Recommendations for a Global AI Auditing Framework: Summary of Standards and Features

The growing integration of artificial intelligence (AI) into critical sectors of society, from healthcare to education, has the potential to support widespread social transformation and progress. However, AI systems also have the power to perpetuate biases, deepen inequalities, and cause environmental harm.

Accurately evaluating the risks and benefits of an AI system requires a careful audit. Current approaches to auditing, however, rarely involve independent auditors, provide sufficient evidence, or account for global impacts.

Policymakers urgently need a comprehensive global framework for AI audits that validates genuine benefits and risks. The IPIE’s Scientific Panel on Global Standards for AI Audits set out to independently establish global, cross-disciplinary scientific consensus on what makes an audit effective and trustworthy. The Panel consisted of 16 experts from computer science, the social sciences, and the humanities, with expertise spanning generative AI systems, algorithmic auditing, indigenous data sovereignty, data journalism, and the relationship between civil society, human rights, and AI.