Coordinated incentives in AI-generated misinformation governance

2026-08-07

AI Summary

This study addresses the escalating spread of misinformation fueled by the proliferation of AI-generated content, which undermines information credibility and societal trust. To analyze this challenge, the authors construct an evolutionary game-theoretic model involving three key stakeholders—government regulators, AI firms, and users—and incorporate heterogeneous reward-punishment mechanisms. By employing replicator dynamics, they examine strategic interactions among these agents. The findings reveal that neither regulatory oversight nor market-based incentives alone suffice to curb misinformation effectively. Instead, an evolutionarily stable equilibrium favoring truthful content production emerges only when coordinated incentives align such that regulatory intensity, reputational penalties for noncompliance, and user-level rewards jointly exceed critical thresholds. This work thus provides a theoretical foundation and identifies essential parameter conditions for the collaborative governance of AI-driven misinformation.

Abstract

With the rapid diffusion of AI-generated content, AI-driven misinformation is becoming increasingly pervasive and difficult to govern, undermining information credibility and social trust. This study models the strategic interdependence among a government regulator, an AI enterprise, and users through a three-party evolutionary game that incorporates heterogeneous rewards and punishments. From the resulting replicator equations, we characterize the evolutionary stability of competing governance and production strategies. The analysis indicates that neither unilateral regulation nor market incentives alone can effectively curb misinformation. Instead, an evolutionarily stable regime of real-information production arises only when regulatory rewards and punishment intensity, enterprise reputation loss, and user adoption incentives collectively surpass critical thresholds. The findings highlight the need for coordinated and adaptive policy mixes that align regulatory instruments with enterprise behavior and user uptake while managing governance costs.

Problem

• AI-generated misinformation
• governance
• strategic interdependence
• information credibility
• social trust

Innovation

• evolutionary game theory
• AI-generated misinformation
• coordinated incentives
• heterogeneous rewards and punishments
• information governance