The ethics of simplification: balancing patient autonomy, comprehension, and accuracy in AI-generated radiology reports
Our findings highlight an ethical tension between improving readability and maintaining clinical accuracy. While 7th-grade readability remains an ethical ideal, current AI tools cannot reliably produce accurate reports below the 11th-grade level. Ethical implementation of AI-generated reporting should include layered communication strategies and model transparency to safeguard patient autonomy and comprehension.
Authors
- Young Han Lee (ORCID: https://orcid.org/0000-0002-5602-391X)
- Hye Sun Lee (ORCID: https://orcid.org/0000-0001-6328-6948)
- Kyunghwa Han (ORCID: https://orcid.org/0000-0002-5687-7237)
- Suk‐Won Song (ORCID: https://orcid.org/0000-0002-9850-9707)
- Chanseok Park (ORCID: https://orcid.org/0000-0002-2208-3498)
- Sungjun Kim (ORCID: https://orcid.org/0000-0002-9873-2474)
- Won Hwa Kim (ORCID: https://orcid.org/0000-0001-7137-9968)
- Jeongrok Seo
- Jae-Il Kim (ORCID: https://orcid.org/0000-0003-3002-6861)
Institutions
- Yonsei University (KR)
- Severance Hospital (KR)
- Kyungpook National University Hospital (KR)
- Kyungpook National University (KR)
- Gangnam Severance Hospital (KR)
- Yonsei University Health System (KR)
- Skyworks Solutions (United States) (US)
Publication Details
- Journal
- BMC Medical Ethics
- Published
- 2025-10-15
- DOI
- https://doi.org/10.1186/s12910-025-01285-3
- Citations
- 4
- Primary Topic
- Artificial Intelligence in Healthcare and Education
- Type
- article
- Field-Weighted Citation Impact
- 2.62
Funders
- Yonsei University
- Yonsei University College of Medicine