Stanford Seminar - Systems for Supporting Intent Formation and Human-AI Communication

January 20, 2023
Elena Glassman of Harvard University
Systems for Supporting Intent Formation and Human-AI Communication: Existing Challenges and Promising Design Strategies
Communication between humans is often a multimodal conversation. It can be a recurring loop with optional steps depending on the complexity of the situation and our possibly evolving understanding of what we want. The same is true of our communication with computers. When a human is reasoning about complex data and asking for automated assistance, this conversation can be especially hard. Carefully designed data rendering and interface affordances can help significantly. I will present a selection of novel interactive systems whose interface designs help users (1) quickly and accurately form a mental model of a concept from relevant data, (2) form - and update - their beliefs about what they want (3) communicate what they want to a computer when its automation capabilities are helpful and/or (4) have justified confidence that the automation being carried out reflects their current intentions. Systems discussed will include an interface for comparing and contrasting similar but distinct programming libraries based on real-world usage and a mixed-initiative neurosymbolic system that helps users perform qualitative coding, i.e., label large volumes of short texts with emergent themes.
About the speaker:
Elena L. Glassman is an Assistant Professor of Computer Science at the Harvard Paulson School of Engineering & Applied Sciences, specializing in human-computer interaction. She recently served as the Stanley A. Marks & William H. Marks Professor at the Radcliffe Institute for Advanced Study. At MIT, she earned a PhD and MEng in Electrical Engineering and Computer Science and a BS in Electrical Science and Engineering. Before joining Harvard, she was a postdoctoral scholar in Electrical Engineering and Computer Science at the University of California, Berkeley, where she received the Berkeley Institute for Data Science Moore/Sloan Data Science Fellowship. Her recent work has been awarded funding by the Harvard Data Science Institute, the NSF programs on Fairness in Artificial Intelligence, Formal Methods in the Field, Cyber-Human Systems, and the Science of Learning and Augmented Intelligence.