Center for Data Innovation Blog

Europe cannot match the United States and China in closed AI models, but it has an opportunity to lead in open models. The EU should remove regulatory and procurement barriers and foster a global open-model ecosystem.

Democrats should approach data centers as they have clean-energy infrastructure: take legitimate local concerns seriously and mitigate their impacts without allowing opposition to become a blanket rejection of development. As AI drives growing demand for data centers, policymakers should balance community protections with the economic, technological, and clean-energy benefits these investments can provide.

As AI systems gain greater autonomy, policymakers should prioritize research and safeguards that make dangerous behavior harder to initiate, easier to detect, and faster to contain. Emergency shutdown capabilities can be one useful tool in that effort, but a government‑mandated kill switch is neither universally feasible nor sufficient to address the broader challenges posed by autonomous AI.

AI presents real risks that warrant serious investment in security, testing, monitoring, and accountability, but claims that it poses an imminent existential threat lack a clear empirical basis. Rather than slowing AI development, policymakers should focus on evidence-based safeguards that make increasingly capable AI systems safer and more reliable.

Data centers can deliver substantial tax revenue, jobs, infrastructure investment, and lower utility costs when communities adopt policies that capture their benefits while managing local impacts.

The United States will not realize the full benefits of AI if policymakers treat it primarily as a technology that needs to be constrained.

Fixed compute thresholds for “frontier” AI models are quickly becoming outdated, and policymakers should adopt a dynamic, capability-based definition that keeps regulation focused on models posing truly exceptional risks.

Debate over AI’s workforce impact focuses too narrowly on whether it creates or eliminates jobs. Rather than impose new reporting requirements on businesses, policymakers should commission studies and expand existing surveys to capture how AI transforms work, not just changes in headcount.

The temporary shutdown of Anthropic's Fable 5 and Mythos 5 highlighted the uncertainty surrounding the government's authority to restrict access to frontier AI models and the costs that uncertainty can impose on innovation and trust. To provide greater clarity for developers, customers, and allies, Congress should establish a transparent statutory framework for AI shutdown authority with clear standards and proportionate safeguards.

Adversarial AI distillation poses a growing threat to U.S. AI leadership and national security, and Congress is right to address it through the Deterring American AI Model Theft Act (DAAMTA). But before passing the bill, lawmakers should narrow its scope, strengthen evidentiary standards, protect legitimate research, and pair it with technical safeguards and international cooperation to better combat large-scale AI model theft without hindering innovation.