  Several policy options exist, or have been proposed, to further responsible
artificial intelligence (AI) development and deployment. Institutions,
including U.S. government agencies, states, professional societies, and private
and public sector businesses, are well positioned to implement these policies.
However, given limited resources, not all policies can or should be equally
prioritized. We define and review nine suggested policies for furthering
responsible AI, rank each policy on potential use and impact, and recommend
prioritization relative to each institution type. We find that pre-deployment
audits and assessments and post-deployment accountability are likely to have
the highest impact but also the highest barriers to adoption. We recommend that
U.S. government agencies and companies highly prioritize development of
pre-deployment audits and assessments, while the U.S. national legislature
should highly prioritize post-deployment accountability. We suggest that U.S.
government agencies and professional societies should highly prioritize
policies that support responsible AI research and that states should highly
prioritize support of responsible AI education. We propose that companies can
highly prioritize involving community stakeholders in development efforts and
supporting diversity in AI development. We advise lower levels of
prioritization across institutions for AI ethics statements and databases of AI
technologies or incidents. We recognize that no one policy will lead to
responsible AI and instead advocate for strategic policy implementation across
institutions.
