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Title: Supporting text-as-data research with controllable and explainable NLP systems

 

Presenter: Maria Pacheco, PhD, Assistant Professor, Department of Computer Science, University of Colorado, Boulder

 

Abstract: Natural Language Processing (NLP) systems are everywhere, and the broader research ecosystem is no exception. Researchers in the social sciences, the humanities and industry have been making increasing use of NLP technologies to make sense of large textual repositories and answer fundamental questions in their fields of study. When NLP systems are employed as research tools, ensuring their reliability and transparency is incredibly important. Most current systems, while seemingly powerful, are opaque and often fail to satisfy the needs of researchers. In this talk, I will discuss the main challenges that arise when incorporating NLP technologies in text-as-data research, and make the case for explainable, controllable alternatives that can strike a balance between generalization and trustworthiness.

 

Bio: Maria Pacheco is an Assistant Professor in the Department of Computer Science at the University of Colorado Boulder. Before joining CU, she was a Postdoctoral Researcher at Microsoft Research NYC. Maria completed her PhD in Computer Science at Purdue University, and her BSc. in Computer Science and Engineering at the Universidad Simon Bolivar in Caracas, Venezuela, where she was born and raised.