arXiv:2505.16388v2 Announce Type: replace Abstract: The serious games between humans and AI have only just begun. Evolutionary Game Theory (EGT) models the competitive and cooperative strategies of biological entities. EGT could help predict the potential evolutionary equilibrium of humans and AI. The objective of this work was to examine EGT models relevant to human-AI interaction, evolution, and co-evolution. Of thirteen EGT models considered, three were examined: the Hawk-Dove Game, Iterated Prisoner's Dilemma, and the War of Attrition. This selection was based on the widespread acceptance
The accelerating advancement and integration of AI necessitate a more formal and predictive understanding of human-AI dynamics beyond immediate technical challenges.
Understanding the potential long-term evolutionary trajectories and equilibrium states of human-AI interaction is crucial for strategic planning and mitigating unforeseen societal impacts.
This research introduces a robust theoretical framework (Evolutionary Game Theory) for analyzing human-AI interactions, shifting the approach from reactive problem-solving to proactive prediction of co-evolutionary outcomes.
- · AI ethicists
- · Policy makers
- · AI developers
- · Sociologists
- · Developers ignoring long-term interaction models
- · Organizations without interdisciplinary planning
The application of EGT to human-AI interaction will lead to new AI safety and alignment research directions.
Governments and international bodies may begin sponsoring research into 'evolutionarily stable strategies' for human-AI coexistence at a systemic level.
This could fundamentally alter AI governance frameworks, moving towards proactive design principles aimed at guiding desired co-evolutionary paths.
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Read at arXiv cs.AI