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This article is adapted from David J. Staley, Alternative Universities: Speculative Design for Innovation in Higher Education, pp. 121–140. © 2019 Johns Hopkins University Press. Reprinted with permission of Johns Hopkins University Press.
In March 2016, AlphaGo—a computer algorithm developed by Google's DeepMind—defeated Lee Sedol, one of the world's top Go players, 4 games to 1, writes David Staley, Director of the Humanities Institute at The Ohio State University.
The result was a worldwide sensation: twenty years after World Chess Champion Garry Kasparov was defeated by IBM's parallel-processing computer Deep Blue and five years after IBM's Watson easily beat the two best Jeopardy champions, artificial intelligence had once again seemingly surpassed human intelligence.
At the time of Kasparov's defeat, many observers (myself included) wondered if a computer would ever defeat a human at Go.1 Chess is a complex game, of course, but at its heart, it is a game of logic and calculation. Given a particular board configuration, a player need only calculate all the possible combinations of moves and decide the best path among those choices. Computers are particularly good at brute-force calculation of this type, and thus it seemed inevitable that as computational power grew exponentially, someone would eventually create a device that could calculate more combinations faster than a human might.
Go, however, is not a game that is easily given over to brute-force calculation, and that is why so many of us thought it unlikely that a computer would defeat a human...
AlphaGo was programmed using machine learning techniques. Unlike Deep Blue, AlphaGo was programmed to learn via experience. It played thousands and thousands of games, each time being programmed to "learn" from the experience of playing. It has been said that to master any domain, one must practice for 10,000 hours.3 With machine learning algorithms, however, computers are developing the ability to become masters...
Conclusion It is indeed possible that artificial intelligence will advance to such a degree that it achieves "general intelligence." Should that day arrive, it is likely that artificial intelligence will have taken over most jobs.18 In such a scenario, the nature and purpose of higher education will have irrevocably changed: higher education will have reverted to its pre-Morrill condition as a luxury, perhaps even a luxury for the many. But in such a scenario, college for human capital development—the guiding logic of higher education since the 1980s—would no longer be the rationale.
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