Agencies should hold information, whether produced by the government or acquired by the government from third parties, that is likely to have a clear and substantial influence on important public policy or private sector decisions (including those made by consumers) to a high standard of quality, transparency, and compliance.

Best practices include transparently articulating the strengths, weaknesses, intended optimizations or outcomes, bias mitigation, and appropriate uses of the AI application’s results.

Agencies should also be mindful that, for AI applications to produce predictable, reliable, and optimized outcomes, data used to train the AI system must be of sufficient quality for the intended use.

Agencies should be transparent about their evaluations of risk and re evaluate their assumptions and conclusions at appropriate intervals so as to foster accountability.

Agencies should consider in a transparent manner the impacts that AI applications may have on discrimination.

Disclosure and transparency

In addition to improving the rulemaking process, transparency and disclosure can increase public trust and confidence in AI applications.

Agencies should carefully consider the sufficiency of existing or evolving legal, policy, and regulatory environments before contemplating additional measures for disclosure and transparency.

What constitutes appropriate disclosure and transparency is context specific, depending on assessments of potential harms, the magnitude of those harms, the technical state of the art, and the potential benefits of the AI application.

Agencies should coordinate with each other to share experiences and to ensure consistency and predictability of AI related policies that advance American innovation and growth in AI, while appropriately protecting privacy, civil liberties, and American values and allowing for sector and application specific approaches when appropriate.