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<p>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.</p>

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The epistemologies of trust: conflicting worldviews in the “Trustworthy AI” discourse

  • 期刊论文

  • 发表日期：

    2026年4月22日

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  • David A. Broniatowski,
  • Alexa Alice Joubin,
  • Susan Ariel Aaronson,
  • Y. Tony Yang,
  • Neal Sikka,
  • Lorien C. Abroms,
  • Aya Zirikly,
  • Zoe Szajnfarber

摘要

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.