Public institutions cannot treat agent deployment as a private experiment. Decisions affect people who may not be able to switch providers, inspect a model or appeal an automated outcome.
Procurement therefore needs an evidence trail: purpose, authority, data, testing, human review and remedy. The public sector does not need perfect systems before it experiments. It does need systems whose limits can be explained to the people governed by them.
A bill introduced by U.S. Senators Mark Warner and Brian Schatz would create a federal AI Safety Board, require pre-release access to certain frontier models, and set reporting rules for serious incidents. It is a proposal; none of its requirements are currently in force.
SPIFFE’s Workload Endpoint omits direct client authentication and relies on out-of-band authenticity checks; OAuth tokens represent scoped, time-limited authorization.
NIST offers a voluntary framework for AI risk. California’s DMV points the public to autonomous-vehicle incident reporting and collision records. These are different tools for asking what happened—and what deserves scrutiny.
