Bilalic, M., Graf, M. and Vaci, N. orcid.org/0000-0002-8094-0902 (2024) Computers and chess masters: The role of AI in transforming elite human performance. British Journal of Psychology. ISSN 0007-1269
Abstract
Advances in Artificial Intelligence (AI) have made significant strides in recent years, often supplementing rather than replacing human performance. The extent of their assistance at the highest levels of human performance remains unclear. We analyse over 11.6 million decisions of elite chess players, a domain commonly used as a testbed for AI and psychology due to its complexity and objective assessment. We investigated the impact of two AI chess revolutions: the first in the late 1990s with the rise of powerful PCs and internet access and the second in the late 2010s with deep learning-powered chess engines. The rate of human improvement mirrored AI advancements, but contrary to expectations, the quality of decisions mostly improved steadily over four decades, irrespective of age, with no distinct periods of rapid improvement. Only the youngest top players saw marked gains in the late 1990s, likely due to better access to knowledge and computers. Surprisingly, the recent wave of neural network-powered engines has not significantly impacted the best players – at least, not yet. Our research highlights AI's potential to enhance human capability in complex tasks, given the right conditions, even among the most elite performers.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2024 The Author(s). British Journal of Psychology published by John Wiley & Sons Ltd on behalf of The British Psychological Society. This is an open access article under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits use, distribution and reproduction in any medium, provided the original work is properly cited. |
Keywords: | AI; Bayesian analysis; generalized additive models (GAM); longitudinal study; multiple change point (MCP) |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Science (Sheffield) > Department of Psychology (Sheffield) |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 09 Dec 2024 11:33 |
Last Modified: | 09 Dec 2024 11:33 |
Status: | Published online |
Publisher: | Wiley (The British Psychological Society) |
Refereed: | Yes |
Identification Number: | 10.1111/bjop.12750 |
Related URLs: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:220321 |