Trust or Check? Understanding the (Evolutionary) Dynamics of User Trust in AI Systems
As the capabilities and adoption of Artificial Intelligence (AI) systems grow, trust in these AI systems is an increasingly urgent concern. Much research has focused on models of AI governance and has primarily examined incentives for safe development and effective regulation. Hence they typically represented users trust as a one-shot adoption choice rather than as a dynamic, evolving process shaped by repeated interactions. We instead model trust as the dynamic choice of reduced monitoring in a repeated, asymmetric interaction between users and AI developers, where checking developers' behaviour is costly. Using evolutionary game theory, we study how users' strategies of trust and develo...
| Authors | Adeela Bashir, Zhao Song, Ndidi Bianca Ogbo et al. |
|---|---|
| Primary category | cs.AI |
| Published | 25 March 2026 |
| Last updated at source | 3 August 2026 |
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