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Cited by 365Ethics and Social Impacts of AIDigitalization, Law, and RegulationE-Government and Public Services

Trustworthy artificial intelligence and the European Union AI act: On the conflation of trustworthiness and acceptability of risk

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Laux, Johann, Wachter, Sandra, Mittelstadt, Brent·2024·Regulation & Governance
DOI 10.1111/rego.12512PMC PMC10903109
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Abstract

In its AI Act, the European Union chose to understand trustworthiness of AI in terms of the acceptability of its risks. Based on a narrative systematic literature review on institutional trust and AI in the public sector, this article argues that the EU adopted a simplistic conceptualization of trust and is overselling its regulatory ambition. The paper begins by reconstructing the conflation of “trustworthiness” with “acceptability” in the AI Act. It continues by developing a prescriptive set of variables for reviewing trust research in the context of AI. The paper then uses those variables for a narrative review of prior research on trust and trustworthiness in AI in the public sector. Finally, it relates the findings of the review to the EU's AI policy. Its prospects to successfully engineer citizen's trust are uncertain. There remains a threat of misalignment between levels of actual trust and the trustworthiness of applied AI.

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  • The European AI Act is predicted to become the global standard for AI regulation by unifying within a single framework the concept of risk acceptability and the trustworthiness of AI systems by their users.

    “The European AI Act is predicted to become the global standard for AI regulation 13 by unifying within a single framework the concept of risk acceptability and the trustworthiness of AI systems by their users [15].”

    From Connecting the dots in trustworthy Artificial Intelligence: From AI principles, ethics, and key requirements to responsible AI systems and regulation (2023) · cites this paper as [15]

    The section “The EU AI act: Trustworthiness as acceptability of risks” says the proposed Act conflates trustworthiness with acceptable risk. But the Introduction and Conclusion say risk acceptability is assessed chiefly by experts or developers, and distinguish those judgments from users’ or citizens’ trust. The global-standard prediction is attached to a different citation (13), not this source ([15]). (LLM, conf=0.86)

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  • [15] argues on four acute challenges facing the European Commission's attempt to signal the trustworthiness of AI through its proposed regulation: the uncertainty about the antecedents of perceived trust in public institutions that utilize AI; the threat of misalignment between trustworthiness and degrees of trust; concealed behavioral factors behind the acceptability of risks; and the need for Im

    “Focused on trust and trustworthiness in AI in the public sector, [15] argues on the four acute challenges facing the European Commission's attempt to signal the trustworthiness of AI through its proposed regulation: the uncertainty about the antecedents of perceived trust in public institutions that utilize AI; the threat of misalignment between trustworthiness and degrees of trust; concealed”

    From Connecting the dots in trustworthy Artificial Intelligence: From AI principles, ethics, and key requirements to responsible AI systems and regulation (2023) · cites this paper as [15]

  • Conflating trust and trustworthiness with the acceptability of risks blurs the distinction between acceptability judgments made by domain experts and the trustworthiness of AI systems implemented in society.

    “Indeed, conflating trust and trustworthiness with the acceptability of risks blurs the distinction between acceptability judgments made by domain experts and the trustworthiness of AI systems implemented in society [15].”

    From Connecting the dots in trustworthy Artificial Intelligence: From AI principles, ethics, and key requirements to responsible AI systems and regulation (2023) · cites this paper as [15]

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Research works printed but not linked: 90

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Authors
Laux, J., Wachter, S., & Mittelstadt, B.
Affiliations
University of Oxford (GB)
Corresponding author
Laux, Johann
ORCID
Venue
Regulation & Governance
Publisher
Wiley
Published
2023-02-06
Volume
18
Issue
1
Pages
3-32
ISSN
  • 1748-5983 (ISSN-L)
  • 1748-5991
DOI
10.1111/rego.12512
PMC
PMC10903109
OpenAlex
W4319299406
Cited by
365
References
113
Citations by year
2026: 135 · 2025: 144 · 2024: 76 · 2023: 9 · 2022: 1
FWCI
90.88
Type
journal article
Language
en
Open access
Licence
Locations
  • Regulation & Governance (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
Funders
  • Alfred P. Sloan Foundation (G‐2021‐16779)
  • British Academy (PF22\220076, PF2\180114, PF\170151)
  • Miami Foundation
  • Wellcome Trust (223765/Z/21/Z)
Topics
  • Social Sciences › Safety Research › Ethics and Social Impacts of AI
  • Social Sciences › Law › Digitalization, Law, and Regulation
  • Social Sciences › Political Science and International Relations › E-Government and Public Services
Keywords
trustworthy AI, EU AI Act, trustworthiness, risk acceptability, institutional trust, public sector AI, AI regulation, public confidence, AI policy

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