Ethical Risks and Structural Implications of AI-Mediated Medical Interpreting

Abstract Artificial intelligence (AI) is increasingly used to support medical interpreting and public health communication, yet current systems introduce serious risks to accuracy, confidentiality, and equity, particularly for speakers of low-resource languages. Automatic translation models often struggle with regional varieties, figurative language, culturally embedded meanings, and emotionally sensitive conversations about reproductive health or chronic disease, which can lead to clinically significant misunderstandings. These limitations threaten patient safety, informed consent, and trust in health systems when clinicians rely on AI as if it were a professional interpreter. At the same time, the large data sets required to train and maintain these systems create new concerns about surveillance, secondary use of linguistic data, and gaps in existing privacy protections. This viewpoint examines the ethical and structural implications of AI–mediated interpreting in clinical and public health settings, arguing that its routine use as a replacement for qualified interpreters would normalize a lower standard of care for people with Non-English Language Preference and reinforce existing health disparities. Instead, AI tools should be treated as optional, carefully evaluated supplements that operate under the supervision of trained clinicians and professional interpreters, within clear regulatory guardrails for transparency, accountability, and community oversight. The paper concludes that language access must remain grounded in human expertise, language rights, and structural commitments to equity, rather than in cost-saving promises of automated systems.