Title: Representation and Identity: Opportunities and Challenges for Language-Capable Robots

Presenter: Assistant Professor of Computer Science, Colorado School of Mines

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Abstract: Robots capable of natural language hold promise across a variety of domains, from intelligent tutoring to advanced manufacturing. Yet they also pose unique challenges not shared by other robotic or language-capable technologies. In this talk, I will begin by introducing the concept of robot cognitive architectures, using as an example our own work on Cognitive Status informed language understanding and generation, in which we infuse insights from cognitive psychology and linguistics into the software design of interactive robots. I will then take a step back and critically consider how roboticists' design choices regarding robots' mind/body and social identities may influence interactions and interactants.

Bio: Tom Williams is an Assistant Professor of Computer Science at the Colorado School of Mines, where he directs the Mines Interactive Robotics Research Lab (MIRRORLab). Prior to joining Mines, Tom earned a joint PhD in Computer Science and Cognitive Science from Tufts University in 2017. Tom’s research focuses on enabling and understanding natural language based human-robot interaction that is sensitive to environmental, cognitive, social, and moral context. His work is funded by grants from NSF, ONR, and ARL, as well as by Early Career awards from NSF, NASA, and AFOSR.