Legal definitions are crucial to the drafting of technology legislation and regulation and are highly-referenced and recycled throughout the lawmaking process. They then cascade from laws to enforcement, leading to unintended consequences if definitions are not carefully scoped. Terms relating to emerging technologies like artificial intelligence (AI) are especially difficult to define due to the fast-changing technological frontier and the broad application of these tools.
For this reason, Congress has historically granted power to executive agencies to interpret definitions and update terms in accordance with new information and best practices. This all changed after the 2024 Loper Bright decision which overturned the “Chevron Doctrine” and significantly weakened agency authority. Now, policy leaders have a new responsibility thrust upon them to get these highly consequential definitions right in legislative text—since they can no longer confer this responsibility to executive agencies—and they urgently need support.
Aspen Digital brought together legal scholars, policy advocates, and leading thinkers in technology to craft a collection of influential definitions of AI, with legal and technological rationales for why a policymaker should choose one potential definition over another in context.
This resource is for policymakers, legislative staff, regulators, advocates, and legal practitioners who need to work with AI definitions as operative legal tools rather than technical descriptions. It assumes there is no single “correct” definition of AI. Instead, it treats definitions as context-dependent choices that can have outsized impact on scope, enforcement, institutional authority, and other downstream legal consequences.
This handbook offers an accessible, easy to use entry point for grappling with the question of how to define AI in a legal context. It is intended to be practical, comparative, and usable by readers who are actively engaging with legislative or regulatory text, whether they are drafting new provisions, interpreting existing ones, or trying to understand how a proposed definition will operate once it leaves the page.
This handbook does not attempt to catalogue every definition of artificial intelligence that exists in statute, regulation, or policy guidance. That would be neither feasible nor especially illuminating. Instead, it offers structured, independent expert analysis of the most influential definitions using a comparative approach. Each entry is intentionally scoped to highlight how a definition works, what it captures or excludes, and what tradeoffs it embeds.
The goal is not depth for its own sake, but clarity: to help readers see how small changes in language—sometimes only a few words—can substantially alter legal interpretation, regulatory reach, and institutional responsibility.
