Skip to main content

Faculty & Research

Close

Training With AI: Evidence From Chess Computers

Journal Article
The authors suggest that AI can help decision-makers learn; specifically, that it can help them learn strategic interactions by serving as artificial training partners and thus help them to overcome a bottleneck of scarce human training partners. The authors present evidence from chess computers, the first widespread incarnation of AI. Leveraging the staggered diffusion of chess computers, the authors find that they did indeed help chess players improve by serving as a substitute for scarce human training partners. The authors also illustrate that chess computers were not a perfect substitute, as players training with them were not exposed to and thus did not learn to exploit idiosyncratic (“human”) mistakes. The authors discuss implications for research on learning, on AI in management and strategy, and on competitive advantage.
Faculty

Associate Professor of Entrepreneurship and Family Enterprise