A new study published in *Cureus* examines how Evolutionary Game Theory (EGT) could model human-AI interaction, evolution, and co-evolution. The authors note that serious games between humans and AI have "only just begun," and EGT, which models competitive and cooperative strategies of biological entities, could help predict the potential evolutionary equilibrium of the two. Of 13 EGT models considered, the study examined three canonical archetypes: the Hawk-Dove (HD) Game, the Iterated Prisoner’s Dilemma (IPD), and the War of Attrition (WOA). The HD Game predicts balanced mixed-strategy equilibria based on conflict costs; the IPD suggests repeated interaction may lead to cognitive co-evolution; and the WOA suggests resource competition may result in strategic co-evolution, asymmetric equilibria, and conventions on sharing resources. Each model was analyzed from human and AI decision-making perspectives, including psychological, biological, and AI viewpoints. The authors state that AI is being shaped by human input and evolving in response, while neuroplasticity allows the human brain to evolve in response to stimuli. They raise profound ethical and cognitive implications if humans and AI converge, combining human neuroplasticity with an ever-evolving AI. The study concludes that EGT may provide a suitable framework to understand and predict human-AI interaction, but future research should extend beyond EGT to explore additional frameworks, empirical validation methods, and interdisciplinary perspectives. An illustrative computational simulation is also provided