Keynote

A Framework for Thinking about Human-AI Communication: Challenges and Affordances for Figuring Out What We Want and Communicating it to Computers

by Elena Glassman (Harvard University, Cambridge, USA)

While we don’t always use words, communicating what we want to a computer, especially an artificially intelligent one, is a conversation—with ourselves as well as with it, a recurring loop with optional steps depending on the complexity of the situation and our potentially evolving understanding of what we want. I will present a framework for thinking about these interactions, illustrated with examples from publications on novel interactive visualization systems, program synthesis-backed systems, and neural network-backed systems. Time permitting, I will describe relevant theories from psychology and learning sciences, e.g., Variation Theory and Analogical Learning Theory, that have design implications for future interface and interactive system design—to hopefully maximize the bidirectional speed and accuracy of human intent formation and human-AI communication.

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.

Additional resources

• Elena Glassman’s website