Using Privacy Infrastructure to Kickstart AI Governance: NIST AI Risk Management Case...
summary
Argues that existing privacy tooling can bootstrap NIST AI RMF adoption by reusing concrete artifacts: a startup leverages a data catalog fed model inputs and enforces a require model registration prior to deployment gate to tame hundreds of models, and teams extend PIAs with AI questions instead of building governance from scratch. Warns against treating the RMF as a checklist, urges prioritizing the Govern core, flags legal blind spots and the lack of standardized measurement benchmarks, and recommends starting small and documenting what exists.
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chapters (9)
- 0:00Introduction
- 1:12Trustworthy AI traits
- 2:35NIST AI risk framework
- 4:21Core functions of NIST AI framework
- 6:06Data governance for AI risk
- 7:28Privacy processes for AI governance
- 8:54AI governance pitfalls
- 10:40AI risk benchmarks challenges
- 11:23Summary
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