Interface University and Other Scenarios for the AI Economy | Artificial Intelligence (AI) - EDUCAUSE Review

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.

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David Staley, Associate Professor of History, The Ohio State University argues, As artificial intelligence moves us to a world without work, what does that mean for higher education institutions and their mission in the new economy?

Photo: >Mark Pernice © 2020

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. 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. Go, invented in China more than 2,5000 years ago, is a deceptively simple game: on a board with a grid of black lines (usually 19x19), two players alternately place black and white stones on the intersections... 

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.

This is the less plausible scenario, however. Instead, artificial intelligence most probably will have reached the stage of development where it is replacing many human tasks, even complex cognitive tasks—but not every human task. The more likely future is one in which humans and artificial intelligence work in tandem to engage in cognition, in a division of labor between what artificial intelligence does better and what humans do better. Learning to cooperate, learning to think together, will become the raison d'être of higher education.

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Source: EDUCAUSE Review