The global policy landscape has coalesced around “Trustworthy AI” as a normative goal for AI governance and development. However, despite its ubiquity, there is no widespread agreement on the definition of the term. Based on a convened discourse of interdisciplinary institute leaders at The George Washington University, this paper argues that the failure to define “Trustworthy AI” is not a technical gap, but a consequence of different epistemologies associated with different worldviews. We argue that “trust” is not a singular property, but a “boundary object” (Star and Griesemer in Soc Stud Sci 19:387–420, 1989) interpreted through four different worldviews: the Technocratic (trust as metrology), the Relational (trust as agency and social contract), the Critical (trust vs. power), and the Pragmatic (trust as pedestrian verification). This paper delineates these paradigms, explores the friction between them, and argues that a rigorous framework for trustworthy AI requires a pluralistic approach that acknowledges these inherent contradictions.
Read the full article in AI & Ethics.