talk: AI Resilient Interfaces for Code Generation and Efficient Reading, Dr. Jonathan Kummerfeld

The UMBC Language Technology Seminar Series  (LaTeSS – pronounced lattice) showcases talks from experts researching various language technologies, including but not limited to natural language processing, computational linguistics, speech processing, and digital humanities. UMBC people can join the group here.

AI Resilient Interfaces for Code Generation and Efficient Reading

Dr. Jonathan K. Kummerfeld, University of Sydney

3-4 pm EDT Tuesday, 10 Sept. 2024, ITE 325b at UMBC and online via WebEx

AI is being integrated into virtually every computer system we use, but often in ways that mean we cannot see the decisions AI makes for us. If we don't see a decision, we cannot notice whether we agree with it, and what we don't notice, we cannot change. For example, using an AI summarization system means trusting that it has captured all the aspects of a document that are relevant to you. If the task is high stakes, then the only way to check is to read the original document, but that significantly decreases the value of the summary. In this talk, I will present the concept of AI resilient interfaces: systems that use AI while giving users the information they need to notice and change its decisions. I will walk through two examples of novel systems that are more AI resilient than the typical solution to the problem for (1) SQL generation and (2) faster reading. I will conclude with thoughts on the potential and pitfalls of designing with AI resilience in mind.

Jonathan K. Kummerfeld is a Senior Lecturer (i.e., research tenure-track Assistant Professor) in the School of Computer Science at the University of Sydney. He is currently also a DECRAfellow, and collaborates with a range of academics across the world, including on DARPA-funded projects on AI agents that communicate. He completed his Ph.D. at the University of California, Berkeley, and was previously a postdoc at the University of Michigan, and a visiting scholar at Harvard. Jonathan’s research focuses on interactions between people and NLP systems, developing more effective algorithms, workflows, and systems for collaboration. He has been on the program committee for over 50 conferences and workshops. He currently serves as Co-CTO of ACL Rolling Review (a peer review system) and is a standing reviewer for the Computational Linguistics journal and the Transactions of the Association for Computational Linguistics journal.