@inproceedings{cercas-curry-etal-2020-conversational,
    title = "Conversational Assistants and Gender Stereotypes: Public Perceptions and Desiderata for Voice Personas",
    author = "Cercas Curry, Amanda  and
      Robertson, Judy  and
      Rieser, Verena",
    editor = "Costa-juss{\`a}, Marta R.  and
      Hardmeier, Christian  and
      Radford, Will  and
      Webster, Kellie",
    booktitle = "Proceedings of the Second Workshop on Gender Bias in Natural Language Processing",
    month = dec,
    year = "2020",
    address = "Barcelona, Spain (Online)",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/jlcl-multiple-ingestion/2020.gebnlp-1.7/",
    pages = "72--78",
    abstract = "Conversational voice assistants are rapidly developing from purely transactional systems to social companions with {\textquotedblleft}personality{\textquotedblright}. UNESCO recently stated that the female and submissive personality of current digital assistants gives rise for concern as it reinforces gender stereotypes. In this work, we present results from a participatory design workshop, where we invite people to submit their preferences for a what their ideal persona might look like, both in drawings as well as in a multiple choice questionnaire. We find no clear consensus which suggests that one possible solution is to let people configure/personalise their assistants. We then outline a multi-disciplinary project of how we plan to address the complex question of gender and stereotyping in digital assistants."
}