Technofeminism at Work: Artificial Intelligence‐Mediated Negotiations and the Reproduction of Gendered Communication Norms

ABSTRACT This study examines how artificial intelligence (AI) reshapes gender dynamics in workplace negotiations. Adopting a technofeminist lens, we conceptualize gender–technology relations as mutually shaping and fluid. Using a convergent mixed‐methods design, participants negotiated job offers with an AI chatbot recruiter. Qualitative transcript analysis identified gendered communication patterns, which were complemented by quantitative measures of negotiation outcomes and pre‐ and post‐survey results. Findings reveal a paradox: AI‐mediated negotiations muted traditional gender gaps—women and men achieved comparable outcomes—yet masculine‐coded communication styles were associated with higher scores than feminine‐coded communication styles. Participants also anthropomorphized the AI, projecting gendered identities that shaped satisfaction and outcomes. We introduce the concept of recursive human‐AI gender learning to explain how humans and algorithms iteratively train one another, reproducing gendered communication norms within seemingly neutral systems. The study contributes to feminist AI scholarship by illuminating how AI both disrupts and reproduces gendered power relations in organizational life.

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Publication Details

Journal
Gender Work and Organization
Published
2026-04-03
DOI
https://doi.org/10.1111/gwao.70145
Primary Topic
Ethics and Social Impacts of AI
Type
article
Field-Weighted Citation Impact
0.00
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article

Technofeminism at Work: Artificial Intelligence‐Mediated Negotiations and the Reproduction of Gendered Communication Norms

Jing Betty Feng, Sue H. Moon
Gender Work and Organization
Ethics and Social Impacts of AI
article

Technofeminism at Work: Artificial Intelligence‐Mediated Negotiations and the Reproduction of Gendered Communication Norms

Jing Betty Feng, Sue H. Moon
article en

Abstract

ABSTRACT This study examines how artificial intelligence (AI) reshapes gender dynamics in workplace negotiations. Adopting a technofeminist lens, we conceptualize gender–technology relations as mutually shaping and fluid. Using a convergent mixed‐methods design, participants negotiated job offers with an AI chatbot recruiter. Qualitative transcript analysis identified gendered communication patterns, which were complemented by quantitative measures of negotiation outcomes and pre‐ and post‐survey results. Findings reveal a paradox: AI‐mediated negotiations muted traditional gender gaps—women and men achieved comparable outcomes—yet masculine‐coded communication styles were associated with higher scores than feminine‐coded communication styles. Participants also anthropomorphized the AI, projecting gendered identities that shaped satisfaction and outcomes. We introduce the concept of recursive human‐AI gender learning to explain how humans and algorithms iteratively train one another, reproducing gendered communication norms within seemingly neutral systems. The study contributes to feminist AI scholarship by illuminating how AI both disrupts and reproduces gendered power relations in organizational life.

Gender Work and Organization
Farmingdale State College (US)
Gender equality
Openalex Percentile: Top 24%
Ethics and Social Impacts of AI
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