In a few short months, many of us have heard of or tried ChatGPT, the large language model (LLM) that generates coherent texts on demand in a broadly accessible chat interface. Many opinions have been voiced about ChatGPT and other natural language intelligence systems, and crucially, how they may affect education and teaching in practice. Are LLMs an unstoppable force for cheating, a powerful tool for learning, or all or none of the above?
In this panel we'll bring together multidisciplinary, research-based perspectives on these topics — UMass professors and an alum who are world-leading experts in the large language models, the impact of technology on education, and social implications of language technologies. In the question period, we invite community members to share examples of what they've seen from ChatGPT in practice. What have we learned about these issues, and what plans, if any, should we have going forward?
Torrey Trust is Associate Professor of Learning Technology in the Department of Teacher Education and Curriculum Studies in the College of Education at UMass Amherst. She is the author of a popular presentation on ChatGPT & Education. More broadly, her work investigates how technology can support teachers in designing contexts that enhance student learning, and critically examines the relationships between teaching, learning, and technology. She is the winner of research and teaching awards including the APEX 2021 Award for Publication Excellence, the Outstanding Teaching Award at the College of Education, and the ISTE Making IT Happen Award for "extraordinary commitment, leadership, courage and persistence in improving digital learning opportunities for students.” She completed her PhD in Education (Teaching & Learning) at the University of California Santa Barbara in 2014.
Mohit Iyyer is Assistant Professor in the College of Information and Computer Sciences at UMass Amherst. His natural language processing research develops methods to better model and evaluate long-form natural language generation, including human-in-the-loop text generations systems to help authors compose text, such as fictional narratives. His research has been recognized by the Samsung AI Research of the Year and National Science Foundation CAREER awards and is supported by Open Philanthropy, Adobe, IBM, and NSF among others. He completed his PhD in 2017 at the University of Maryland and served as Young Investigator at the Allen Institute for AI.
Su Lin Blodgett is Senior Researcher in the Fairness, Accountability, Transparency, and Ethics in AI (FATE) group at Microsoft Research Montréal. She studies the ethical and social implications of language technologies, developing approaches for anticipating, measuring, and mitigating harms. Her work focuses on the complexities of language and language technologies in their social contexts, and on supporting NLP practitioners in their ethical work. She has been named one of 100 Brilliant Women in AI Ethics, and Rising Star in EE/CS. She completed her Ph.D. in computer science from UMass Amherst in 2021.
The panel is moderated by Brendan O'Connor, an Associate Director of the Computational Social Science Institute.
This panel is co-organized by the Computational Social Science Institute (CSSI), Institute for Social Science Research (ISSR), and Public Interest Technology Initiative (PIT @ UMass).
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