Education, Technology, and Empirical Data

Deven Desai

Deven Desai is an associate professor of law and ethics at the Scheller College of Business, Georgia Institute of Technology. He was also the first, and to date, only Academic Research Counsel at Google, Inc., and a Visiting Fellow at Princeton University’s Center for Information Technology Policy. He is a graduate of U.C. Berkeley and the Yale Law School. Professor Desai’s scholarship examines how business interests, new technology, and economic theories shape privacy and intellectual property law and where those arguments explain productivity or where they fail to capture society’s interest in the free flow of information and development. His work has appeared in leading law reviews and journals including the Georgetown Law Journal, Minnesota Law Review, Notre Dame Law Review, Wisconsin Law Review, and U.C. Davis Law Review.

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3 Responses

  1. A.J. Sutter says:

    On what basis can anyone one make a “promise of improved educational outcomes”? First of all, how long a baseline does one need to judge this — until students have grown up to be fully-participating citizens in society? How do such outcomes compare to those of an era of less data, but smaller classroom sizes, for example? And while you’re right to point out the privacy and fairness issues, there’s also the question of how much all this data collection and objectification of students will interfere with teaching and learning.

    Many of these “improvements” are just projections of the latest scientistic fads, and also of many Baby Boomers’ belief that with the right tricks they can turn their kids into Übermenschen. No doubt (and G-d willing) in a few years this will look tremendously dated, as will the “Google mindset”.

  2. Deven Desai says:


    Great points. Although I won’t go into details here, the group was well aware of your points and had some interesting debates about metrics, class size, and the problems of possible interference with teaching and learning. I did not discern agreement about these issues. The one thing that struck me was a sense that at least having data and trying to use it to assess whatever goal any group aimed at was a good idea. That idea reminds me of the social entrepreneurship movement which also tries to embrace setting goals with some outcome measurement and then seeing whether those goals were met, and if not, what might explain them.

    On a related note, it also reminds me of some material about espionage that argued that the difference between English and U.S. approaches is that the English have fewer resources and rely on human networks whereas the U.S. loves to gather vast amounts of information and then see what it can discern. My guess is that there is no perfect answer to which is better. And, as many in the session pointed out, a blend of methods may be the best way forward.