About:
I’m broadly interested in examining the social and ethical implications of natural language processing (NLP) technologies, and on creating more equitable, just, and empowering NLP technologies by centering people—who are inseparable from language—in technologies’ development and evaluation. My recent work has addressed principled evaluation and measurement, particularly of generative AI capabilities, behaviours, and impacts; understanding how people perceive and use generative AI; and supporting AI and NLP practitioners in their ethical work. I’ve also worked on using NLP approaches to examine language variation and change (computational sociolinguistics), for example developing models to identify language variation on social media. I approach my work from an interdisciplinary and sociotechnical perspective and draw inspiration from a wide range of disciplines, including NLP, responsible AI (RAI), human-computer interaction (HCI), and sociolinguistics.
I was previously a principal researcher in the Fairness, Accountability, Transparency, and Ethics in AI (FATE) group at Microsoft Research Montréal, where I was also a postdoctoral researcher. I completed my Ph.D. in computer science at the University of Massachusetts Amherst working in the Statistical Social Language Analysis Lab under the guidance of Brendan O’Connor, where I was also supported by the NSF Graduate Research Fellowship. I received my B.A. in mathematics from Wellesley College. I interned at Microsoft Research New York City in summer 2019, where I worked with Solon Barocas, Hal Daumé III, and Hanna Wallach. I was named one of the 2022 100 Brilliant Women in AI Ethics.
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