[2603.20248] Stability of AI Governance Systems: A Coupled Dynamics Model of Public Trust and Social Disruptions

Computer Science > Computers and Society arXiv:2603.20248 (cs) [Submitted on 10 Mar 2026] Title:Stability of AI Governance Systems: A Coupled Dynamics Model of Public Trust and Social Disruptions Authors:Jiaqi Lai, Hou Liang, Weihong Huang View a PDF of the paper titled Stability of AI Governance Systems: A Coupled Dynamics Model of Public Trust and Social Disruptions, by Jiaqi Lai and 1 other authors View PDF HTML (experimental) Abstract:As artificial intelligence (AI) is increasingly deployed in high-stakes public decision-making (from resource allocation to welfare distribution), public trust in these systems has become a critical determinant of their legitimacy and sustainability. Yet existing AI governance research remains largely qualitative, lacking formal mathematical frameworks to characterize the precise conditions under which public trust collapses. This paper addresses that gap by proposing a rigorous coupled dynamics model that integrates a discrete-time Hawkes process -- capturing the self-exciting generation of AI controversy events such as perceived algorithmic unfairness or accountability failures -- with a Friedkin-Johnsen opinion dynamics model that governs the evolution of institutional trust across social networks. A key innovation is the bidirectional feedback mechanism: declining trust amplifies the intensity of subsequent controversy events, which in turn further erode trust, forming a self-reinforcing collapse loop. We derive closed-form equilibriu...