AI Exchange @ UVA [2026.12]
Our mission is simple: to keep the UVA community informed, engaged, and inspired as we navigate this transformation together.
Research Spotlight: Responsible Research in an AI-driven World
👉 Main idea: AI is helping us see climate change more clearly, while forcing harder conversations about the environmental costs of the systems that power it.
Xi Yang, an Associate Professor in the University of Virginia’s Department of Environmental Sciences
“Because of the large quantity of data and the way we identify trees we have to use AI to to do this kind of work. Traditional remote sensing algorithm and approaches cannot help us”. - Prof. Yang
Lauren Bridges, an Assistant Professor in UVA’s Department of Media Studies, explores how artificial intelligence intersects with the environment.
“I do think three to five years from now we're going to see some really smart, very geographically specific policy aimed at addressing the various different harms, in particular of the data center industry, while also trying to support the growth of the industry”. - Prof. Bridges
Together, they offer perspectives on what responsible AI research looks like as environmental challenges continue to grow.
🔑 Key Insights from the Podcast
AI is mapping climate change tree by tree.
Using deep-learning models and high-resolution imagery, Xi Yang’s lab identified more than six million dead “ghost trees” along the Atlantic coast.The AI boom has material, local consequences.
Lauren Bridges studies data center expansion in Northern Virginia, home to the world’s densest concentration of server farms. From diesel backup generators and water-intensive cooling systems to massive electricity demand, her research highlights how the infrastructure powering AI reshapes local environments and communities.AI is both a tool and a tension.
The same high-powered computing that enables climate modeling also powers data center growth. Yang’s research uses advanced computation to reveal environmental change, while Bridges studies the environmental footprint of the infrastructure powering those systems.
Tools & Initiatives Mentioned:
Digital Technology for Democracy Lab - Pioneering transdisciplinary research to explore democracy in the digital age
Rivanna - UVA’s supercomputing system used for AI model training
AI Research: How Firms Are Really Using AI (and What They Expect Next)
Yotzov, I., Barrero, J. M., Bloom, N., Bunn, P., Davis, S. J., Foster, K. M., Jalca, A., Meyer, B. H., Mizen, P., Navarrete, M. A., Smietanka, P., Thwaites, G., & Wang, B. Z. (2026, February). Firm data on AI (NBER Working Paper No. 34836). National Bureau of Economic Research.
A new NBER working paper surveys nearly 6,000 senior executives across four countries to understand how AI is actually affecting firms today, and how leaders expect it to reshape work in the near future.
💡 The Big Idea
AI is already widespread inside firms (about 70% report using it), but so far, it has barely moved the needle on jobs or productivity. Executives, however, expect more noticeable effects soon: modest job reductions and meaningful productivity gains over the next three years.
“This contrast implies a sizable gap in expectations, with senior executives predicting reductions in employment from AI and employees predicting net job creation”. (pg. 2)
🧪 How they did it
Surveyed ~6,000 senior executives (primarily CEOs/CFOs) across the U.S., UK, Germany, and Australia (Nov 2025–Jan 2026).
Asked about current AI adoption, personal weekly AI use, and AI’s impact on employment and sales per worker (past 3 years and expected next 3 years).
Ran a parallel U.S. employee survey (~3,000 workers) with identical impact questions.
📈 Key findings
69% of firms report using AI (U.S. highest at 78%, Australia lowest at 59%).
Most common use: text generation with LLMs (41%), followed by data processing and visual content creation (~30%).
Executives use AI ~1.5 hours per week on average; 28% report no use. UK executive usage has risen ~50% since early 2025.
Over the past 3 years, 80–90% of firms report no employment or productivity impact. Average realized productivity gain: just 0.29%.
Over the next 3 years, executives expect AI to:
Boost productivity by 1.4% overall (2.3% in the U.S.)
Reduce employment by 0.7% overall (–1.4% UK, –1.2% U.S.)
Increase total output by ~0.8%
UVA AI In The News:
🌍 Why Climate Forecasts Still Depend on Supercomputers
Author: Antonios Mamalakis, Professor of Data Science and Environmental Science
Climate projections aren’t powered by AI alone. They rely on massive physics-based models running on petaflop-scale supercomputers like those at NCAR. AI can speed things up — but it can’t replace the math that governs Earth’s chaotic system.
🧮 Virtual Earth models: Scientists divide the planet into millions of 3D grid boxes and simulate temperature, wind, oceans, and more over decades.
🌀 Chaos requires ensembles: Because small changes can shift outcomes, researchers run many simulations to separate real trends from noise.
⚡ Supercomputers are essential: Quadrillions of calculations per second are needed to project future climate risks.
🤖 AI complements, not replaces: AI improves short-term forecasts and data analysis, but long-term climate projections require solving physical equations.
Bottom line: AI helps us analyze the climate — but supercomputers remain the backbone of understanding and preparing for a warming world.
AI Funding Opportunities
Schmidt Sciences’ Humanities and AI Virtual Institute (HAVI) is accepting proposals for research projects at the intersection of digital humanities and artificial intelligence.
Funding: Up to $800,000 per project
Deadline: March 13, 2026
The program supports two-way collaboration: humanities scholars applying AI tools to their research, and AI researchers gaining humanistic perspectives on data, models, and problem spaces.
Questions? Contact havi@schmidtsciences.org
DTD Lab Seed Grants
The UVA Democracy & Digital Technology (DTD) Lab is now accepting proposals for its 2026 Seed Grants supporting research at the intersection of democracy and digital technology. Open to all UVA faculty (postdocs eligible as co-PIs), the program includes:
Large Seed Grants (up to $40K) for collaborative, externally fundable projects
Small Seed Grants (up to $15K) for early-stage research and partnerships
NEW: AI & Democracy Grants (up to $50K, with potential second-year renewal) focused on the institutional and societal integration of AI systems
Full proposals for all programs due March 20, 2026.
AI Events @ UVA
UVA Library: Practical AI Ethics
🗓 March 18, 2026| 11:00 AM–12:00 PM | Shannon Library
🎤 David Danks (Philosophy, AI, UVA School of Data Science)
A practical approach to AI ethics that yields processes and tools for designers, regulators, and users, grounded in real case studies.
HooHacks 2026
🗓 March 23 - 24, 2026| 24-hour hackathon
Virginia’s largest hackathon and one of the top 50 collegiate hackathons nationally. Teams compete across categories including AI/ML applications, with $10,000+ in prizes and workshops from sponsors like Google Cloud, Intel, and Capital One (Open to students 18+).
2nd Annual Cosmic Horizons Conference
🗓 July 13 - 26, 2026| Charlottesville, VA
The NSF-Simons AI Institute for Cosmic Origins (CosmicAI) is excited to announce the 2nd Annual Cosmic Horizons Conference hosted by the NSF National Radio Astronomy Observaotry (NRAO).
The recent revolution in AI is fundamentally changing how astronomers observe, explore, analyze, and model astronomical data. The Cosmic Horizons Conference aims to bring together researchers who are actively developing and applying AI/ML methods in astronomy.
Coming Soon: AI and the Future of Writing at UVA
Piers Gelly and T. Kenny Fountain, faculty members in the University of Virginia’s Department of English, explore how generative AI is reshaping the teaching and practice of writing. As large language models change how students draft, revise, and think on the page, they examine what this shift means for voice, authorship, and academic integrity. Through classroom experiments and broader pedagogical frameworks, they highlight both the opportunities and tensions of integrating AI into writing instruction.
UVA AI Resources
AI in the Curriculum Playbook: A practical framework for intentionally embedding AI capabilities into any program or course.
AI for Academic Excellence - Student Toolkit: A comprehensive guide for students on the best uses of AI.
AI Agents in Economic Research (Anton Korinek): A guide for researchers on the use of AI agents.
UVA Claude Builders Student Club: A 250+ strong group for those interested in development via Claude.
UVa AIML Seminar - Seminar featuring artificial intelligence, machine learning, and their applications.
UVA Podcasts We Listen to
Co-Opting AI: Public Conversations About Artificial Intelligence and Society:
Prof. Mona Sloane’s series Co-Opting AI is a virtual public speaker series that interrogates and demystifies AI.UVA Data Points: Podcast from the School of Data Science.
HOOS in STEM: From Prof. Ken Ono this series showcases the marvelous cornucopia of STEM at UVA, from the latest innovations to growth inside and outside the classroom.
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