To achieve the goal of building natural language processing systems that help real-world users with tasks, such systems need to be able to communicate bi-directionally with their users. This includes systems describing and explaining their solutions and their difficulties. This also involves systems that can learn from a wide variety of feedback — including language — that a user may provide. I’ll describe our past and ongoing work in this space, and how it ties into our current ArtIAMAS project on systems to help triage documents efficiently and effectively.

Dr. Hal Daumé III is a Perotto Professor in Computer Science and Language Science at the University of Maryland, College Park; he has a joint appointment as a Senior Principal Researcher at Microsoft Research, New York City. His primary research interest is in developing new learning algorithms for prototypical problems that arise in the context of natural language processing and artificial intelligence, with a focus on interactive learning and understanding and minimizing social harms that can be caused or exacerbated by computational systems.