This report describes an accountability framework for artificial intelligence (AI). The framework is organized around four complementary principles and describes key practices for federal agencies and other entities that are considering and implementing AI systems. Each practice includes a set of questions for entities, auditors, and third-party assessors to consider, along with audit procedures and types of evidence for auditors and third-party assessors to collect.

This report discusses a proposed framework for modifications to AI/ML-based SaMD that is based on the internally harmonized International Medical Device Regulators Forum risk categorization principles, FDA's benfit-risk framework, risk management principles in the software modifications guidance, and the organization-based TPLC approach as envisioned in the Digital health Software Precertification Program. The authors ask for public feedback about the questions posed in the report.