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激励关于医疗保健技术发展中的偏见的透明沟通

Anna Tovmasyan1,2, Alice Liefgreen3, Sandra Wachter2

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Collabra. Psychology
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概括

激励性信息不会直接增加人工智能开发人员培训偏见透明度的意图. 然而,内部和外部的动机都与对AI偏见的技能培养和道德沟通的更大意图有关.

关键词:
医疗保健 人工智能 人工智能包容性 包容性 包容性动机 激励 动机透明度 透明度 透明度值的价值观 值的价值观

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科学领域:

  • 计算机科学 计算机科学
  • 人工智能伦理学 人工智能伦理学

背景情况:

  • 医疗保健人工智能 (AI) 系统越来越复杂,但它们的偏见潜力,特别是关于患者受保护的特征,越来越令人担忧.
  • 开发人员经常未能披露这些固有的局限性,这引发了关于人工智能开发透明度的问题.

研究的目的:

  • 调查支持性激励信息是否影响医疗保健AI开发人员愿意透明地沟通他们技术中的偏见.
  • 探索不同动机框架 (支持自主性与控制) 和重点 (个人利益与法律影响) 对开发人员意图的影响.

主要方法:

  • 进行了两项涉及计算机科学学生 (N=271和N=209) 的研究.
  • 参与者被随机分配到以支持自主或控制的方式框架的通信中,强调个人利益或缺乏透明度的法律后果.
  • 测量了与透明度培训,技能发展,道德声音和对抗主义有关的行为意图.

主要成果:

  • 沟通框架 (自主支持与控制) 并没有显著影响参加偏见透明度教育课程的意图.
  • 内部 (自主) 和外部动机都与有意获得透明技术开发技能的意图有积极的关联.
  • 增加的动机与更大的道德声音相关,并减少了对透明度的敌意.

结论:

  • 一个单一的,简短的培训干预不足以促进关于AI偏见的透明沟通.
  • 大学和工作场所应该培养一个广泛支持的激励环境,以鼓励人工智能开发人员的透明度和道德实践.