People are impacted by language technology in various ways: as direct users of the technology (by choice or otherwise), and indirectly, including as the subject of queries, as the subject of stereotypes, and as contributors to corpora. In these roles, risks are borne differentially by different speaker populations, depending on how well the technology works for their language varieties. This talk explores strategies for mitigating these risks based on transparent documentation of training data and situating our research in a broader context.
Emily M. Bender is a Professor of Linguistics at the University of Washington and the Faculty Director of the Professional Masters in Computational Linguistics (CLMS) program. Her research interests include the interaction of linguistics and NLP, computational semantics, multilingual grammar engineering, and the societal impact of language technology.