Departments / AI
AI Policy
Governance · Audit · Compute
Governance frameworks for autonomous systems and algorithmic constitutionalism.
From third-party audit standards for public-sector AI to compute as a policy lever, the desk builds verifiable governance for algorithmic systems before benefits and lives depend on them.
Published work
Stakeholder consultation on the Draft Guidelines on the classification of high-risk AI systems under Article 6 of the AI Act
Aadyant Singh Harnwal, Claire Yang, Stanley Zhou, and Anvitha J
Policy comment on the Draft Guidelines on the classification of high-risk AI systems under Article 6 of the AI Act, published by the European Union.
Public Comment on The EU Cybersecurity Act
Claire Yang, Abhinav Kokkula, Ellta T. Abraham, Suryaa Kalyan, Saathvik Valvekar
This paper announces the 2026 revision to the European Union Cybersecurity Act, an update designed to strengthen the EU’s resilience to increasingly sophisticated threats to infrastructure and supply chains. While the original 2019 Act established a foundation through the European Cybersecurity Certification Framework (ECCF) and a permanent mandate for ENISA, the recent landscape has necessitated a more aggressive and comprehensive strategy. Key findings include operational expansion (81.5% budget increase and the creation of the EU Cybersecurity Reserve to assist Member States), supply chain de-risking (including a horizontal framework to identify and phase out “high risk” suppliers), and critical policy gaps (lack of mandatory certification consistency and fragmented coordination between EU institutions and individual member states, which can disproportionately burden SMEs). Ultimately, while the transition away from high-risk suppliers carries short-term costs, the long-term benefits are projected to save EU businesses up to 15.3 billion euros over five years.
Public Comment on HHS Health Sector AI RFI - Request for Information: Accelerating the Adoption and Use of Artificial Intelligence as Part of Clinical Care
Claire Yang, Ellta T. Abraham, Saathvik Valvekar
This paper responds to the U.S. Department of Health and Human Services’ Request for Information on accelerating the adoption of artificial intelligence in clinical care. It identifies key regulatory, workforce, interoperability, and equity barriers to AI implementation and offers policy recommendations to support ethical and effective integration across the U.S. healthcare system.
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