ChatGPT, a chatbot powered by a large language model (LLM), is used by millions globally. Whether it is perceived as an anthropomorphic agent is currently being mapped out. Notably, the degree and nature of how ChatGPT is gendered remains unclear, despite agent gender cues being known to impact user attitudes and behaviors. ChatGPT, with its natural communication style and minimal gender cues, may offer radical insights on agent gendering. In this online mixed methods study, we invited first-time and experienced users to undertake tasks with ChatGPT. We surveyed their perspectives at two time-points following the interaction. Results indicated that ChatGPT’s communicative abilities correlated with gendered traits and its perceived capabilities reflected gender stereotypes. Our work suggests that ChatGPT is not gender-neutral, with implicit gender stereotyping occurring in the absence of gender cues and regardless of exposure. We advocate for conscientious design interventions to overcome agent-based perpetuation of human stereotypes.
Madeleine Steeds, Katie Seaborn, Takao Fujii et al.· International Conference on...· 0 citations
AI agents are typically deployed with gender cues that match traditional role expectations, such as female voices or avatars in assistive and support roles, because stereotype‐congruent designs enhance consumer adoption, trust, and engagement. However, prior research suggests that this practice risks entrenching occupational gender stereotypes at a societal level, raising the question of whether, and under what conditions, consumers’ stereotype‐congruent preferences can be attenuated. Drawing on Role Congruity Theory and research on bias correction, we propose that preferences for gender‐stereotypical AI agents are not fixed but contingent on the salience of gender cues in the decision context: when gender is foregrounded as a potential source of bias, consumers may deliberately shift toward counterstereotypical choices. Four experimental studies (
N
= 2530) test this proposition. Study 1 establishes that, under low gender‐cue salience, consumers default to AI agents whose gender aligns with stereotypical occupational roles. Study 2 shows that making gender cues salient in the choice process can attenuate these default preferences, and, under certain conditions, shift choices toward counterstereotypical agents. Studies 3 and 4 provide process evidence consistent with a role for action‐efficacy beliefs, whereby individuals come to view choosing a counterstereotypical AI agent as a meaningful way to promote gender equality. Gender salience, whether induced through design choices (Study 3) or explicit bias warnings (Study 4), was associated with stronger action‐efficacy beliefs, and the conditional indirect effects through these beliefs emerged primarily among women in male‐typed contexts, while comparable effects were weaker or absent among men and in female‐typed domains. Our findings identify conditions under which AI design choices can attenuate stereotype‐congruent preferences and provide evidence regarding the psychological processes associated with these shifts, offering actionable insights for managers and policymakers seeking to design AI agents that support more equitable human–AI interactions.
Marius C. Claudy, Anshu Suri, Sheng-Nan Ren et al.· Psychology & Marketing· 0 citations
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