通过一种说服知识镜头来评估AI接收能力
Jared Watson1, Francesca Valsesia2, Shoshana Segal1
1Department of Marketing, Leonard N. Stern School of Business, New York University, New York, NY, USA.
Current opinion in psychology
|July 6, 2024
概括
这项研究将人工智能 (AI) 视为一种说服剂,检查影响AI接受和厌恶的因素. 研究探讨人工智能特性,用户特征和交互背景,以指导未来的人类-人工智能研究.
科学领域:
- 人与计算机的交互
- 人工智能研究 人工智能研究
- 说服科学是说服的科学.
背景情况:
- 人与人工智能的互动是一个快速扩展的研究领域.
- 现有的文献缺乏统一的框架来理解人工智能的接受和厌恶.
- 将人工智能概念化为一种说服剂提供了一个新的视角.
研究的目的:
- 审查和综合当前关于人与人工智能相互作用的研究.
- 通过说服知识的镜头来分析AI接受和厌恶.
- 确定影响用户与人工智能系统交互的关键因素.
主要方法:
- 对人与人工智能相互作用研究的系统文献综述.
- 人工智能作为一种说服力代理的概念化.
- 研究结果的分类基于AI属性,用户特征和交互背景.
主要成果:
- 人工智能接受和厌恶受到人工智能属性 (例如,人类形象,可用性) 的影响.
- 用户判断和任务执行的个体差异会影响人工智能交互.
- 背景因素,包括决策类型和领域,显著塑造AI参与.
结论:
- 一个说服知识框架为人类-AI动态提供了有价值的见解.
- 了解人工智能作为一种说服力代理可以解释用户的接受和拒绝.
- 未来的研究应该进一步探索这些因素,以优化人类-人工智能合作.
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