Health Equity Considerations in the Age of Artificial Intelligence

Abstract

Artificial intelligence (AI) is rapidly reshaping neurology, offering opportunities to improve efficiency, expand access to care, and enhance clinical decision making. Yet, without deliberate safeguards, AI can perpetuate or exacerbate existing health disparities, especially for systemically marginalized populations. This article examines the dual potential of AI, as both a driver of innovation and a source of bias, in the context of neurologic care. Drawing on literature review, stakeholder consultations, and practical examples, we outline the risks of AI worsening health disparities stemming from biased data sets, nonrepresentative training populations, and opaque algorithms. We also highlight opportunities for AI to promote health equity, including early disease detection in underserved settings, language-access tools, improved clinical trial diversity, and targeted quality improvement interventions. We propose 3 guiding principles for the neurology community to ensure that AI serves as a driver of equity: (1) ensuring diverse perspectives and community engagement in AI development; (2) expanding AI education and training for neurologists; and (3) establishing ethical policy and governance mechanisms. These recommendations are intended for clinicians, researchers, educators, health system leaders, policymakers, and professional societies and provide actionable strategies to integrate equity into every stage of AI design, implementation, and oversight. By centering inclusion, transparency, and accountability, AI can be harnessed to improve equitable access to high-quality neurologic care and to address long-standing disparities in neurologic health outcomes.

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