A Risk-Based Governance Framework for Using Generative Artificial Intelligence in Anatomy Education
A new risk management model has been developed to align artificial intelligence integration in medical education with ethical and academic standards.
A comprehensive study addressing the ethical and technical challenges of using generative artificial intelligence technologies in anatomy education has been published. Synthesizing data from 2016 to 2026, this study proposes a risk-based framework that determines the role of artificial intelligence in preserving donated cadaveric materials, anatomical accuracy, and assessment processes.
Ethical Standards and Donor Dignity
In the integration of artificial intelligence applications into anatomy education, the ethical use of donated human tissues and cadavers stands out as a primary priority. The study emphasizes that artificial intelligence models must operate in harmony with established ethical standards regarding body donation.
Anatomical Accuracy and Information Security
The risk of generative artificial intelligence models producing false information, known as 'hallucinations' in anatomical data, poses a serious threat to educational processes. Therefore, the verification of content generated by artificial intelligence and the maintenance of human oversight are defined as critical requirements.
Risk-Based Governance Model
The proposed framework aims to guide educational institutions by classifying the use of artificial intelligence according to different risk levels. This model aims to ensure that the technology remains a supporting tool for traditional and ethics-based anatomy education.