Reciprocal Trust and Distrust in Artificial Intelligence Systems: The Hard Problem of Regulation
This addresses the challenge of AI regulation for policy makers and stakeholders, but it is incremental as it builds on existing discussions about trustworthiness without introducing new empirical data or methods.
The paper tackles the problem of regulating AI systems by proposing that they should be recognized as capable of agency, enabling reciprocal trust or distrust relationships with humans, and it examines the implications for regulators, concluding with key tensions and unresolved dilemmas for future governance.
Policy makers, scientists, and the public are increasingly confronted with thorny questions about the regulation of artificial intelligence (AI) systems. A key common thread concerns whether AI can be trusted and the factors that can make it more trustworthy in front of stakeholders and users. This is indeed crucial, as the trustworthiness of AI systems is fundamental for both democratic governance and for the development and deployment of AI. This article advances the discussion by arguing that AI systems should also be recognized, as least to some extent, as artifacts capable of exercising a form of agency, thereby enabling them to engage in relationships of trust or distrust with humans. It further examines the implications of these reciprocal trust dynamics for regulators tasked with overseeing AI systems. The article concludes by identifying key tensions and unresolved dilemmas that these dynamics pose for the future of AI regulation and governance.