Legal and regulatory systems were built to govern technologies that changed over years or decades. Artificial intelligence, biotechnology, and quantum computing are moving on a shorter timescale, and the resulting gap between the speed of innovation and the speed of legal doctrine is itself a research problem worth studying directly.
Law moving at the speed of statute, technology moving faster
Regulatory systems are deliberately paced: rulemaking involves notice-and-comment periods, legislative debate, and judicial review because binding public rules should not change on a whim. That deliberateness is a feature when the subject matter is stable. It becomes a structural mismatch when a large language model’s capabilities, a gene-editing technique’s precision, or a quantum algorithm’s implications can shift meaningfully within one rulemaking cycle.
Existing legal categories were built around assumptions that fast-moving technology strains. Liability doctrine assumes an identifiable human decision-maker whose negligence or intent can be evaluated; autonomous or emergent systems complicate that assumption without necessarily invalidating the underlying concept. Export-control and biosecurity frameworks assume dangerous capability is tied to specialized equipment; software and accessible laboratory techniques weaken that assumption. None of this means existing law is irrelevant—it means adapting it is a genuinely open question.
Existing frameworks as building blocks
Administrative law, products liability, intellectual property doctrine, and sector-specific regimes each carry decades of reasoning about uncertainty, responsibility, and the balance between innovation and public risk. The research task is identifying which parts transfer cleanly, which require deliberate extension, and which genuinely break down.
Doing that analysis rigorously requires working directly with statutes, regulations, case law, and legislative history at a scale that makes systematic comparison possible. Computational methods can surface patterns across regulatory documents or judicial opinions without replacing the legal judgment required to interpret what those patterns mean.
How INSTAR approaches science and technology law
INSTAR’s law research examines how regulatory systems can keep pace with artificial intelligence, gene editing, autonomous systems, and quantum technologies. This work combines legal scholarship with machine-learning-assisted review of regulatory corpora, while keeping conclusions grounded in openly accessible legal materials such as statutes, regulations, case law, and legislative records.
Because the program sits at the intersection of law and technical work in AI, life sciences, and quantum computing, it is naturally interdisciplinary: legal scholars, computer scientists, and domain researchers working through the same governance questions from different angles.