The HAIP Reporting Framework: Its Value in Global AI Governance and Recommendations for the Future
The Hiroshima AI Process Reporting Framework represents a multilateral effort to promote transparency and accountability in the development of advanced AI systems. Launched in February 2025 as part of the Group of Seven (G7) Hiroshima AI Process (HAIP), the framework provides a mechanism for organizations developing advanced AI systems to voluntarily report on their risk mitigation practices, aiming to facilitate cross-organizational comparability and to identify and disseminate good practices. The multilateral agreement on the HAIP framework and the wide participation by companies suggest that it can be an important advance in international AI governance. It can propel improvements in risk mitigation by providing AI companies with insights into each other’s governance practices, allowing enterprise customers to compare AI offerings, and benchmarking best practices for researchers and eventually policymakers.
Joint research from CDT’s AI Governance Lab and the Brookings Institution, this report examines the framework’s first reporting cycle through analysis of submissions, stakeholder surveys, and targeted interviews. The analysis reveals that the framework’s flexibility enables diverse participation and provides internal benefits to submitters. At the same time, its current format limits comparability across submissions and creates challenges around clarity of purpose. We also find that while HAIP’s positioning in international governance efforts makes it a uniquely appealing forum to build consensus around risk mitigation practices, the potential impact of the framework can be enhanced by increasing awareness, certainty about the target audience for reports, and strengthening information verification. Based on these findings, we provide recommendations for enhancing future iterations of the framework.
CDT Comment Welcomes NIST Effort to Develop Zero Draft
Drawing on CDT’s previous comments on this NIST effort and our prior research on documentation, our submission welcomes NIST’s effort to develop the zero draft, which provides a much-needed step toward more standardized, high-quality guidance on how developers of AI system components should document key properties and potential sources of AI risk. This guidance will be a valuable resource for organizations to improve interoperability, build more performant AI products, and more effectively identify and mitigate AI risks.
Coalition Urges Senate Not to Let Companies Waive Financial Regulations for AI
CDT joined AI Now Institute, American Civil Liberties Union, and several organizations dedicated to tech policy, consumer protection, and civil rights in a letter to Senate leadership and the Senate Banking, Housing, and Urban Affairs Committee opposing the “AI Innovation Labs” language in Sec. 10509 of the CLARITY Act.
As concern about risks and harms related to AI systems continue to grow, a growing chorus of policymakers, industry leaders, and advocates have called for independent AI assessments. This explainer provides an overview of recent proposals for third-party assessment in the United States, including state and federal legislation, executive actions, and industry proposals.
Having third parties assess AI systems might seem like common sense, but crafting effective policies toward this goal can be devilishly tricky. A poorly-constructed ecosystem for third-party assessment could easily fail to consider the most consequential mechanisms of risk, neglect the AI harms that most impact people, or do more to protect AI companies than people.
