Ethical Risks and Structural Implications of AI-Mediated Medical Interpreting

Comprehensive Summary

The article examines the ethical and structural challenges of using AI in medical interpreting and public health communication. AI systems often struggle with regional dialects, figurative language, culturally embedded meanings, and emotionally sensitive conversations, such as those about reproductive health or chronic illness. These limitations can result in clinically significant misunderstandings that compromise patient safety, informed consent, and trust in health care. Additionally, the large datasets required for AI raise concerns about surveillance, secondary use of linguistic data, and gaps in privacy protections. The author emphasizes that AI should supplement, not replace, professional interpreters, and must operate under clear oversight and regulatory standards.

Outcomes and Implications

Relying on AI interpreters as a substitute for human professionals risks normalizing lower standards of care for patients with limited English proficiency, potentially worsening health disparities. Health systems must prioritize language access grounded in human expertise, community oversight, and structural equity rather than cost-saving automation. The careful integration of AI could improve efficiency and support clinicians, but only if it complements professional interpreters, maintains transparency, and protects patient confidentiality and rights. Policymakers and health institutions should implement regulatory guardrails to ensure ethical, equitable, and safe use of AI in clinical and public health settings.