ACADEMIC SESSION 3
summary
Argues that individual consent often fails because of data externalities (e.g. Myspace-style reidentification), proposes control without consent by banning consent when third‑party harms are likely and using collective rules instead; applies a democracy-by-practice lens to AI governance, using Warren’s three functions to evaluate designs for energy networks coordination; shows NIST-style privacy risk assessments are tunable and non‑replicable so regulators should prefer third‑party or standardized audits; empirical crawl visits 2.8 million pages, finds email exfiltration on ~1,800 EU / 2,950 US sites, 290 test emails returned, ~50 incidental password leaks, and ships a proof‑of‑concept Leak Inspector browser extension that detects and blocks such leaks.
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chapters (10)
- 0:00Introduction
- 2:51Control and consent in data law
- 15:07Q&A
- 20:04AI democratization challenges
- 38:43Q&A
- 41:42Privacy risk limitations
- 53:27Q&A
- 58:31Leaky forms and email tracking
- 1:15:19Q&A
- 1:17:11Summary
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