In the coming
days, Google DeepMind’s alphaGo program is expected to defeat one of the
world’s leading professional Go players, Lee Sedol, in a best-of-five
unhandicapped Go matchup. AlphaGo has already won the first two games, and a
profound reality is upon us: the walls are crumbling around one of the last
major strongholds of superior human intelligence. This looming defeat raises
important questions for research on human intelligence. What can we learn from
continued advances in gameplay artificial intelligence? What role can games
play in measuring continued progress in research on intelligence more generally?
Is there an “endgame” for the role of games in AI research?
The lasting
importance of games in AI research, beyond serving as a source of well-defined
and widely understood challenge problems, is that they provide a unique means
of measuring intelligence through task-based comparisons. Intelligence is
notoriously difficult to measure, even in humans. Games offer simple and useful
comparisons of skills, reasoning skills. Overall, games provide a rich
framework for measuring progress in machine reasoning capabilities through
competitive comparisons. Computer Go will likely continue to be relevant to AI
researchers for quite some time, and it will be exciting to see how the related
wide range of challenges are met by the broad AI research community.
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