If done right, Generative AI technologies such as ChatGPT or BARD have the potential to revolutionize the teaching and learning process. But what does “done right” even mean? Join us on a discussion with students, teachers, and experts in generative AI, to discuss the opportunities and challenges of this new AI technologies. Can they help students with better and more diverse learning experiences? Or can they help educators create more effective, personalized educational opportunities? Education-wise, are we on the path to “idiocracy” or is this a chance for us to become even better and more educated than we’ve ever been?
About the Speakers:
Kevyn Collins-Thompson is an Associate Professor of Information and Computer Science at the University of Michigan, where he is also Director of the Masters in Applied Data Science program. His research explores algorithms and systems for optimally connecting people with information, particularly at the intersection of AI and education. His research has been applied to real-world systems ranging from intelligent systems that help children with their literacy skills, to Web search engines that help people learn more effectively. He received his Ph.D. from the Language Technologies Institute at Carnegie Mellon University and B.Math from the University of Waterloo. Before joining the University of Michigan he was a researcher at Microsoft Research. His work has been recognized with honors that include several ACM best paper awards, the Coursera Outstanding Educator Award, and selection as a Distinguished Member of the ACM for outstanding scientific contributions to computing.
Zara M. Burzo is a freshman at Skyline Highschool in Ann Arbor. She enjoys reading, writing, traveling, learning languages, tennis, and chess. Her first encounter with coding was learning binary at the age of 5 in the sand at a beach in Mexico. Zara has taken coding classes and also helped teach them — she is also currently taking AP Computer Science Principles at Skyline.
Rada Mihalcea is the Janice M. Jenkins Professor of Computer Science and Engineering at the University of Michigan and the Director of the Michigan Artificial Intelligence Lab. Her research interests are in computational linguistics, with a focus on lexical semantics, multilingual natural language processing, and computational social sciences. She serves or has served on the editorial boards of the Journals of Computational Linguistics, Language Resources and Evaluations, Natural Language Engineering, Journal of Artificial Intelligence Research, IEEE Transactions on Affective Computing, and Transactions of the Association for Computational Linguistics. She was a program co-chair for EMNLP 2009 and ACL 2011, and a general chair for NAACL 2015 and *SEM 2019. She is an ACM Fellow, a AAAI Fellow, and served as ACL President (2018-2022 Vice/Past). She is the recipient of a Sarah Goddard Power award (2019) for her contributions to diversity in science, and the recipient of a Presidential Early Career Award for Scientists and Engineers awarded by President Obama (2009).
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