  With the recent wave of progress in artificial intelligence (AI) has come a
growing awareness of the large-scale impacts of AI systems, and recognition
that existing regulations and norms in industry and academia are insufficient
to ensure responsible AI development. In order for AI developers to earn trust
from system users, customers, civil society, governments, and other
stakeholders that they are building AI responsibly, they will need to make
verifiable claims to which they can be held accountable. Those outside of a
given organization also need effective means of scrutinizing such claims. This
report suggests various steps that different stakeholders can take to improve
the verifiability of claims made about AI systems and their associated
development processes, with a focus on providing evidence about the safety,
security, fairness, and privacy protection of AI systems. We analyze ten
mechanisms for this purpose--spanning institutions, software, and hardware--and
make recommendations aimed at implementing, exploring, or improving those
mechanisms.
