对人工智能系统的以人为中心的解释
C Baber1, P Kandola1, I Apperly2
1School of Computer Science, University of Birmingham, Birmingham, UK.
Ergonomics
|April 8, 2024
概括
本研究引入以人为中心的可解释AI (XAI),以确保AI建议与用户偏好保持一致. 一个新的界面有助于用户了解他们的输入如何影响AI决策,提高对人工智能的信任和透明度.
科学领域:
- 人与计算机的交互
- 人工智能伦理学 人工智能伦理学
- 可解释的人工智能 (XAI)
背景情况:
- 人工智能 (AI) 系统日益增长的功能引发了人们对它们对日常决策的影响的担忧.
- 现有的可解释AI (XAI) 往往忽略了人工智能驱动的建议中关键的人类因素.
- 人工智能系统需要透明,能够响应个人用户的需求和偏好.
研究的目的:
- 正式定义以人为中心的可解释AI (XAI).
- 设计和评估一个用户界面,以促进用户偏好输入和与AI建议进行比较.
- 提高用户对人工智能决策过程及其影响的理解.
主要方法:
- 以人为中心的XAI原则的正式定义.
- 开发一个用户界面,用于偏好指示和比较.
- 进行用户试用,以评估界面的有效性.
主要成果:
- 用户可以在界面中有效地表明他们的偏好.
- 用户试验表明,参与者理解他们的偏好如何影响AI建议.
- 用户还可以欣赏他们的偏好和人工智能系统的偏好之间的对比.
结论:
- 拟议的以人为中心的XAI方法提高了用户对AI建议的理解.
- 开发的用户界面有效地支持用户参与和AI系统的透明度.
- 为实施以人为中心的XAI提供了指导方针,以培养更值得信赖的AI.
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