Training with AI: Evidence from chess computers

Fabian Gaessler, Henning Piezunka

Research output: Contribution to journalArticlepeer-review

23 Scopus citations

Abstract

We 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. We present evidence from chess computers, the first widespread incarnation of AI. Leveraging the staggered diffusion of chess computers, we find that they did indeed help chess players improve by serving as a substitute for scarce human training partners. We 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. We discuss implications for research on learning, on AI in management and strategy, and on competitive advantage.

Original languageEnglish
Pages (from-to)2724-2750
Number of pages27
JournalStrategic Management Journal
Volume44
Issue number11
DOIs
StatePublished - Nov 2023
Externally publishedYes

Keywords

  • artificial intelligence
  • chess
  • difference-in-differences
  • learning
  • strategic interaction

Fingerprint

Dive into the research topics of 'Training with AI: Evidence from chess computers'. Together they form a unique fingerprint.

Cite this