Exploring the moral status of cadavers through artificial intelligence: a thematic analysis of AI-based perspectives in anatomy education
Philosophy, Ethics, and Humanities in Medicine, cilt.21, sa.1, 2026 (SCI-Expanded, AHCI, SSCI, Scopus)
- Yayın Türü: Makale / Tam Makale
- Cilt numarası: 21 Sayı: 1
- Basım Tarihi: 2026
- Doi Numarası: 10.1186/s13010-026-00222-5
- Dergi Adı: Philosophy, Ethics, and Humanities in Medicine
- Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Arts and Humanities Citation Index (AHCI), Social Sciences Citation Index (SSCI), Scopus, IBZ Online, CINAHL, EMBASE, MEDLINE, Philosopher's Index, Psycinfo, Directory of Open Access Journals, Philosopher's Index full-text, Academic Search Ultimate (EBSCO), Biomedical Reference Collection: Corporate Edition (EBSCO), Health Research Premium Collection (ProQuest)
- Anahtar Kelimeler: Cadaver, Anatomy Education, Moral Obligations, Artificial Intelligence, Professionalism
- Sağlık Bilimleri Üniversitesi Adresli: Evet
Özet
Background: Cadavers play an irreplaceable role in anatomy education, offering unique opportunities for hands-on learning and the internalization of ethical values. While large language models (LLMs) are increasingly utilized in medical education, their perspectives on the moral status of cadavers remain underexplored. Methods: This study examined the responses of four LLMs—ChatGPT, Gemini, DeepSeek, and Copilot—regarding the concept, significance, and ethical responsibilities toward cadavers. A thematic analysis was conducted based on the AI-generated responses. Results: Three main themes emerged: (1) The Meaning of the Cadaver, where all LLMs preferred the term “donor,” reflecting respect for the body’s human origin and voluntary contribution to science; (2) The Importance of the Cadaver, emphasizing its educational superiority over models and simulations due to realism, anatomical variation, and ethical learning; and (3) Attitudes and Responsibilities, where LLMs expressed moral, ethical, legal, and academic responsibilities, highlighting respect, non-maleficence, and professional conduct. LLMs also acknowledged that donor-related terminology and background knowledge influence learners’ attitudes. Conclusions: Large language models attribute moral value to cadavers based on their human origin and educational role. While not granting full personhood, they support respectful and ethically guided engagement. These findings suggest that LLMs, when integrated into medical education, may reinforce ethical awareness and serve as potential tools for promoting professional identity formation.