PreprintCited by 106Artificial Intelligence in GamesArtificial Intelligence ApplicationsSport Psychology and Performance

The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.

Superhuman Artificial Intelligence Can Improve Human Decision Making by Increasing Novelty

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Shin, Minkyu, Kim, Jin, van Opheusden, Bas, Griffiths, Thomas L.·2023·Proceedings of the National Academy of Sciences

Preprint — published as 10.1073/pnas.2214840120 · Paper page

Abstract

How will superhuman artificial intelligence (AI) affect human decision making? And what will be the mechanisms behind this effect? We address these questions in a domain where AI already exceeds human performance, analyzing more than 5.8 million move decisions made by professional Go players over the past 71 years (1950-2021). To address the first question, we use a superhuman AI program to estimate the quality of human decisions across time, generating 58 billion counterfactual game patterns and comparing the win rates of actual human decisions with those of counterfactual AI decisions. We find that humans began to make significantly better decisions following the advent of superhuman AI. We then examine human players’ strategies across time and find that novel decisions (i.e., previously unobserved moves) occurred more frequently and became associated with higher decision quality after the advent of superhuman AI. Our findings suggest that the development of superhuman AI programs may have prompted human players to break away from traditional strategies and induced them to explore novel moves, which in turn may have improved their decision-making.

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Authors
Shin, M., Kim, J., van Opheusden, B., & Griffiths, T. L.
Affiliations
  • City University of Hong Kong (HK)
  • Tongji University (CN)
  • Princeton University (US)
Corresponding author
  • Shin, Minkyu
  • Kim, Jin
  • van Opheusden, Bas
Venue
Proceedings of the National Academy of Sciences
Published
2023-03-13
Volume
120
Issue
12
Pages
e2214840120-e2214840120
ISSN
0027-8424 (ISSN-L)
OpenAlex
W4324028585
Cited by
106
References
1
Citations by year
2026: 30 · 2025: 37 · 2024: 25 · 2023: 14
FWCI
9.99
Type
journal article
Language
en
Open access
Locations
  • Proceedings of the National Academy of Sciences (publishedVersion, cc-by-nc-nd)
  • PubMed Central (publishedVersion, cc-by-nc-nd)
  • PubMed (publishedVersion)
  • RePEc: Research Papers in Economics (submittedVersion)
  • arXiv (Cornell University) (submittedVersion)
  • CityU Scholars (submittedVersion, cc-by-nc-nd)
  • PsyArXiv (OSF Preprints) (submittedVersion, cc-by)
  • PsyArXiv (OSF Preprints) (submittedVersion)
  • arXiv (Cornell University)
Topics
  • Physical Sciences › Computer Science › Artificial Intelligence › Artificial Intelligence in Games
  • Physical Sciences › Computer Science › Artificial Intelligence › Artificial Intelligence Applications
  • Social Sciences › Psychology › Developmental and Educational Psychology › Sport Psychology and Performance
Keywords
human decision-making, Go, novelty, counterfactual analysis, human-AI interaction, professional Go players, game strategy
MeSH terms
Artificial Intelligence, Decision Making, Humans

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