多利益相关者对负责任的人工智能和教育中的可接受性的观点
Alexander John Karran1, Patrick Charland2, Joé Trempe-Martineau3
1HEC Montréal, Montréal, Québec, Canada. alexander-john.karran@hec.ca.
NPJ science of learning
|July 8, 2025
概括
这项研究调查了学生,教师和家长在教育中接受人工智能 (AI) 的情况. 调查结果显示,人工智能的接受和信任在各种利益相关者群体和人工智能应用中存在显著差异.
科学领域:
- 教育技术的教育技术
- 人工智能伦理学 人工智能伦理学
- 人与计算机的交互
背景情况:
- 人工智能 (AI) 在教育中具有变革性的潜力,需要对其接受进行调查.
- 对数据隐私,人工智能代理,透明度,可解释性和道德部署的担忧是教育环境中人工智能采用的关键障碍.
- 了解多方利益相关者的观点 (学生,教师,家长) 对于有效的AI集成至关重要.
研究的目的:
- 从学生,教师和家长的角度探索教育中各种AI应用的可接受性.
- 识别和分析影响教育环境中人工智能接受的关键问题和障碍.
- 评估人工智能代理,透明度,可解释性和隐私方面的变化如何影响用户的看法和意图.
主要方法:
- 采用了四种不同的AI场景,呈现四种不同的AI场景,具有操纵的属性 (代理,透明度,可解释性,隐私).
- 从1198名参与者收集数据,包括学生,教师和家长,通过调查评估对AI实用性,有用性,正义,信心,风险和使用意向的看法.
- 利用调解分析来检查AI特征,用户感知和整体接受之间的关系.
主要成果:
- 人工智能接受度和信任度在不同利益相关者群体 (学生,教师,家长) 中表现出显著的变化.
- 人工智能的全球实用性,个人实用性,正义,信心和风险的感知受到场景中操纵的人工智能的特征的影响.
- 使用人工智能的意图因利益相关者群体和提出的特定人工智能应用而有很大差异.
结论:
- 利益相关者的观点对教育中人工智能的接受产生了批判性的影响.
- 解决与人工智能代理,透明度,可解释性和数据隐私相关的问题对于促进信任和采用至关重要.
- 将人工智能应用程序和沟通策略定制为不同的教育利益相关者,可以提高整体接受度和有效实施.
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