POLICY · REGULATION · #2637
Conformance as a Distribution: delegation contracts and evaluation mechanisms for use-based AI regulation (arXiv:2610.33112v1)
This arXiv preprint formalizes "conformance as a distribution" for use-based AI regulation and analyzes delegation contracts among a deployer, auditor, and enforcement point. It proposes mechanisms and theoretical propositions addressing truthful declared context mixtures, unbiased commit-reveal audits, certification error budgets (including halving budgets and α-investing), per-subgroup audit scaling, and limitations of failure-only incident metrics, and tests each claim in five preregistered synthetic studies; no language models or production systems are evaluated. The paper frames conformance-as-a-rate as an alternative to static conformity assessment such as in the EU AI Act.
KEY POINTS
- This arXiv preprint formalizes "conformance as a distribution" for use-based AI regulation and analyzes delegation contracts among a deployer, auditor, and enforcement point.
- It proposes mechanisms and theoretical propositions addressing truthful declared context mixtures, unbiased commit-reveal audits, certification error budgets (including halving budgets and α-investing), per-subgroup audit scaling, and limitations of failure-only incident metrics, and tests each claim in five preregistered synthetic studies; no language models or production systems are evaluated.
- The paper frames conformance-as-a-rate as an alternative to static conformity assessment such as in the EU AI Act.
WHY IT MATTERS
The paper proposes concrete, theoretically-grounded mechanisms for allocating evaluation authority and bounding deployment failure rates under use-based regulation, which is directly relevant to designing audits and conformity regimes (e.g., EU AI Act).