person
Inioluwa Deborah Raji
A research and interview route into who audits AI systems and what an audit can establish.
Inioluwa Deborah Raji coauthored Actionable Auditing with Joy Buolamwini.[1]
The participant’s perspective
In RE•WORK’s February 3, 2021 published Q&A, Raji describes noticing missing representation in training data during an internship and reaching out to Buolamwini. She discusses internal and external auditors’ different circumstances, and says facial recognition can be harmful “even when it does work”. This is her account and perspective, not an independently reconstructed workplace incident.[2]
A reading route
Start with the original audit, then the follow-up’s methods and limitations. Compare the arrest case to ask whether a benchmark answers the question an institution needs answered. Social Alignment asks whose interests determine acceptable use; Safety Case asks how evidence supports a deployment claim.
The interview is preserved as the publisher’s written Q&A. No full recording or current institutional-role claim is inferred from it.
Sources
- Actionable Auditing: Investigating the Impact of Publicly Naming Biased Performance Results of Commercial AI Products · Source record ref-actionable-auditing-2019 · Back to claim ↑1
- Interview with Inioluwa Deborah Raji, Forbes Tech 30 Under 30 Pick · Source record ref-raji-interview-2021 · Back to claim ↑1
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Last updated 2026-10-12