Plenary Talk: How Easy Access to Statistical Likelihoods of Everything Will Change Interaction with Computers
Jeffrey Bigham, Carnegie Mellon University, will give a plenary talk on 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 and program computers would dramatically (and quickly!) change. That hasn’t really happened… yet. This talk will first take a step back to ground current possibilities in what we know about effectively designing for interacting with machine learning. Then, I’ll overview work we’ve been doing in my lab to provide the technical foundation for remaking how user interfaces work and how they’re built, with the goal of leveraging our new easy access to statistical likelihoods over almost everything.
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.
Event Snapshot
When and Where
Who
Open to the Public
| Cost | FREE |
Interpreter Requested?
Yes