FAccT Conference's Deep Impact on AI Governance: From Algorithm Audits to Real-World Policy
rajiinio · x · 2026-07-23
In a discussion with researchers, the author highlights the tangible impact that FAccT (Fairness, Accountability, and Transparency) has had on AI policy and governance over the years.
The author points to several widely referenced real-world cases where research from the conference directly informed policy and regulation. Examples include the controversies surrounding child welfare algorithms in Allegheny County, the DoJ settlement over Facebook's ad discrimination, and the enforcement of NYC Local Law 144 (which mandates bias audits for automated employment decision tools). The author themselves has also been involved in seminal work such as Gender Shades, Model Cards, and third-party evaluations.
Related event: Scholars Debate FAccT's Substantial Impact on AI Policy(13 posts)→
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