A MIDAS Data and AI in Society Forum:

AI and Creativity Forum

Wednesday, April 19, 2023, 3:30-4:30pm
Watkins Lecture Hall, Earl V. Moore Building, 1100 Baits Drive, Ann Arbor

ChatGPT Logo Artists and musicians have long relied on their own creativity and originality to produce works that inspire, move, and delight audiences. But what happens when we introduce generative AI tools into the creative process? In this panel discussion, a group of experts will discuss how artificial intelligence tools work and the opportunities and challenges they pose for music and art composition. From defining creativity to assessing intellectual property, panelists will examine the complex issues that artists and musicians face when using AI to compose novel music and art. They will also consider the potential disruption that generative AI tools may bring to existing modes of creative composition and how this could impact the future of the arts. Join us for a thought-provoking conversation about the intersection of technology and the future of creative work.

The paragraph above was written by ChatGPT, a large language model by OpenAI.

The image was generated by Stable Diffusion.


How will AI change the way we teach and learn?

If the headlines are to be believed, higher education is about to face its biggest disruption in history. But will AI tools really “end higher education as we know it,” “revolutionize the classroom,” or something else?

Faculty and others interested in adapting to such technology in the classroom joined our panel of distinguished educators, administrators, and researchers to learn about the principles and functionality of ChatGPT and other large language models, explore the implications of this new technology, discuss what roles AI can and should play in a classroom setting and develop concrete ideas for faculty to adapt to such technology.

Panelists and the audience discussed:

  • How the technologies underlying chatbots and language models work;
  • Ways that student use of these tools that might disrupt existing assignments and evaluation techniques;
  • Ways AI tools can aide teaching and learning;
  • How faculty determine acceptable and unacceptable uses of AI tools in the classroom;
  • What AI tools are currently good at and not good at (i.e. the errors they can introduce);
  • The promises and pitfalls of AI detection;
  • How AI tools are likely to evolve in the future and how faculty can be prepared for them.

Forum Co-Sponsors

About the Speakers

Forum Moderator

Associate Professor of Communication and Media, Associate Professor of Political Science, College of Literature, Science, and the Arts and Faculty Associate, Center for Political Studies, Institute for Social Research

Dr. Josh Pasek’s research explores how new media and psychological processes shape political attitudes, public opinion, and political behaviors. He moderated the panel and audience discussion as a social scientist who works with new and developing AI methods.


Vice President, Marketing & Communications, University Musical Society


Sara Billmann is the Vice President, Marketing & Communications for the University Musical Society (UMS), the National Medal of Arts-winning presenting organization at the University of Michigan. In this role, she oversees the strategic and creative campaigns for a 50-event season in classical music, theater, dance, jazz, and world music. She has served as co-chair of a national research study on value and impact in the arts and was project manager for UMS’s four-year Wallace Foundation Building Audiences for Sustainability grant, which focused on adventurous work and audiences and included a multi-year qualitative and quantitative research project.

Billmann received a Bachelor’s Degree in English from the University of Michigan and an M.B.A. with additional certification in public management from Stanford University.

Associate Professor of Music, School of Music, Theatre, and Dance

Michael Gurevich teaches courses in media art, computer-based composition, and physical computing, and also designs, studies, and composes for interactive music systems. His research explores new aesthetic and interactional possibilities that can emerge in performance with real-time computer systems.


John F. Nickoll Professor of Law, Michigan Law

Before rejoining the Michigan faculty in 2006, Litman was a professor of law at Wayne State University in Detroit, a visiting professor at New York University School of Law and at American University Washington College of Law, as well as a professor at Michigan Law from 1984 to 1990. In addition, she has taught copyright law at the University of Tokyo as part of the Law Faculty Exchange Program. Litman is a past trustee of the Copyright Society of the USA, a past chair of the Association of American Law Schools Section on Intellectual Property, and a past member of the Future of Music Coalition’s advisory council and the advisory board for Public Knowledge. She is an adviser for the American Law Institute’s Restatement of Copyright, a director of the American Trademark Law Society, and a member of the advisory board of Cyberspace Law Abstracts.

Assistant Professor of Electrical Engineering and Computer Science, College of Engineering

Lu’s research is focused on natural language processing, computational social science, and machine learning. More specifically, Lu works on algorithms for text summarization, language generation, argument mining, information extraction, and discourse analysis, as well as novel applications that apply such techniques to understand media bias and polarization and other interdisciplinary subjects.


Edgar F Codd Distinguished University Professor and Bernard A Galler Collegiate Professor; MIDAS Director

Dr. Jagadish contributed his perspectives as the host of the event and MIDAS Director. In his own words: “Data science has so much potential to do good things in so many aspects of life and society. I’m passionate about helping with that transformation and helping Michigan lead in that transformation while at the same time being cognizant of the potential risk and pitfalls. I want to help us get as much of the benefit of data science and AI as we can without suffering the harm they could bring if mismanaged.”

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