The Data Science and AI Hub has responded to the White House
The Data Science and AI Hub has responded to the White House Request for Information on the Development of a 2025 National Artificial Intelligence (AI) Research and Development (R&D) Strategic Plan. The University of Minnesota has a longstanding legacy of leadership in foundational AI research, development, and real-world translation consistently contributing to breakthroughs in core AI technologies, applications, and ethics. Today, the UMN continues to play a pivotal role in shaping the future of AI in ways that reinforce and strengthen the US's leadership in this strategically vital domain.
We present three priority areas for AI Training, Foundational AI Research, and AI for Scientific Discovery.
- Advance and Accelerate AI Training and Learning - To ensure that the United States remains globally competitive in a rapidly evolving economy shaped by artificial intelligence and data-driven technologies, new federal investments in university-led workforce development and upskilling are essential.
- Support Foundational AI Research and Its Application - As the pace of AI innovation accelerates globally, new federal investments in university-led foundational AI research will be essential to maintain the United States’ leadership in the field. Foundational AI research—especially in areas such as Knowledge-Guided Machine Learning, scalable learning systems, AI for scientific discovery, and trustworthy AI—requires a long-term commitment and flexible research environments that are often difficult to sustain with short-term or narrowly scoped funding. Increased federal investment would amplify the university's ability to expand its impact, scale its innovations, and help shape the future of responsible AI development nationwide.
- Support the Development of Data Science and Other Research Areas Essential for the Advancement of Artificial Intelligence - To advance the frontiers of AI, new investments in universities are critically needed to strengthen the foundational ecosystem of data science, which underpins nearly every aspect of AI development. High-quality, well-curated data is essential for building robust, generalizable, and ethical AI systems.
Check out our full report to find the specific actions we recommend.
Authors: Jim Wilgenbusch, Shashi Shekar, Galin Jones, Vipin Kumar, Hayley Borck, and Genevieve Melton-Meaux
