Gender and AI: An Ethical Assessment of Why Female Users’ Trust Matters

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Women frequently report lower levels of trust in artificial intelligence than men and express greater concerns regarding the use of this technology. Existing literature suggests several contributing factors, including gender bias in AI outputs, social concerns about professional judgment when relying on AI, women’s underrepresentation in the AI workforce, and heightened concerns about data privacy and misuse. While closing this “AI trust gap” is important to ensure equitable access to the benefits of AI, this paper argues that the issue should not be framed merely as increasing adoption or consumer engagement; instead, women’s more cautious relationship with AI may reflect a valuable form of critical trust that offers important insights for ethical AI design. The analysis further suggests that women’s lower levels of trust in AI may function as a form of critical trust that helps identify limitations, biases, and accountability gaps that might otherwise remain overlooked in AI design and governance. Through a normative ethical analysis informed by empirical findings, this paper examines the claim that fostering calibrated trust in AI among all members of society requires an ethics-of-care approach. Rather than promoting either blind trust or excessive distrust, calibratedtrust involves reliance that appropriately reflects AI’s capabilities, limitations, and broader societal implications. We argue that care ethics provides a suitable framework for designing AI systems that are responsive to relational vulnerability, contextual inequalities, and diverse user experiences.