Objectives
Abstract: Demographic biases are widely affecting artificial intelligence. In particular, gender bias is clearly spread in natural language processing applications, e.g. from stereotyped translations to poorer speech recognition for women than for men. In this talk, I am going to overview the research and challenges that are currently emerging towards fairer natural language processing in terms of gender.
Short bio: Marta R. Costa-Jussà is a Ramon y Cajal Researcher at the Universitat Politècnica de Catalunya (UPC, Barcelona). She received her PhD from the UPC in 2008. Her research experience is mainly in Machine Translation. She has worked at LIMSI-CNRS (Paris), Barcelona Media Innovation Center, Universidade de São Paulo, Institute for Infocomm Research (Singapore), Instituto Politécnico Nacional (Mexico) and the University of Edinburgh. She has participated in 18 European (including a MarieCurie Action) and Spanish national projects. She has organised 10 workshops in top venues and published more than 100 papers. She has been part of the Editorial Board of the Computer Speech and Language journal. She regularly cooperates with companies as a scientific consultant. Currently, she is leading the Spanish Project of AMALEU. Recently, she has received two Google Faculty Research Awards (2018 and 2019).