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.

Report discussing currently available machine learning (ML) medical diagnostic technologies for five selected diseases, emerging ML medical diagnostic technologies, challenges affecting the development and adoption of ML technologies for medical diagnosis, and policy options to help address challenges in the use of artificial intelligence (AI) technologies in health care (Part One). Part Two presents a framework for evaluating and promoting provider adoption of new AI-assisted diagnostic decision support tools (AI-DDS), centered on four integrated domains: 1) Reason to Use, 2) Means to Use, 3) Methods to Use, and 4) Desire to Use.

Document summarizing deepfake technology and highlighting opportunities, challenges, and policy questions related to the development of this technology.