‘Opacity’ and ‘Trust’: From Concepts and Measurements to Public Policy

This paper provides four insights relating to policy-making, focusing on the complex relationship between the abstract concept of trust—with its numerous empirical expressions—and the concept of opacity in AI technologies. First, we set the ground by discussing the nature of trust as it evolves from interpersonal to technological realms (§ 2), examining the plethora of measurement methods and objects that reflect the concept’s rich diversity. We then investigate the concept of opacity in AI systems (§ 3), challenging the conventional wisdom that less opacity invariably leads to greater trust, and illustrate this relationship’s nuanced and context-dependent reality. The conclusion (§ 4) bridges these theoretical discussions with pragmatic policy-making considerations, crystallizing abstract ideas into actionable directives. We present four key insights for policy-makers: First, policies must mediate between the abstract concept of trust and the concrete outcomes of AI interactions. Second, they should mirror societal values. Third, policy-making must be adaptive, evolving alongside technological advancements to effectively address both technical and policy issues relating to trust and opacity. Lastly, we anticipate that academic discourse will inform future policies, suggesting the creation of a standardized trust index for AI systems, transparency guidelines based on opacity levels, and explainability protocols for high-stakes applications. These insights aim to ensure that AI-based technologies are governed in a manner that upholds societal values and fosters the common good.