可解释的人工智能在信任模型中对人类因素的有效性
Justin C Cheung1,2, Shirley S Ho3,4
1Wee Kim Wee School of Communication and Information, Nanyang Technological University, 31 Nanyang Link, Singapore, 637718, Singapore.
Scientific reports
|July 2, 2025
概括
可解释的人工智能沟通增强了公众对人工智能工程师的信任,影响了人们的看法和接受. 这种信任,特别是对人工智能工程师的能力的信任,影响了使用自动驾驶客运无人机的意图.
科学领域:
- 科学沟通科学沟通
- 人与计算机的交互
- 人工智能伦理学 人工智能伦理学
背景情况:
- 可解释性AI (XAI) 通信对于建立对AI系统的信任至关重要.
- 人工智能工程师对人工智能工程师的信任是公众接受人工智能的不足但至关重要的因素.
- 现有研究强调了人工智能信任与公众看法之间的联系.
研究的目的:
- 调查可解释性感知如何影响对AI工程师的信任.
- 检查对人工智能工程师的信任与对人工智能系统的信任之间的关系.
- 确定可解释的AI是否可以提高公众对AI工程师的信任.
主要方法:
- 在新加坡进行了一项公众论调查,共有1002名参与者.
- 用结构方程建模来分析数据.
- 该研究测量了感知可解释性,对人工智能工程师的信任 (能力,仁慈,诚信) 以及对人工智能系统的信任.
主要成果:
- 感知可解释性显著影响了对人工智能工程师信任的所有维度.
- 对人工智能工程师能力的信任积极影响了人们对使用自动驾驶客运无人机的态度和意图.
- 在可解释性感知和使用意图之间确定了涉及对能力和态度的信任的连续调解途径.
结论:
- 可解释的人工智能有效提高对人工智能工程师的信任.
- 对人工智能工程师的信任,特别是他们的能力,在推动像无人机这样的人工智能技术的采用方面发挥着关键作用.
- 这些发现对人工智能开发和科学传播策略具有重要的理论和实践意义.
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