人类培训数据 (HTD) 对人工智能 (AI) 技术购买意向的影响解释
Stephanie Kwari Dharmaputri1, Greg Nyilasy1, Anish Nagpal1
1Department of Management and Marketing, University of Melbourne, Melbourne, Victoria, Australia.
PloS one
|February 2, 2026
概括
解释人类如何训练人工智能系统,通过使人工智能看起来更人性化,增加了消费者购买意图. 然而,对于已经信任人工智能技术的消费者来说,这种影响可能不那么明显.
科学领域:
- 消费者心理学 消费者心理学
- 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:
- 消费者对人工智能 (AI) 的抵抗很普遍,通常源于对AI缺乏人类品质的看法.
- 现有的研究突出了如何弥合这一消费者对人工智能采用信任赤字的理解上的差距.
- 基于源代码的可解释AI (XAI) 通过澄清AI系统的起源和过程,提供了潜在的解决方案.
研究的目的:
- 研究人类培训数据 (HTD) 解释对消费者购买人工智能技术的意图的影响.
- 探索在HTD解释和购买意图之间的关系中,感知到人类本质转移的调解作用.
- 检查对人工智能的预先存在的信任对HTD解释的有效性的潜在缓解影响.
主要方法:
- 定义的HTD解释是对人工智能培训数据中人类参与的简单描述.
- 进行了四次主体间实验,以测试有关HTD解释,购买意图和调解的假设.
- 利用统计分析来检查主要影响,调解和适度.
主要成果:
- 研究1证实了HTD解释对消费者购买意向的主要积极影响.
- 研究2和研究3提供了证据,证明感知到人类本质转移的调解作用.
- 研究4表明,HTD解释可能会降低对人工智能的高预先信任度的消费者采用意图.
结论:
- HTD解释作为一个可行的基于源代码的XAI策略,以提高消费者对AI技术的接受度.
- 将HTD解释与消费者结果联系在一起的心理机制是复杂的,需要进一步研究.
- 研究结果表明,基于消费者信任水平,人性化效应 (PET和深度人性化) 可能存在细微差别.
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