Ethics, bias and regulation of artificial intelligence in dentistry

Youris Samón Mayan and Marta María Capote Fernández

SAP Artificial Intelligence in Dentistry, 2025

Abstract: Artificial intelligence is transforming dentistry, but its adoption raises ethical, bias-related, and regulatory questions that the accuracy-focused literature has left largely unexamined. This narrative review synthesizes the ethical dimensions of dental artificial intelligence across five axes: algorithmic bias and fairness, ethical principles, regulation and governance, data privacy and consent, and accountability and liability. The review draws on sources published up to 2025 and on the broader medical artificial intelligence literature. Dental models inherit demographic and acquisition biases from their training data, and fairness metrics are rarely reported. The principles of autonomy, beneficence, non-maleficence, and justice apply directly, and trustworthy use requires explainability and transparency. Regulatory frameworks are emerging but heterogeneous, and dental tools sit uneasily between medical device and general software regulation. Data governance, informed consent, and the allocation of responsibility for model errors remain unresolved. The review concludes that the clinical value of dental artificial intelligence will depend as much on resolving these dimensions as on further gains in accuracy.

Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:cwf:aidart:aid202528

DOI: 10.62486/aid202528

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