This event is organized by the Schwartz Reisman Institute for Technology and Society.
Note: Event details may change. Please refer to the Schwartz Reisman Institute for Technology and Society’s events page for the most current information.
Our weekly SRI Seminar Series welcomes Hamsa Sridhar Bastani, Associate Professor of Operations, Information, and Decisions and of Statistics and Data Science at the Wharton School of the University of Pennsylvania, where she co-directs the Wharton Healthcare Analytics Lab. Bastani is an expert in machine learning and optimization, with a strong focus on human–AI collaboration and applications in healthcare, public policy, and education.
In this talk, Bastani will share results from the first large-scale field experiment deploying generative AI tutors in high school math classrooms. The study reveals that while generative AI can significantly improve short-term performance, poorly designed tools may harm long-term learning by encouraging overreliance and undermining skill acquisition. Bastani shows how embedding simple safeguards can mitigate these risks—offering essential guidance for decision-makers deploying AI tools in educational and professional settings.
Moderator: Shreyas Sekar, Department of Management, UTSC
Location: Online
Talk title:
“Unpacking the unintended consequences of AI in education”
Abstract:
The rapid integration of AI into educational settings presents opportunities and challenges. This talk will discuss findings from three large-scale field studies investigating the impact of AI on student learning. First, we found that unfettered access to ChatGPT negatively impacted short-term student learning outcomes. Second, to understand longer-term effects, we examined learning in chess academies. Contrary to the popular strategy of promoting student agency, our findings show that self-regulated learning—where students decide when to request AI help—can substantially harm learning by diminishing engagement and motivation. Third, we found that training students with “adversarial examples” significantly improved their ability to identify and correct ChatGPT-generated hallucinations, enabling effective human-AI collaboration. Taken together, these studies suggest that while providing students with unguided AI tools can be detrimental, targeted interventions that train students to critically engage with AI can be beneficial.
Suggested reading:
Hamsa Bastani, Osbert Bastani, Alp Sungu, Haosen Ge, Özge Kabakcı, and Rei Mariman, “Generative AI without guardrails can harm learning: Evidence from high school mathematics,” Proceedings of the National Academy of Sciences of the United States of America 122 (26), https://doi.org/10.1073/pnas.2422633122 (2025).
About Hamsa Bastani
Hamsa Sridhar Bastani is an associate professor of Operations, Information, and Decisions (OID) as well as Statistics and Data Science at the Wharton School of the University of Pennsylvania, where she co-directs the Wharton Healthcare Analytics Lab. Bastani’s research focuses on developing novel machine learning algorithms for learning and optimization, including methods for sequential decision-making (bandits, reinforcement learning, active learning), learning from auxiliary data sources (transfer learning, meta-learning, surrogates), and designing effective human–AI interfaces (interpretability, fairness). Recently, she has been exploring how AI systems affect and augment human behavior, with the goal of designing AI tools that help humans thrive.
Bastani is passionate about applying machine learning and AI to tackle high-impact societal problems across domains such as healthcare, public policy, and education. She has worked closely with national governments to deploy algorithms at the country scale to improve public health outcomes. For example, she collaborated with the Government of Greece to nearly double the efficacy of their national border COVID-19 screening via reinforcement learning, and with the Government of Sierra Leone to improve patient access to essential medicines by nearly 20% through decision-aware learning. She also co-led the first large field study deploying generative AI tutors in high school math classes, demonstrating critical risks for human overreliance and deskilling. Her recent work continues to combine field evidence from randomized controlled trials with theoretical models to inform the careful design necessary for effective human–AI collaboration.
Her research has been published in leading outlets including Nature, Management Science, Operations Research, and PNAS, and has garnered numerous recognitions, including the Wagner Prize for Excellence in Operations Research, the INFORMS Pierskalla Award for best healthcare paper, and the George Nicholson Prize. Bastani graduated summa cum laude from Harvard in 2012 with an A.M. in physics and an A.B. in physics and mathematics. She completed her PhD in Electrical Engineering at Stanford University under the supervision of Mohsen Bayati and spent a year as a Herman Goldstine postdoctoral fellow at IBM Research.
About the SRI Seminar Series
The SRI Seminar Series brings together the Schwartz Reisman community and beyond for a robust exchange of ideas that advance scholarship at the intersection of technology and society. Seminars are led by a leading or emerging scholar and feature extensive discussion.
Each week, a featured speaker will present for 45 minutes, followed by an open discussion. Registered attendees will be emailed a Zoom link before the event begins. The event will be recorded and posted online.