CS Colloquium Speaker Speaker: Jeffrey Bigham, Carnegie Mellon University Date: Monday, November 4 Time: 12:30pm EST Location: CS 105 Host: Andrés Monroy-Hernández Event page: https://www.cs.princeton.edu/events/26736 Register for live-stream online here: https://princeton.zoom.us/webinar/register/WN_rsGVIJvfSfuDNAZVKJ5Dlg Title: How Easy Access to Statistical Likelihoods of Everything Will Change Interaction with Computers Abstract: The recent arrival of impressive large language models and coding assistants has led to speculation that the way we interact with computers would dramatically (and quickly!) change. That hasn’t really happened… yet, but we are at an inflection point where we can influence interaction for both better and, potentially, worse. In this talk, I’ll use examples from our research to highlight four coming challenges and opportunities in how we interact with computers in (i) maintaining user agency, (ii) designing user interfaces that encourage responsibility, (iii) making computer systems accessible, and (iv) designing, generating, and navigating user interfaces automatically. The future of human-computer interaction will be both more familiar and less familiar than we think; this talk is intended to help develop your sense of what is likely to be and which futures you want to build. Bio: Jeffrey P. Bigham is an Associate Professor in the Human-Computer Interaction and Language Technologies Institutes in the School of Computer Science at Carnegie Mellon University, and the Director of Human-Centered Machine Learning within AIML at Apple. He builds systems that advance how people can responsibly work with machine learning to do interesting and useful things. This has taken on a variety of focuses throughout his career – he has worked on applications in accessibility for disabilities, systems that used crowdsourcing to power a wide variety of real-time experiences, and most recently on how we can design responsible and useful experiences using generative AI. Much of his work has focused on accessibility because he sees the field as a window into the future, given that people with disabilities are often the earliest adopters of AI. Bigham received his B.S.E degree in Computer Science from Princeton University in 2003, and his Ph.D. in Computer Science and Engineering from the University of Washington in 2009.