Data Innovation

While false “Made in USA” claims are a real problem, the solution is not holding online marketplaces liable but strengthening data infrastructure and verification systems that enable regulators, consumers, and AI tools to more effectively identify and enforce legitimate claims.

China has surged ahead of the United States in adopting sidewalk delivery robots due to more proactive and coordinated policy experimentation, offering lessons for U.S. policymakers on how real-world pilots and clearer regulatory frameworks can accelerate deployment of autonomous delivery technology.

Agentic commerce—where AI agents autonomously shop and transact on users’ behalf—could deliver major efficiency gains, but outdated regulations and unresolved legal questions risk slowing adoption unless policymakers update rules built for human-driven transactions.

Policymakers who want to protect patients while ensuring clinicians can use tools that improve care should look to Utah for how regulatory sandboxes can maximize patient access to beneficial tools while minimizing clinical risk.

To protect individuals while preserving the open information ecosystem that supports innovation, policymakers should focus on outputs rather than training inputs, encourage transparency norms for autonomous AI agents, and create a safe harbor for responsible use of publicly available data.

Center for Data Innovation Director Daniel Castro sent a letter to Maryland Senate Finance Committee Chair Pamela G. Beidle, Vice Chair Antonio L. Hayes, and members of the committee in opposition to Senate Bill 889.

The European Parliament has disabled built-in AI features on corporate tablets and phones issued to MEPs and staff over concerns that data sent to cloud services by these features presented a security risk. This decision is misguided because it does not address security risks, drives AI use into the shadows, disrupts everyday productivity tools, and imposes disproportionate costs on the Parliament’s smaller delegations.

ITIF’s spring seminar course explores core emerging technologies and issues that are reshaping our world and, in the process, creating public policy challenges and opportunities. The course is open to congressional and federal staff only.

In Tech Policy Press, Daniel Castro argues that a dispute between the U.S. Department of Defense and Anthropic over military AI use underscores the need for Congress—not executive pressure or private contracts—to set clear statutory guardrails for deploying AI in national defense.

The GRID Act misdiagnoses the problem of rising electricity costs by treating data centers as inherently extractive and imposing punitive requirements, rather than addressing flawed market design. A better approach is a flexibility-first model that rewards adjustable AI demand, allowing data centers to support grid stability while protecting households from price spikes.