人工智能在胚胎评估中的伦理:绘制地形图
Julian J Koplin1, Molly Johnston1, Amy N S Webb1,2
1Monash Bioethics Centre, Monash University, Clayton, VIC, Australia.
Human reproduction (Oxford, England)
|December 10, 2024
概括
人工智能 (AI) 可以通过使用机器学习 (ML) 来进行胚胎评估来增强生育治疗. 本综述探讨了诸如算法偏见和非人类化等伦理问题,以确保在生殖医学中负责任地实施人工智能.
科学领域:
- 生殖医学 生殖医学
- 医学伦理 医学伦理
- 人工智能的人工智能
背景情况:
- 人工智能 (AI) 提供了标准化和自动化生育治疗的潜力.
- 机器学习 (ML) 工具正在出现用于胚胎评估,旨在改善临床结果.
- 有限的文献存在于胚胎评估中的ML的伦理考虑.
研究的目的:
- 调查在医疗保健和医学中的ML的主要伦理问题.
- 确定与基于ML的胚胎评估在生育治疗中的相关伦理问题.
- 为讨论人工智能在辅助生殖中的负责任实施做出贡献.
主要方法:
- 关于与医疗保健中的ML相关的伦理关切的小审查.
- 识别和讨论与胚胎评估中的ML相关的伦理问题.
- 对人类生殖和患者信任的潜在影响的分析.
主要成果:
- 确定的伦理问题包括繁殖的"非人性化",算法偏见和责任问题.
- 透明度,可解释性,临床医生的非培训和正义也是重要的伦理考虑因素.
- 这些问题与ML在评估转移胚胎的应用有关.
结论:
- 解决伦理问题对于成功地在生育治疗中临床实施ML至关重要.
- 需要积极管理伦理问题,以保持消费者对人工智能辅助生殖技术的信任.
- 需要进一步的研究和讨论,以导航胚胎评估中的ML的伦理格局.
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