Artificial intelligence and gender equity: An integrated approach for health professional education

Abstract

INTRODUCTION: As artificial intelligence (AI) increasingly integrates into health workplaces, evidence suggests AI can exacerbate gender inequity. Health professional programmes have a role to play in ensuring graduates grasp the challenges facing working in an AI-mediated world. APPROACH: Drawing from feminist scholars and empirical evidence, this conceptual paper synthesises current and future ways in which AI compounds gender inequities and, in response, proposes foci for an integrated approach to teaching about AI and equity. ANALYSIS: We propose three concerns. Firstly, multiple literature reviews suggest that the gender divide is embedded within AI technologies from both process (AI development) and product (AI output) perspectives. Next, there is emerging evidence that AI is reinforcing already entrenched health workforce inequities, where certain types of roles are seen as being the domain of certain genders. Finally, AI may disassociate health professionals' interactions with an embodied, agentic patient by diverting attention to a gendered digital twin. IMPLICATIONS: Responding to these concerns is not simply a matter of teaching about bias but needs to promote an understanding of AI as a sociotechnical phenomenon. Healthcare curricula could usefully provide clinically relevant educational experiences that illustrate how AI intersects with inequitable gendered knowledge practices. Students can be directed to: (1) explore doubts when working with AI-generated data or decisions; (2) refocus on caring through prioritising embodied connections; and (3) consider how to negotiate gendered workplaces in a time of AI. CONCLUSION: The intersection of gender equity and AI provides an accessible, illustrative case about how changing knowledge practices have the potential to embed inequity and how health professional education programmes might respond.

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