AI Initiative Shares UChicago’s Vision for AI-Empowered Interdisciplinary Research

Written by Manasa Reddy (DSI) and Casey Keel (DSI)

Artificial intelligence (AI) is transforming daily life, but how will it continue reshaping the way we learn and discover? In 2024, President Paul Alivisatos and Provost Katherine Baicker convened a university-wide committee to explore this question and its implications for research and education at the University of Chicago.

At the AI Initiative Campus Event on February 12, 2026, researchers introduced findings from five projects funded by the Artificial Intelligence and Education Working Group, and from ten interdisciplinary AI Research Areas that integrate AI and machine learning (ML) with discipline-specific expertise to foster new interdisciplinary lines of inquiry. Across pedagogy and research, each project helped articulate how UChicago scholars and students can think with AI, about AI, and without AI to advance our collective understanding.

President Paul Alivisatos called this moment “a signal period in intellectual history,” adding “This heralds a new chapter of thinking with machines. I believe it is critical that we approach this time of vast scholarly opportunity by centering the human experience, and empowering and challenging the finest minds in the world—so many of whom are at UChicago among our students and faculty.”

“This initiative is building bridges across campus…bringing together depth of expertise in AI methods and across domains to tackle questions no discipline can answer alone,” said Rebecca Willett, Faculty Director of AI at the Data Science Institute and Worah Family Professor in the Wallman Society of Fellows, Department of Statistics, Computer Science, and the College. “Facilitating that bridge-building across disciplines is going to lead to entirely new fields of inquiry.”

Some of the projects featured in the event are discussed below.

Teaching Students to Think With and About AI

Five of the twelve projects funded by the AI and Education Working Group presented, sharing their inquiries into how AI alters, enhances, and disrupts existing classroom practices and dynamics. Julia Koschinsky (Executive Director and Senior Research Associate, The Center for Spatial Data Science) shared research on helping students use AI to strengthen rather than bypass their reasoning skills in order to “fool ourselves less with AI.” Mina Lee (Assistant Professor of Computer Science and Data Science) discussed her team’s work that deliberately builds friction into AI interactions to promote more mindful use of large language models.

AI and Education Working Group Funded Research Projects:

Integrating Evidence, AI, and Impact: A Novel Journal Club Models for Vascular Neurology Training
AI-Driven Placement testing for Spanish and Italian: Enhancing Language Placement Accuracy Through ACTFL-ALigned Assessment (Sara Dallavalle presented)
Enhancing NICU Fellows’ Communication Skills Using an AI-Driven Chatbot Simulation
DIY AI: Building Critical LLM Literacy Through Creative Coding
Enhancing Collaborative Learning with Customized AI Tutors in Introductory Economics Courses (Fulya Ersoy & Tomer Yeohshua-Sandak presented)
Writing without AI in the College
Fooling Ourselves Less with AI? Exploring AI-Assisted Scientific Reasoning with Students to Improve, Not Diminish, Their Reasoning Skills in Final Projects (Julia Koschinsky presented)
Machine Learning and Artificial Intelligence for Molecular Discovery and Engineering
Integrating Retrieval-Augmented AI Agents into University Curricula: A Case Study in Introductory Physics
Creating Teaching Materials to Introduce First-Year Law Students to the Effective and Ethical Use of AI (William Hubbard presented)
Designing Friction to Promote Mindful Use of LLMs (Mina Lee presented)
Leveraging AI to Enhance Electronics Education
AI Research Areas

The ten AI Research Area teams comprise scholars spanning archaeology, visual arts, public policy, natural sciences, economics, law, medicine, and philosophy. These teams are further organized into four thematic areas of study in which UChicago has distinctive strength—Culture and Creativity in an AI-Empowered Society, Learning the Rules of Life and the Universe, AI for Resilient and Adaptive Societies, and AI in the Service of Therapeutics.

Culture and Creativity in an AI-Empowered Society

AI and Human-Environment History: Ancient Cultures, Modern Insights (Timothy Harrison presented)
Human-Machine Creativity (Jason Salavon presented)

Can AI enrich lives through the arts? Or as Human-Machine Creativity researcher Jason Salavon (Associate Professor, Visual Arts) asked, “Can AI help us create meaning beyond statistical remixing of its training data?” The Culture and Creativity in an AI-Empowered Society research theme has treated creativity as exploration, innovation, and invention while bringing together diverse institutes, departments, and organizations. AI and Human-Environment research area leader Timothy Harrison (Professor of Near Eastern Archeology; Director, Institute for the Study of Ancient Cultures) discussed how AI-powered geospatial modeling and language analysis can illuminate the complex history of human-environment interaction that “reveals the past and guides the future.”

Learning the Rules of Life and the Universe

New Forms of Socio-Cognitive AI (James Evans presented)
Science Labs That Only AI can Build (Abigail Vieregg presented)
From Cells to Organs With AI (Margaret Gardel presented)

Spanning cognitive science, physics, and cell biology, this research theme asks how AI can help scientists discover the fundamental principles that govern minds, matter, and living systems. New Forms of Socio-Cognitive AI research area leader James Evans (Max Palevsky Professor of Sociology & Data Science; Director, Knowledge Lab; Faculty Co-Director, Novel Intelligence) described his team’s work building curiosity into AI’s structure to enable “disruptive hypothesis generation” at the margins of what we already know. Their goal, he explained, is “to build the least human AI rather than the most human,” to ultimately move “from digital twins to designing friendly cultural and cognitive aliens.”

Margaret Gardel (Horace B. Horton Professor, Physics, Molecular Engineering, and Molecular Genetics & Cell Biology) and collaborators are building AI frameworks to predict, understand, and engineer life across biological scales, supported by the NSF-Simons National Institute for Theory and Mathematics in Biology and the Biohub.

AI for Resilient and Adaptive Societies

Jobs and Prosperity Impacts of AI (Anders Humlum presented)
AI Innovations in Markets and Governance (Nicole Marwell presented)
AI Models of Climate and Sustainable Growth (Pedram Hassanzadeh presented)

Teams from Chicago Booth, the Becker Friedman Institute, the Harris School of Public Policy, the Crown Family School of Social Work, Policy & Practice, and the Law Schools are partnering with Fortune 500 companies, NGOs, and government agencies to understand how AI might spur and support societal change. AI Innovations in Markets and Governance research area leader Nicole Marwell (Professor and Faculty Director, SSL Program) oriented her team’s research around a central tension—governance depends on stability and predictability, but AI introduces uncertainty and risk. “How does AI challenge the rules and practices of governance?” she asked. “How can we reimagine governance to advance the public good, cultivate innovation, and manage risk?”

Pedram Hassanzadeh (Associate Professor, Geophysical Sciences; Member, Committee of Computational and Applied Mathematics; Faculty Director, AI for Climate) described how AI has ushered in the “second revolution in weather forecasting,” with AI-driven models capable of generating forecasts 100,000 times faster than traditional methods. Working with Harris School colleagues and the Indian government, the team delivered monsoon onset predictions to 38 million farmers in 2025.

AI in the Service of Therapeutics

AI-Driven Cancer Drug Discovery (Rick Stevens presented)
AI-Based Biological Design (Rama Ranganathan presented)

This theme builds on the longstanding partnership between the University of Chicago Medicine Comprehensive Cancer Center and Argonne National Laboratory to accelerate the translation of scientific discoveries into lifesaving treatments. Rick Stevens (Professor of Computer Science, Associate Laboratory Director, Computing, Environment and Life Sciences, Argonne National Lab) outlined his team’s goals to use AI to move beyond reviewing data to actively discovering new dynamics, interactions, and modules to accelerate the development of novel therapeutics, expand the diversity of target molecules, and lower costs.

Rama Ranganathan (Joseph Regenstein Professor in the Department of Biochemistry and Molecular Biology, Pritzker School of Molecular Engineering, and the College) described his team’s work using generative AI and statistical models to understand and engineer new biological systems as well as to discover design rules across scales of biology.

Looking Ahead

After the lightning talks, the event hosted a panel discussion on what it means for the University to lead AI research. Moderated by Dan Nicolae (Interim Chair, Elaine M. and Samuel D. Kersten, Jr. Distinguished Service Professor in the Departments of Statistics, Human Genetics, Medicine, and the College, Section of Genetic Medicine, and Faculty Co-Director, Data Science Institute), the conversation convened voices spanning computer science, statistics, cinema and media studies, African history, and econometrics. The discussions demonstrated a dynamic President Alivisatos described in his opening remarks: “It is precisely in moments like this when UChicago is at its best: When we insist on rigor, when we hold fast to careful standards of evidence, when we ask the hardest questions first, and when we refuse to be rushed into false choices between innovation and principle.”

In concluding, Katherine Baicker (Provost of the University of Chicago and Emmett Dedmon Distinguished Service Professor at the Harris School of Public Policy) noted that “We’re not trying to ‘out-Google’ Google.” What makes UChicago distinctive, she argued, is “not only that we have doctors who talk to artists who talk to philosophers—it’s the culture of rigorous questioning. That’s how ideas get better.” The research teams will continue developing over the coming year planning workshops, events, and community-building activities that will be open to the campus community.

You can find a video playlist of the day’s proceedings here. To watch the workshop and panel recordings from the event you will need CNET ID access. For more information about the UChicago AI Initiative or to get involved, contact aiinitiative@uchicago.edu.

This article was originally published on the Data Science Institute website.