A framework that integrates that capacity into rule-level analytic design and opens the resulting learning agenda to researchers, industry, and the public.
Innovation & Technology
Highlighting the Center's recent work and research on the regulation of emerging technologies
Regulating AI: A Practical Framework for Legislators
November 4, 2026
By Susan Dudley
This Regulatory Insight presents a practical, evidence-based governance framework for policy officials seeking to address artificial intelligence risks without stifling technological innovation and competitiveness.
Beyond the Sandbox: Critical Assessment of Regulatory Sandboxes for AI
September 11, 2026
By Giovana Carneiro
Considering the conditions under which sandboxes deliver, and when alternative tools achieve comparable outcomes with greater reach and accountability.
Evidence-First Regulation: A Procedural Architecture for Governance Under Deep Uncertainty
September 8, 2026
By Steven Wegener
Algorithmic Pricing and Regulation: A Game-Theoretic Analysis of Fairness and Competition Tradeoffs
September 8, 2026
By Eliane Catilina
Use of artificial intelligence in pricing has renewed policy concerns about price discrimination and consumer harm.
Enabling Regulation and the Alignment of Regulatory Mechanisms to Accommodate Technological Change
September 8, 2026
By Deborah Aiken
An analysis of test cases shows how reforms to the operational features of a safety regime perform across different technological settings.
Adaptive Governance of Artificial Intelligence in Agriculture and Food Systems: A Risk-Based and Case-Oriented Analysis
September 8, 2026
By Paul Mwebaze
AI-enabled tools are increasingly applied in precision agriculture, autonomous machinery, climate forecasting, and digital traceability systems.
Adaptive Regulation of Emerging Technologies, Risks and Reactions: From Climate to AI
September 8, 2026
By Arden Rowell & Jonathan Wiener
Technologies—applications of knowledge to convert inputs into outputs, to solve problems, and to generate new opportunities—carry the potential for both benefits and risks to individuals and society. A technology can be considered a bundle or portfolio of opportunities and risks—and an emerging technology represents a new emerging bundle. Risk regulation in response to emerging technologies also represents a bundle or portfolio of opportunities (risk reduction) and risks (countervailing harms)—one can even consider regulation as a technology, a human construct to address the risks and opportunities of our other technologies.
Regulatory Capacity: Governing in an Era of Rapid Technological Change
September 8, 2026
By Ann Keller, Konrad Posch, Brian Scholl, Margaret Taylor, Kenneth Taymor & Alexa Tisopulos
Comparing the regulatory regimes around gene therapies, including CRISPR/Cas-9 gene editing, and autonomous vehicle technology.
Lessons From the Past for Regulating AI
November 12, 2024
By Susan Dudley
To offer some insight into the question of how Artificial Intelligence should be regulated, this essay looks at experience with regulating past novel technologies—commercial flight, biotechnology, and the internet. These case studies help inform some preliminary lessons that may be applicable to other emerging technologies, including AI.
Dynamic Benefit-Cost Analysis for Uncertain Futures
September 17, 2019
By: Susan E. Dudley, Daniel R. Pérez, Brian F. Mannix, & Christopher Carrigan
Policymakers face demands to act today to protect against a wide range of future risks, and to do so without impeding economic growth. Yet traditional analytical tools may not be adequate to frame the relevant uncertainties and tradeoffs. Challenges such as climate change, nuclear war, and widespread natural disasters don't lend themselves to decision rules designed for discrete policy questions and marginal analyses. We refer to such issues as "uncertain futures."
Muddling-Through and Deep Learning for Managing Large-Scale Uncertain Risks
September 17, 2019
By: Tony Cox
Building on Charles Lindblom's research on the limits of rational-comprehensive decision-making, Tony Cox provides insights on how machine learning can help individuals and institutions make better informed decisions - improving society's experience of 'muddling through' policymaking under uncertainty.
Privacy Research: The Need for Evidence in the Design of U.S. Privacy Policy
July 03, 2019
By: Daniel R. Pérez
This regulatory policy insight details the importance of using evidence to inform the development of U.S. privacy policy and identifies the kinds of evidence that would be particularly useful for policymakers to consider.
NTIA's Approach to Consumer Privacy
November 12, 2018
By Daniel R. Pérez
The National Telecommunications and Information Administration issued a request for public comments on developing the administration's approach to consumer privacy. This public interest comment provides an overview of the agency's proposed approach to guide federal policymaking, and provides three core recommendations (1) Privacy regulation should be based on consumers' value, (2) the benefits of regulation should exceed social costs, and (3) future research should be focused on improving benefit-cost analysis of privacy regulations.