When AI Governance Has to Prove Itself (Stanford CodeX)
Colorado's proposed AI rules turn broad principles into hard evidence. You have to prove what your system did.
Eran Kahana's second CodeX piece runs Colorado's proposed AI rules through one simple test. Can the organization actually prove what its system did.
His read turns broad principles into hard evidentiary demands. Reproducibility means rebuilding the full system configuration at decision time, the model version alone won't cut it. Independent review means a real firewall around the reviewer. Feasibility turns into an evidence claim, down to documenting the approaches you rejected.
Product counsel will feel this one. None of it bolts on at launch review. Each named capability is an engineering requirement wearing a compliance label, and that's the argument for designing governance in from the start.