Toward Trustworthy AI Development: Mechanisms for Supporting Verifiable Claims

TL;DR

This paper discusses mechanisms to enhance the verifiability of claims about AI systems, aiming to build trust through accountability and scrutiny of safety, security, fairness, and privacy aspects.

Contribution

It analyzes ten mechanisms across institutions, software, and hardware to improve verifiability of AI claims and offers recommendations for their implementation and enhancement.

Findings

Identifies ten mechanisms for verifiable AI claims

Provides recommendations for implementing these mechanisms

Emphasizes importance of evidence in safety, security, fairness, privacy

Abstract

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.