看到就是相信吗? 探索人工智能中的性别偏见 专科医生的影像
Alice Hartley1, James Fisher1,2
1School of Medicine, Newcastle University, Newcastle upon Tyne, UK.
The clinical teacher
|December 8, 2025
概括
人工智能生成的医疗专业人员图像显示出明显的性别偏见,过度代表男性并延续刻板印象. 医疗保健教育工作者必须谨慎使用人工智能图像,以避免在医学中强化有害的性别规范.
科学领域:
- 医疗教育 医学教育
- 人工智能的人工智能
- 性别偏见的性别偏见
背景情况:
- 妇女在医学和医学教育中面临不成比例的性别偏见.
- 人工智能 (AI) 越来越多地被用于医学教育.
- 如果用于生成医疗专业人员的图像,人工智能可以加强性别刻板印象.
研究的目的:
- 检查人工智能生成的医生图像中的性别分布.
- 为了比较AI图像的性别代表性与英国专业实习医生数据.
主要方法:
- 在30个医学专业中生成了1200张AI图像.
- 不包括招聘率低于0.25%的专业.
- 将人工智能图像的性别分布与英格兰NHS的招聘数据进行比较,使用奇平方测试.
主要成果:
- 人工智能图像显示男性占有率明显高 (82%),而不是NHS数据 (47%).
- 人工智能工具没有产生女性全科医生,整形外科医生或泌尿科医生.
- 女性在皮肤病学,产科/妇科和整形外科方面占有过多的比例.
结论:
- 人工智能生成的医疗图像表现出代表性和呈现性性别偏见.
- 这种偏见可能会在医疗职业道路上延续有害的性别刻板印象.
- 医疗保健教育工作者应该谨慎行事,并为负责任的AI图像使用制定指南.
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