Overview
Generative Artificial Intelligence (AI) is rapidly transforming how the public interacts with federal statistical data. As AI systems increasingly draw on public datasets, ensuring that federal statistics are accurately and reliably represented has become a critical priority. This webinar will present the findings and recommendations from the recent FCSM report, AI-Ready Federal Statistical Data: An Extension of Communicating Data Quality (FCSM 25-03) and some of the early work in this space. The session will explore how agencies can prepare their data assets for seamless integration with generative AI tools and agent models, which rely on machine-understandable data to deliver accurate, context-rich responses to users. A key focus will be on the adoption of Model Context Protocols (MCPs)—emerging open-source standards designed to enable AI agents to retrieve, interpret, and utilize federal data in a controlled and standardized way. By enhancing APIs and metadata with MCPs and other AI-friendly features, agencies can ensure that both human users and AI agents have access to authoritative, high-quality statistical information.
Speakers
Bella Mendoza, Data Scientist at the Department of Commerce in the Office of the Undersecretary for Economic Affairs
Luke Keller, Chief Innovation Officer & Bureau AI Lead, US Census Bureau
Dominique Duval-Diop, Deputy Chief Data Officer & Acting Chief Data Officer, Department of Commerce
Discussant
Travis Hoppe, Chief AI officer, Centers for Disease Control and Prevention
About the Speakers
Bella Mendoza is a Data Scientist at the Department of Commerce in the Office of the Undersecretary for Economic Affairs, where they work on advancing data accessibility and AI readiness in federal data systems. Previously, they served as a Data Science Fellow at the White House Office of Science and Technology Policy with the U.S. Digital Corps. In that role, Bella co-chaired an interagency working group on diversifying the federal data workforce and built automation tools that streamlined federal funding reporting under the Bipartisan Infrastructure Law and Inflation Reduction Act. Bella holds dual B.A. degrees in Data Science and Legal Studies from the University of California, Berkeley.
Luke Keller is the Chief Innovation Officer and Bureau AI Lead at the U.S. Census Bureau, where they manage cross-functional teams delivering AI products that help policymakers, researchers, and the public better understand the nation’s people and economy. They lead a portfolio of AI, privacy engineering, and policy and governance projects at the largest statistical agency in the country, combining technical product leadership with strategic oversight to turn cutting-edge AI innovation into practical solutions. Luke’s career spans industries including social impact technology startups and web development, where they were instrumental in developing web-based products and advancing innovation. Their expertise in AI, risk mitigation, and continuous user feedback has been highlighted in discussions on platforms such as FedInsider. Under their leadership, Census teams have delivered: AI platforms eliminating 800K+ hours of manual work through machine learning automation; Model Context Protocol (MCP) infrastructure enabling AI agent interoperability; Privacy-enhancing technologies that enable secure computation on confidential data; AI governance frameworks balancing innovation velocity with responsible AI best practices.
Dr. Dominique Duval-Diop is the Department of Commerce Acting Chief Data Officer serving in the Office of the Undersecretary for Economic Affairs. An accomplished policy leader, data scientist, and economic geographer, she has used data analytics and AI to support responsible decision-making and program design. Prior to joining Commerce, Dr. Duval-Diop served as the U.S. Chief Data Scientist at the White House Office of Science and Technology Policy. She served as an American Association for the Advancement of Science (AAAS) fellow and Geospatial Information Advisor, and then as Associate Director at the Millennium Challenge Corporation, where she worked on creating data-informed international infrastructure programs in countries including Senegal, Mozambique, Tunisia, and the Solomon Islands. Dr. Duval-Diop earned a Bachelors in Economics from Northwestern University, a Master of Public Administration from Columbia University, a doctorate degree in Economic Geography from Louisiana State University, and a certificate in Applied Data Analytics from the Coleridge Initiative.
Discussant
Travis Hoppe is the Chief AI officer at Centers for Disease Control and Prevention. He holds a Ph.D. in Physics from Drexel University, and served his post-docs at the National Institutes of Health. He serves as the CDC representative for the National Science and Technology Council (NSTC) for AI/ML, a standing member of the Federal Committee on Statistical Methodology (FCSM), and leads research, development, and policy work on AI at the CDC.
Event Type
- NISS Hosted