Leveling the Playing Field -- Fairness in AI Versus Human Game Benchmarks
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Abstract (arXiv)
From the beginning if the history of AI, there has been interest in games as a platform of research. As the field developed, human-level competence in complex games became a target researchers worked to reach. Only relatively recently has this target been finally met for traditional tabletop games such as Backgammon, Chess and Go. Current research focus has shifted to electronic games, which provide unique challenges. As is often the case with AI research, these results are liable to be exaggerated or misrepresented by either authors or third parties. The extent to which these games benchmark consist of fair competition between human and AI is also a matter of debate. In this work, we review the statements made by authors and third parties in the general media and academic circle about these game benchmark results and discuss factors that can impact the perception of fairness in the contest between humans and machines
Key facts. Cited by 4 papers in the map (data through 14 Oct 2026). First posted on arXiv 17 Mar 2019.
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Citing papers per year: 2021: 2; 2022: 1; 2023: 0; 2024: 0; 2025: 0; 2026: 1.
4 papers.
- 2022Making Intelligence: Ethical Values in IQ and ML Benchmarkscited by 10
- 2021General Board Game Conceptscited by 8
- 2021Scope and Sense of Explainability for AI-Systemscited by 2
- 2026Runtime Action Interference for AI Control of AlphaStar in StarCraft IIcited by 0
- 2026Runtime Action Interference for AI Control of AlphaStar in StarCraft II5 Aug 2026
- 2022Making Intelligence: Ethical Values in IQ and ML Benchmarks1 Sep 2022
- 2021Scope and Sense of Explainability for AI-Systems20 Dec 2021
- 2021General Board Game Concepts2 Jul 2021