Sexualised synthetic personas encode and amplify gendered power asymmetries through voice
For researchers and designers of AI systems, this work highlights how voice AI can perpetuate harmful gender stereotypes, calling for more inclusive design.
This study examines how commercial AI voice systems reproduce gendered power asymmetries, finding that female-coded voices are more often described with sexualised and submissive terms while male-coded voices are associated with dominance and positive traits.
This work examines sexualised AI-generated English-speaking voices offered by a popular commercial platform. New technologies may enable sexual empowerment and greater diversity in gender expression, yet toxic masculinity, heteronormativity, and the abuse of women and LGBTQ+ people remain pervasive online. Drawing on a Feminist HCI perspective, we examine how commercial voice AI systems reproduce and circulate particular performances of gender. We conducted a listening experiment with a diverse group of listeners, combining quantitative adjective selection, qualitative free-text responses, and acoustic analysis. Participants evaluated male- and female-coded voices presented with either sexualised scripts or neutral text. Results reveal a narrow range of gender expression, largely binary and heteronormative. Female-coded voices are more frequently described using sexualised and submissive terms, while male-coded voices are more often associated with dominance and positive traits.