Emily M. Bender, Keynote

Emily M. Bender, Keynote

Professor, Linguistics, University of Washington

Meaning making with artificial interlocutors and risks of language technology

Humans make sense of language in context, bringing to bear their own understanding of the world including their model of their interlocutor's understanding of the world. In this talk, I will explore various potential risks that arise when we as humans bring this sense-making capacity to interactions with artificial interlocutors. That is, I will ask what happens in conversations where one party has no (or extremely limited) access to meaning and all of the interpretative work rests with the other, and briefly explore what this entails for the design of language technology.

Bio: Emily M. Bender is a Professor of Linguistics and an Adjunct Professor in the School of Computer Science and the Information School at the University of Washington, where she has been on the faculty since 2003. She holds an AB in Linguistics from UC Berkeley (1995) and a PhD in Linguistics from Stanford (2001). Her research interests include multilingual grammar engineering, computational semantics, and the societal impacts of language technology. Her work includes the LinGO Grammar Matrix, an open-source starter kit for the development of broad-coverage precision grammars; data statements for natural language processing, a set of practices for documenting essential information about the characteristics of datasets; and two books which make key linguistic principles accessible to NLP practitioners: Linguistic Fundamentals for Natural Language Processing: 100 Essentials from Morphology and Syntax (2013) and Linguistic Fundamentals for Natural Language Processing II: 100 Essentials from Semantics and Pragmatics (2019, with Alex Lascarides). She is the co-author of recent influential papers such as Climbing towards NLU: On Meaning, Form, and Understanding in the Age of Data (ACL 2020) and On the Dangers of Stochastic Parrots: Can Language Models Be Too Big? 🦜 (FAcct 2021). In her public scholarship, she brings linguistic insights to lay audiences to cut through the hype about 'AI' and facilitate understanding of the actual functionality of the systems being sold under that name.