了解对生成人工智能技术的接受和抵抗:一个整合功能,风险和社会法律因素的多理论框架
1Hult International Business School, San Francisco, CA, United States.
Frontiers in artificial intelligence
|May 13, 2025
概括
这项研究揭示了功能因素促进生成性AI接受,而风险增加了抵抗力. 社会法律因素调解了这些影响,这对于负责地将人工智能纳入高等教育至关重要.
科学领域:
- 人工智能的人工智能
- 人与计算机的交互
- 技术社会学技术的社会学.
背景情况:
- 生成型人工智能采用面临的挑战是由于用户的接受和抵抗.
- 现有的研究往往孤立地检查因素,缺乏综合的理论观点.
研究的目的:
- 调查影响大学生接受和抵制生成性AI的因素.
- 整合技术接受模型 (TAM),保护动机理论 (PMT) 和社会交换理论 (SET) 以全面理解.
主要方法:
- 一项结构化调查收集了407名大学生的数据.
- 结构方程建模 (SEM) 分析了功能,风险和社会法律因素对用户态度的影响.
主要成果:
- 功能因素 (实用性,易用性,可靠性) 积极影响了接受度和降低了阻力.
- 风险因素 (隐私,安全,伦理) 增加了抵抗力,减少了接受力.
- 社会法律因素 (治理,监管信任) 起到了关键的调解作用.
结论:
- 一个综合的理论框架为AI采用动态提供了更深入的见解.
- 研究结果强调需要解决风险并利用功能性感知来有效地整合人工智能.
- 为在高等教育中负责任地采用人工智能提供了政策和实践建议.
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