The OECD.AI Policy Navigator

Published by the National Institute of Standards and Technology (NIST) in March 2025, NIST AI 100-2e2025 provides a taxonomy of concepts and terminology in the field of adversarial machine learning (AML). It covers key types of ML methods, life cycle stages of attack, and attacker goals, capabilities, and knowledge, alongside mitigation methods, aiming to establish a common language to inform standards and practice guides for assessing and managing the security of AI systems.

The Stargate Project is a US-based AI infrastructure initiative established by OpenAI, SoftBank, and Oracle, with an investment commitment of $500 billion over four years. Launched in January 2025, it aims to build large-scale AI data centres across the United States, beginning in Texas. The initiative targets nearly 7 gigawatts of planned capacity and over 25,000 on-site jobs.

The Action Plan sets forth policy goals for near-term execution by the Federal government and articulates policy recommendations in line with the President’s vision for US leadership in AI. It is articulated around three main pillars: innovation, infrastructure, and international diplomacy and security.

The National Artificial Intelligence Advisory Committee Law Enforcement Subcommittee (NAIAC-LE), authorised under Section 5104 of the National Artificial Intelligence Initiative Act of 2020, held an open meeting on 19 January 2024. The primary purpose of the meeting was for Subcommittee Members to report working group findings, identify actionable recommendations, and discuss updates on goals and deliverables related to the development of artificial intelligence in law enforcement.

Developing Strategies to Increase Capacity in AI Education (September 2025) presents findings from the NSF LEVEL UP AI project, based on 32 virtual roundtables with 202 experts. Conducted in 2024, it aims to improve AI education in US undergraduate institutions by analysing challenges such as infrastructure, skills gaps and curricula, and proposing strategies including faculty development, interdisciplinary approaches and expanded access.

The U.S. National Science Foundation-led National Artificial Intelligence Research Resource (NAIRR) is a scalable national infrastructure that provides the research and education communities with access to the critical computing, software, data, models, educational resources and expertise needed to advance AI innovation for the U.S.

The NAIRR pilot brings together computational, data, software, model, training and user support resources to demonstrate and investigate all major elements of the NAIRR vision first laid out by the NAIRR Task Force.

This relevant, user-friendly resource was developed through engagement with educators, community members and technology leaders and is shaped by the real-world challenges faced by schools and districts of all sizes. Whether an education leader is at the beginning stages of AI adoption or is already exploring its applications, this toolkit offers critical guidance to support the intentional use of AI in education

The PCAST Generative AI Working Group advises the President on the safe and fair use of generative AI technology. It helps identify risks and opportunities to guide responsible development and deployment. This initiative benefits the public by promoting AI that is trustworthy and used fairly.