Beyond a Neutral Tool or Teammate: Envisioning AI Interventions for Women’s Equity in Male-Dominated Teams

Paper Title

Beyond a Neutral Tool or Teammate: Envisioning AI Interventions for Women’s Equity in Male-Dominated Teams

Publication Info

• Topic area: AI interventions for gender equity in male-dominated teams.
• Keywords: AI, gender equity, male-dominated teams, human-AI collaboration, feminist HCI, workplace dynamics, equity-oriented design, gender bias, team collaboration, inclusion.

Background and Problem

• Problem / challenge: Women in male-dominated AI teams face barriers to participation, influence, and recognition due to gendered dynamics, microaggressions, and structural inequities. Current technologies fail to address these specific challenges.
• Significance: Addressing these inequities is critical for fostering inclusive team environments and ensuring diverse perspectives in AI design, which impacts broader societal outcomes.
• Motivation and related work: Prior research highlights gender bias in AI systems and male-dominated workplaces, but few studies explore how AI itself could intervene to support women in such environments. This paper builds on feminist HCI and CSCW traditions to address this gap.

Solution

• Proposed approach: AI interventions designed to mitigate gender inequities in male-dominated teams by supporting equitable collaboration, amplifying marginalized voices, and empowering women through personalized mentorship and coaching.
• Novelty:
  1. Linking women AI professionals’ lived experiences to envisioned AI interventions for equity.
  2. Extending feminist HCI principles to AI-mediated collaboration, treating AI as a social actor capable of shaping team norms.
  3. Proposing concrete AI-mediated strategies for addressing gender inequities while identifying risks and safeguards.
• Procedure and key techniques:
  • Conducted semi-structured interviews with 30 AI professionals (22 women) to understand gendered challenges and envision AI interventions.
  • Thematic analysis of interview data to identify recurring challenges, intervention ideas, and concerns.
  • Developed design principles for equity-oriented AI systems based on participant insights and feminist HCI theories.

Results

• Concrete findings:
  • Women face barriers such as frequent interruptions, overlooked contributions, and double standards in competence and authority.
  • Envisioned AI interventions include gender-aware meeting analytics, turn-taking regulation, voice amplification, and personalized coaching.
  • Concerns include risks of surveillance, transparency issues, and reinforcing stereotypes through anthropomorphism.
• Advantage over baselines: AI interventions are envisioned to provide nuanced, real-time support for equitable collaboration, addressing subtle interactional dynamics that traditional tools overlook.
• Experiments / evaluation:
  • Semi-structured interviews with 30 participants (22 women, 7 men, 1 non-binary) across academia and industry.
  • Analysis focused on identifying gendered challenges, speculative AI solutions, and perceived limitations.
• Limitations and future work:
  • Sample imbalance (more women in academia, more men in industry) may limit generalizability.
  • Predominantly Global North participants; cross-cultural perspectives are needed.
  • Limited representation of non-binary and intersectional identities.
  • Future research should explore AI interventions in diverse sectors and cultural contexts.

Summary

This study investigates how AI can address gender inequities faced by women in male-dominated teams, focusing on their lived experiences and speculative visions for AI interventions. Findings reveal challenges such as interruptions, overlooked contributions, and structural barriers, alongside envisioned solutions like gender-aware analytics, equitable turn-taking, and personalized coaching. Concerns about surveillance, transparency, and anthropomorphism highlight design tensions. The paper contributes to feminist HCI and CSCW by proposing AI as a social actor capable of reshaping team norms for equity. Future research should expand on intersectional and cross-cultural dimensions to refine these interventions.