Regulating Uncertainty: The Importance of Trust and Affect in the Regulation of AI in The Netherlands

• 成果类型: Article; Early Access
• 署名作者: Versluis, Esther; Spendzharova, Aneta; Feltkamp, Odile
• 署名单位: Maastricht University
• 刊物名称: REGULATION & GOVERNANCE
• ISSN/ISSBN: 1748-5983
• DOI: 10.1111/rego.70070
• 发表日期: 2025
• 关键词: technology; heuristics; risks

摘要

The rapid adoption of artificial intelligence (AI) introduces significant uncertainty regarding its future applications and potential risks. What is the preferred regulatory approach when confronted with such uncertainty? To cope with uncertainty, people often screen information in a biased way, consistent with their own prior beliefs and predispositions. Heuristics such as trust and affect are likely to influence how new (scientific) information is judged, in turn influencing the preferred regulatory approach. This article explores the complex interplay between trust, affect, and regulatory preferences in the context of AI governance. Drawing on an exploratory survey and interviews with AI regulators and professionals in the Netherlands, the study finds relatively low trust in AI providers and users, alongside a preference for flexible, adaptive regulation that is strictly enforced by the public authorities. By shedding light on the role of trust and affect in the emerging regulation of AI, this article contributes to understanding how such heuristics influence the preferred regulatory approach.