The Evocative Audit: What Metrics...
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The Evocative Audit: What Metrics Cannot Carry in AI Bias | Deep Dive
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The Other AI: Audio Briefings on Augmented Intelligence and ... by Basil C. Puglisi

Episode notes

What happens when a structured multi-AI review process spends months scanning a book manuscript for accuracy and still misses a foundational concept? Three sentences from Dr. Timnit Gebru on LinkedIn caught what eleven platforms could not.

This episode is a deep dive into Dr. Joy Buolamwini's 2022 MIT PhD thesis, "Facing the Coded Gaze with Evocative Audits and Algorithmic Audits," and the concept at its center: the evocative audit. Buolamwini argues that the standard approach to AI accountability, testing systems and publishing error rates, produces evidence that moves institutions but fails to move people. The evocative audit is her formal answer to that gap. It combines human experience with documented evidence using a mechanism she calls the counter-demo to make algorithmic harm visible in ways that numbers alone cannot.

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Keywords
AI governanceevocative auditalgorithmic auditJoy BuolamwiniTimnit GebruAI biasGender Shadesfacial recognitionBlack feminist epistemologyUnmasking AI