The Concept of Accountability in AI Ethics and Governance
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Calls to hold artificial intelligence to account are intensifying. Activists and researchers alike warn of an “accountability gap” or even a “crisis of accountability” in AI. Meanwhile, several prominent scholars maintain that accountability holds the key to governing AI. But usage of the term varies widely in discussions of AI ethics and governance. This chapter begins by disambiguating some different senses and dimensions of accountability, distinguishing it from neighboring concepts, and identifying sources of confusion. It proceeds to explore the idea that AI operates within an accountability gap arising from technical features of AI as well as the social context in which it is deployed. The chapter also evaluates various proposals for closing this gap. It concludes that the role of accountability in AI ethics and governance is vital but also more limited than some suggest. Accountability’s primary job description is to verify compliance with substantive normative principles—once those principles are settled. Theories of accountability cannot ultimately tell us what substantive standards to account for, especially when norms are contested or still emerging. Nonetheless, formal mechanisms of accountability provide a way of diagnosing and discouraging egregious wrongdoing even in the absence of normative agreement. Providing accounts can also be an important first step toward the development of more comprehensive regulatory standards for AI.
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AI agents act autonomously, creating risks of agency drift.
“Like human bureaucrats, AI agents act autonomously, creating risks of agency drift (Lechterman 2022).”
From Holding <scp>AI</scp> Accountable Like Herding Cats: The Contingent Impact on the Legitimacy of Algorithmic Bureaucracy (2026) · cites this paper as Lechterman 2022
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Accountability in Government Use of <scp>AI</scp> : Citizen Concerns and Preferences
Feng, N., & Chandra, Y. (2025) · Public Administration · doi:10.1111/padm.70030 · Cited by 18 · see citing works
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Nabben, K. (2024) · Data & Policy · doi:10.1017/dap.2024.58 · Cited by 11 · see citing works
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- Authors
- Lechterman, T. M.
- Affiliations
- University of Oxford (GB)
- Corresponding author
- Lechterman, Theodore M.
- Venue
- The Oxford Handbook of AI Governance
- Publisher
- Oxford University Press
- Published
- 2022-12-19
- Pages
- 164-182
- OpenAlex
- W4311911485
- Cited by
- 23
- References
- 46
- Citations by year
- 2026: 9 · 2025: 9 · 2024: 4 · 2022: 1
- FWCI
- 12.49
- Type
- book chapter
- Language
- en
- Open access
- green
- philarchive.org
- Locations
- Oxford University Press eBooks (publishedVersion)
- PhilPapers (PhilPapers Foundation) (submittedVersion)
- IE Repository (submittedVersion, cc-by-nc-nd)
- Topics
- Social Sciences › Safety Research › Ethics and Social Impacts of AI
- Social Sciences › Law › Digitalization, Law, and Regulation
- Physical Sciences › Computer Science › Artificial Intelligence › Explainable Artificial Intelligence (XAI)
- Keywords
- accountability, AI ethics, AI governance, accountability gap, normative principles, AI regulation
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