The evolution of AI in diagnostic dentistry has transformed the field with high-performance models, yet ethical considerations remain underexplored. This paper emphasizes the need for a framework addressing unique challenges in dental AI, including bias, data privacy, and the impact on dental professionals. Ethical issues arise from the reliance on AI for caries detection, given the potential for misdiagnosis and the need for diverse datasets to avoid reinforcing discrimination. Additionally, patient privacy concerns are significant, as many studies neglect ethical approval processes and patient consent. The literature predominantly reflects high-income countries, leaving gaps in representation from low-to-middle-income nations. Future research must adopt collaborative, multicenter approaches to ensure comprehensive and inclusive AI implementations. Establishing transparent guidelines, diversity protocols, and mandatory training for dental professionals will enhance ethical practices. This balanced approach is crucial for maximizing AI benefits while promoting equity in dental care, ensuring no population is excluded or further marginalized.
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