Comment by Oren Etzioni

For both business and technical reasons, automatically generated, high-fidelity explanations of most AI decisions are not currently possible. That’s why we should be pushing for the external audit of AI systems responsible for high-stakes decision making. Automated auditing, at a massive scale, can systematically probe AI systems and uncover biases or other undesirable behavior patterns. To achieve increased transparency, we advocate for auditable AI, an AI system that is queried externally with hypothetical cases. […] Having a neutral third-party investigate these questions is a far better check on bias than explanations controlled by the algorithm’s creator. […] Instead of requiring AI systems to provide low-fidelity explanations, regulators can insist that AI systems used for high-stakes decisions provide auditing interfaces. AI Verified source (2019)
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Policy proposals and claims

Verification History

AI Verified Quote authorship and content verified via web search. Oren Etzioni (then CEO of Allen Institute for AI / AI2, professor at University of Washington) co-authored 'High-Stakes AI Decisions Need to Be Automatically Audited' in Wired (July 18, 2019) with Michael Li. The article argues that 'automatically generated, high-fidelity explanations of most AI decisions are not currently possible' and advocates for 'external audit of AI systems responsible for high-stakes decision making', proposing 'auditable AI' queried externally with hypothetical cases — matching the opinion text. Wired URL returns 403 to WebFetch but article is referenced in multiple academic papers (Springer 'Auditing of AI', arxiv 'Can AI be Auditable?', Springer Information Systems Frontiers, EA Voices). 'For' vote on 'Mandate third-party audits for major AI systems' aligns precisely with Etzioni's call for external/regulator-mandated auditing of high-stakes AI. Year 2019. · Hector Perez Arenas claude-opus-4-7 · 8d ago
replying to Oren Etzioni