人工智能与人类筹款者:证据表明叙事视角和筹款者的身份影响捐赠意图
Huarong Liu1, Qilong Li1, Yumeng Sun1
1Department of Psychology, Renmin University of China, Beijing, China.
Cyberpsychology, behavior and social networking
|October 25, 2025
概括
人工智能 (AI) 筹款从第一人称叙事中受益,而人类筹款者在第三人称故事中表现更好. 同理心的关注驱动了这些捐赠意图的差异.
科学领域:
- 人与计算机的互动.
- 营销 营销 营销 营销 营销 营销
- 心理学 心理学 心理学
背景情况:
- 人工智能 (AI) 越来越多地用于慈善筹款,挑战传统理论.
- 在筹款中,叙事视角 (第一人称与第三人称) 的有效性对于人类筹款者来说已经有充分的证据,但对于人工智能来说尚未被探索.
研究的目的:
- 调查叙事视角和筹款人身份 (人工智能与人类) 在捐赠意图之间的相互作用.
- 了解同情关心在调解这些影响中的作用.
- 确定这些叙事策略的边界条件,例如寻求帮助者的识别能力.
主要方法:
- 通过应用叙事传输理论 (NTT) 进行了三项研究.
- 参与者的捐赠意图被测量为对人工智能和人类筹款者的回应,使用第一人称和第三人称叙述.
- 对同情的关注和寻求帮助者的识别能力被评估为调解和调节变量.
主要成果:
- 研究1:人工智能筹款者在第一人称叙述中更有效,而人类筹款者在第三人称叙述中更有效.
- 研究2:同情的关注调解了效果,叙事视角影响了同情,这反过来又影响了捐赠意图.
- 研究3:当寻求帮助者的身份模糊时,特定叙事视角的优势消失了.
结论:
- 非营利组织可以通过使用第一人称叙述和使用第三人称叙述的人类筹款来优化人工智能筹款.
- 感同情的关注是关键的机制,将叙事视角,筹款人身份和捐赠意图联系起来.
- 寻求帮助者的可识别性是影响人工智能和人为主导的筹款中不同叙事策略有效性的关键因素.
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