Serious Games: Human-AI Interaction, Evolution, and Co-evolution

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 the 13 EGT models considered, three were examined: the Hawk-Dove (HD) Game, the Iterated Prisoner's Dilemma (IPD), and the War of Attrition (WOA). The rationale for this selection is that these three models represent canonical archetypes of EGT and are relevant to basic human-AI interaction. The HD Game predicts balanced mixed-strategy equilibria based on the costs of conflict. The IPD suggests that repeated interaction may lead to cognitive co-evolution. The WOA suggests that competition for resources may result in strategic co-evolution, asymmetric equilibria, and conventions on sharing resources. Each model was examined from the perspective of human and AI decision-making, from psychological and biological perspectives, and from an AI viewpoint. AI is being shaped by human input and is evolving in response to it. So too, neuroplasticity allows the human brain to evolve in response to stimuli. If humans and AI converge in the future, what might be the result of human neuroplasticity combined with an ever-evolving AI? There are profound ethical and cognitive implications. EGT may provide a suitable framework to understand and predict human-AI interaction, evolution, and co-evolution. However, future research should extend beyond EGT and explore additional frameworks, empirical validation methods, and interdisciplinary perspectives. In the spirit of further exploration, an illustrative computational simulation is provided.