Charlie Bullock is a Senior Research Fellow at the Institute for Law & AI (ILAI, also styled LawAI), where his research focuses on the intersection of AI governance and U.S. law (Source: https://www.lawfaremedia.org/contributors/cbullock). He sits on the organization's U.S. Law and Policy team, advises state and federal policymakers on AI governance topics, and publishes research on legal questions with practical relevance to U.S. AI policy, with a particular focus on U.S. administrative law (Source: https://law-ai.org/team/charlie-bullock/). He is a contributor to Lawfare on AI legal and policy questions.
Background
Bullock received his J.D. from Yale Law School in 2020, where he was an editor of the Yale Journal on Regulation (Source: https://www.lawfaremedia.org/contributors/cbullock). His listed areas of expertise at ILAI are U.S. law and policy and constitutional and administrative law (Source: https://law-ai.org/team/charlie-bullock/). He is also affiliated with Harvard University's Berkman Klein Center for Internet & Society in connection with his work on LawAI's U.S. Law and Policy team (Source: https://cyber.harvard.edu/people/charlie-bullock).
Research and positions
Bullock works with ILAI Director Christoph Winter on the legal design of advanced-AI governance. His publications include:
- Radical Optionality (2026, with Christoph Winter) — introduces the Radical Optionality approach to governing Transformative AI (TAI) under deep uncertainty; the source summary is at Radical Optionality: Governing Transformative AI Under Uncertainty.
- The Governance Misspecification Problem (2024, with Christoph Winter) — on the difficulty of specifying governance objectives for systems whose behavior and impact are hard to predict in advance.
- Legal Considerations for Defining "Frontier Model" (2024, with Suzanne Van Arsdale, Mackenzie Arnold, Cullen O'Keefe & Christoph Winter) — an analysis of how the legal category "frontier model" can be defined for regulatory purposes, a recurring problem for compute-threshold and frontier-model rules.
His work centers on the legal craft of AI rules: how statutory and regulatory definitions, and the institutions that apply them, can be written so they remain workable as AI capability changes. It is the U.S.-law-facing complement to Winter's broader governance-under-uncertainty program.
The Institute for Law & AI states that Bullock's current research includes projects on whistleblower protections, preemption, information-gathering authorities, emergency powers, and regulatory updating (Source: https://www.lawfaremedia.org/contributors/cbullock). The Berkman Klein Center describes his recent research as examining federal preemption of state AI laws, federal and state AI whistleblower protection legislation, and the likely consequences of the end of Chevron deference for the future of AI regulation (Source: https://cyber.harvard.edu/people/charlie-bullock).
AI whistleblower protections
Bullock, with ILAI Director of U.S. Policy Mackenzie Arnold, has written in support of statutory whistleblower protections for AI-industry employees. In a July 2025 Lawfare piece, the two analyzed the AI Whistleblower Protection Act (AI WPA), a bipartisan bill introduced by Sen. Chuck Grassley with companion legislation from Reps. Ted Lieu and Jay Obernolte, and argued that the bill is minimally burdensome because it imposes no affirmative obligations on companies and requires only that they refrain from retaliating against employees who lawfully disclose information about wrongdoing (Source: https://law-ai.org/protecting-ai-whistleblowers/). They argued that the AI WPA fills a gap in existing law by protecting disclosures about "substantial and specific" dangers to public safety, public health, or national security even where no law violation can be identified, in contrast to California's state whistleblower statute, which protects only disclosures about law violations, and that the bill's bar on contractual waiver of whistleblower rights addresses the kind of broad nondisclosure agreements that drew attention during the 2024 controversy over OpenAI's exit paperwork (Source: https://law-ai.org/protecting-ai-whistleblowers/).
Federal preemption of state AI laws
Bullock has written on proposals for federal preemption of state AI laws and the exceptions for "generally applicable" laws that such proposals often contain. In a December 2025 ILAI commentary, he argued that there is little agreement among experts about what "generally applicable" means in the AI-preemption context, that existing case law does not clearly resolve the question, and that the term is likely to be extensively litigated if preemption legislation with such an exception is enacted (Source: https://law-ai.org/ai-preemption-and-generally-applicable-laws/). He noted that a law such as California's Transparency in Frontier Artificial Intelligence Act (SB 53) would likely not be considered "generally applicable" because it imposes requirements specifically on AI companies, while laws that do not mention AI but were prompted by it, such as Tennessee's ELVIS Act, present harder cases (Source: https://law-ai.org/ai-preemption-and-generally-applicable-laws/).
Relationships
- affiliated-with: Institute for Law & AI (Senior Research Fellow, U.S. Law and Policy team)
- co-author-with: Christoph Winter
- authored: Radical Optionality: Governing Transformative AI Under Uncertainty
- supports: Radical Optionality, Regulating Under Uncertainty, Transformative AI (TAI)
Sources
- Radical Optionality: Governing Transformative AI Under Uncertainty — Bullock & Winter, Radical Optionality (2026).
- (Source: https://www.lawfaremedia.org/contributors/cbullock) — Lawfare contributor page (role as Senior Research Fellow at the Institute for Law & AI; J.D. Yale Law School 2020; Yale Journal on Regulation editor; current research areas).
- (Source: https://law-ai.org/team/charlie-bullock/) — ILAI team page (U.S. Law and Policy team; areas of expertise; advisory role; education).
- (Source: https://cyber.harvard.edu/people/charlie-bullock) — Berkman Klein Center profile (affiliation; recent research areas, including Chevron deference and AI regulation).
- (Source: https://law-ai.org/protecting-ai-whistleblowers/) — Bullock & Mackenzie Arnold, "Protecting AI Whistleblowers" (July 2025), on the AI Whistleblower Protection Act.
- (Source: https://law-ai.org/ai-preemption-and-generally-applicable-laws/) — Bullock, "AI Preemption and 'Generally Applicable' Laws" (December 2025).