Conversational Assistants and Gender Stereotypes: Public Perceptions and Desiderata for Voice Personas

By Amanda Cercas Curry, Judy Robertson, Verena Rieser. 2020

Subfields: Dialogue & Conversational AI, AI Ethics, Fairness & Society

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In AI Ethics, Fairness & Society

1. Diyi Yang
2. William S. Isaac
3. Iason Gabriel
4. Borja Balle
5. T. Stepleton
6. Atoosa Kasirzadeh
7. Abeba Birhane
8. Zeerak Talat

Citations in the corpus

• Characteristics of Harmful Text: Towards Rigorous Benchmarking of Language Models (2022, background): “If a model with a persona claims a particular identity, the model could misrepresent or denigrate that identity group by perpetuating stereotypes, e.g., subservient digital assistants that have female personas [24].”
• Taxonomy of Risks posed by Language Models (2022, background): “presented as inherently linked to the female gender [19, 36].”
• The Importance of Modeling Social Factors of Language: Theory and Practice (2021, background): “Examples include conversational agents’ inconsistent personality in conducting dialogues with humans (Cercas Curry et al., 2020), the failure of machine translation systems in generating culturally appropriate and polite outputs (Jones and Irvine, 2013; Matusov, 2019; Vanmassenhove et al., 2019),…”