Reciprocal Trust and Distrust in Artificial Intelligence Systems: The Hard Problem of Regulation
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Abstract (arXiv)
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.
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References · 13
- 2024Alignment faking in large language modelscited by 360
- 2024Frontier Models are Capable of In-context Schemingcited by 287
- 2021Trustworthy AI: From Principles to Practicescited by 207
- 2020Formalizing Trust in Artificial Intelligence: Prerequisites, Causes and Goals of Human Trust in AIcited by 167
- 2023Consciousness in Artificial Intelligence: Insights from the Science of Consciousnesscited by 104
- 2020Trustworthy AIcited by 62
- 2023Managing extreme AI risks amid rapid progresscited by 48
- 2017Human-in-the-loop Artificial Intelligencecited by 40
- 2024Trust in AI: Progress, Challenges, and Future Directionscited by 35
- 2024The Necessity of AI Audit Standards Boardscited by 9
- 2024To Trust or Distrust Trust Measures: Validating Questionnaires for Trust in AIcited by 6
- 2024Inherent Diverse Redundant Safety Mechanisms for AI-based Software Elements in Automotive Applicationscited by 4
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