Chinese women use AI masks to shape livestream identities
Assembling, Breaking, and Refusing the Mask: Agency in AI-Mediated Self-Presentation in Livestreaming
Human-Computer Interaction
Summary
Lots of Chinese women who livestream online create special online 'masks' to show ideal versions of themselves. The authors studied how these masks use AI and personal choices to handle pressures from gender roles, business needs, and platform rules. Sometimes, streamers change or remove these masks when it becomes too hard or not right for them. The study shows that controlling these masks is about managing many things at once, not just one tool, and that breaking masks reveals the hidden work and unfair effects of being visible online.
What this means in practice
- •For livestream platform designers: Create features that allow streamers to better negotiate and control AI-based self-presentation tools reflecting complex social demands.
- •For social media product teams: Design systems that support users in modifying or rejecting AI-generated persona aspects to reduce unseen labor and improve user agency.
Authors
Yang Hong, Nusrat Jahan Mim, Sharifa Sultana
Abstract
Our mixed-method study examines how Chinese women livestreamers use masking to construct idealized mediated personas while navigating gendered, commercial, organizational, and platform pressures alongside personal agendas. We built on the concept of masking, analyzed 627 recruitment posts, and conducted livestream observations and interviews with 26 Chinese women streamers. We found that streamers assembled masks across bodies, AI-mediated technologies, spaces, performances, and social relations to become recognizable while protecting personal boundaries. These masks were continually negotiated, and participants sometimes broke, resisted, or refused them when demands became misaligned or unsustainable. We conceptualize masking as a sociotechnical assemblage in which agency lies in preserving, disrupting, and reconfiguring relations rather than controlling a single interface. We further theorize breaking as a consequential part of masking that exposes hidden labor and unequal costs of visibility. We offer theoretical and design directions for more negotiable, contestable, and agency-supporting AI-mediated self- presentation.