Lowell Lecture: AI and Civic Engagement with Nathan Sanders, Dr. Avijit Ghosh, and Jessica Chapel

About this event

All Adults, College Students, Older Adults, Young Adults (Ages 20-34). Artificial Intelligence experts Nathan Sanders, Dr. Avijit Ghosh, and Jessica Chapel lead a panel discussion on AI and civic engagement as a part of the 2026 Lowell Lecture Series; moderated by BPL President David Leonard. Jessica Chapel is Chief of Digital & Online Services at the Boston Public Library, where she leads digitization, digital stewardship, and UX, with a growing focus on AI's role in information access and discovery. Her department operates Digital Commonwealth, the statewide repository connecting 270+ Massachusetts libraries, archives, and museums. She co-hosts an ongoing speaker series with the Leventhal Map & Education Center on AI and cultural heritage collections, and co-moderates BPL's AI Interest Group. Dr. Avijit Ghosh is a Lead Technical AI Policy Researcher at Hugging Face, a central platform for open AI models, datasets, and research tools used by industry, government, and academic developers worldwide. He is also a Research Affiliate at the University of Connecticut. His work sits at the intersection of AI research and policy, with a central focus on how we measure and benchmark AI systems, and whether those measurements can actually be trusted. He founded and leads the EvalEval Coalition, a multi-stakeholder initiative bringing methodological rigor and accountability to AI evaluation. His broader research spans algorithmic bias, agent autonomy, AI for science, and third-party flaw disclosure, with coverage in The New York Times, Forbes, The Guardian, ProPublica, Wired, and MIT Technology Review. He represents Hugging Face in technical engagements with legislators and regulators in the United States, United Kingdom, European Union, and Singapore on open-source AI governance and evaluation standards. His work has helped shape AI regulation in New York City and prompted Facebook to remove its biased ad targeting algorithm. Nathan E. Sanders is a data scientist focused