Goisauf Melanie, Cano Abadía Mónica
ELSI Services and Research, BBMRI-ERIC, Graz, Austria.
Front Big Data. 2022 Jul 14;5:850383. doi: 10.3389/fdata.2022.850383. eCollection 2022.
Artificial intelligence (AI) is being applied in medicine to improve healthcare and advance health equity. The application of AI-based technologies in radiology is expected to improve diagnostic performance by increasing accuracy and simplifying personalized decision-making. While this technology has the potential to improve health services, many ethical and societal implications need to be carefully considered to avoid harmful consequences for individuals and groups, especially for the most vulnerable populations. Therefore, several questions are raised, including (1) what types of ethical issues are raised by the use of AI in medicine and biomedical research, and (2) how are these issues being tackled in radiology, especially in the case of breast cancer? To answer these questions, a systematic review of the academic literature was conducted. Searches were performed in five electronic databases to identify peer-reviewed articles published since 2017 on the topic of the ethics of AI in radiology. The review results show that the discourse has mainly addressed expectations and challenges associated with medical AI, and in particular bias and black box issues, and that various guiding principles have been suggested to ensure ethical AI. We found that several ethical and societal implications of AI use remain underexplored, and more attention needs to be paid to addressing potential discriminatory effects and injustices. We conclude with a critical reflection on these issues and the identified gaps in the discourse from a philosophical and STS perspective, underlining the need to integrate a social science perspective in AI developments in radiology in the future.
人工智能(AI)正在医学领域得到应用,以改善医疗保健并促进健康公平。基于人工智能的技术在放射学中的应用有望通过提高准确性和简化个性化决策来提升诊断性能。虽然这项技术有改善医疗服务的潜力,但许多伦理和社会影响需要仔细考虑,以避免对个人和群体,尤其是最脆弱人群造成有害后果。因此,引发了几个问题,包括:(1)在医学和生物医学研究中使用人工智能会引发哪些类型的伦理问题?(2)放射学领域,特别是在乳腺癌的情况下,如何应对这些问题?为了回答这些问题,我们对学术文献进行了系统综述。在五个电子数据库中进行了检索,以识别自2017年以来发表的关于放射学中人工智能伦理主题的同行评议文章。综述结果表明,讨论主要涉及与医学人工智能相关的期望和挑战,特别是偏差和黑箱问题,并且已经提出了各种指导原则以确保人工智能符合伦理规范。我们发现,人工智能使用的一些伦理和社会影响仍未得到充分探索,需要更多关注以解决潜在的歧视性影响和不公正问题。我们从哲学和科学技术研究(STS)的角度对这些问题以及讨论中发现的差距进行了批判性反思,强调未来在放射学人工智能发展中需要整合社会科学视角。