Think tank · Policy · Washington, DC · Est. 2013
The Center for Data Innovation is a policy research center focused on pro-innovation public policy for data-driven technologies, especially artificial intelligence. It formulates and promotes “pragmatic public policies” designed to maximize benefits of data-driven innovation in both public and private sectors, and it educates policymakers and the public on opportunities and challenges associated with data and technology trends such as open data, AI, and the Internet of Things.
The Center operates as part of the nonprofit, nonpartisan Information Technology and Innovation Foundation (ITIF), and ITIF describes the Center as one of its named policy centers. The Center also hosts the AI Policy Network and runs an AI Policy working group (“Ground Truth for AI Policy”) aimed at keeping policy professionals anchored in technical AI realities. The Center’s current strategic emphasis is on translating AI and data governance debates into implementable policy approaches (e.g., around AI model security, data rules for training/public information, AI adoption in the public sector, and infrastructure impacts such as data centers).
No curated programs yet. Check the careers page ↗.
Publications are temporarily unavailable.
The Center argues that mandatory government-directed “kill switch” approaches risk creating cybersecurity, reliability, and national security risks and should not be viewed as a sufficient substitute for broader controls needed to manage autonomous AI systems.
The Case for Safer AI Without Slowing ProgressThe Center argues against calls to slow frontier AI based on ungrounded probabilities of catastrophic outcomes, emphasizing evidence-based safety research, practical safeguard approaches, and the need to clarify what is known versus merely feared.
Congress Can Bring Clarity to AI Shutdown AuthorityThe Center discusses the practical and legal issues involved in shutting down AI systems, including confidentiality protections and uncertainty around government authority, in response to recent events involving model access controls and negotiations.
How to Fix the AI Model Theft Bill Before It Becomes LawThe Center argues that Congress should address specific shortcomings in the Deterring American AI Model Theft Act of 2026 approach so it deters harmful extraction without discouraging legitimate research or slowing U.S. innovation.
The CNN-Perplexity Lawsuit Is Not Just Another AI Copyright CaseThe Center argues that policymakers should distinguish between different types of AI-related copyright/trademark claims and treat the CNN-Perplexity lawsuit as legally distinct from training-data disputes; it contends existing legal tools may already address the underlying issues.
Five Concerns About AI Data Centers, and What to Do About ThemThe Center presents a report asserting that many public concerns about AI data centers stem from measurement and management frameworks rather than AI infrastructure scale itself, and it outlines policy directions focused on systemic impacts such as electricity, grid access, pricing, reliability, and water.