Engineering and finance as models for AI safety

One writer argues that AI labs rely on “slapdash empirics,” contrasting that approach with system safety and conditional proofs. The writer says AI-assisted supervision during training might make current methods enough to survive, but warns against betting on it. Another argues that finance-style audits and supervision could improve AI governance without making it safe, citing failures of financial controls and the less predictable risks of new AI systems.