetic representation, a sort of “don’t hate me because I’m beautiful” bias. He adds that the risk of design skewing our perception is dwarfed by the cost of not designing at all.

Visualization is a tricky subject, and I’ll freely admit that I’m underwhelmed by much of the work I’ve encountered. Perhaps my past work in information visualization makes me a particularly harsh critic. But Fry presents a compelling picture–or rather, a compelling video, since his work is full of motion. My only complaint is that he hasn’t explored the world of search and information retrieval. His work seems to beg for application in that domain. Food for thought.

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