Reciprocal Trust and Distrust in Artificial Intelligence Systems: The Hard Problem of Regulation

TL;DR

This paper explores the complex dynamics of trust and distrust between humans and AI systems, emphasizing AI's agency and its implications for regulation and governance.

Contribution

It introduces the idea of AI systems as agents capable of reciprocal trust relationships, impacting regulatory approaches and addressing unresolved dilemmas.

Findings

AI systems can be viewed as agents capable of exercising trust and distrust.

Reciprocal trust dynamics influence AI regulation and governance.

Key tensions and dilemmas in regulating AI trustworthiness are identified.

Abstract

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.