生成型人工智能和错误信息的接受:对预先警告人工智能幻觉效应的实验测试
1Department of Digital Media, Myongji University, Seodaemun-gu, Seoul, Korea.
Cyberpsychology, behavior and social networking
|February 24, 2025
概括
预先警告人们关于人工智能 (AI) 幻觉,其中AI产生不正确的信息,有助于减少对AI错误信息的接受. 这种效应在那些喜欢努力思考的人中更强烈.
科学领域:
- 人工智能的人工智能
- 认知心理学 认知心理学
- 信息科学 信息科学 信息科学
背景情况:
- 生成型人工智能 (AI) 可以产生可信但事实上不正确的陈述,称为AI幻觉.
- 人工智能幻觉对产生和传播错误信息构成重大风险.
- 了解如何减轻人工智能产生的错误信息的接受度至关重要.
研究的目的:
- 调查预先警告人工智能幻觉是否可以减少对人工智能产生的错误信息的接受.
- 检查预警是否会影响真实的AI产生的信息的接受.
- 探索个人差异,特别是对努力思考的偏好,是否会缓和预警的效果.
主要方法:
- 一个在线实验是对208名韩国成年人进行的.
- 参与者接触到有关AI幻觉的信息.
- 这项研究衡量了对错误信息的接受程度和对努力思考的偏好中和作用.
主要成果:
- 对人工智能幻觉的预警显著降低了对人工智能产生的错误信息的接受率 (p = 0.001,科恩的d = 0.45).
- 预先警告没有显著影响真实AI生成信息的接受 (p = 0.91).
- 由于事先警告,错误信息接受度的减少在那些对努力思考的偏好较高的人群中比那些偏好较低的人群更为明显 (p < 0.01).
结论:
- 预警是一种有效的策略,可以打击对人工智能产生的错误信息的接受.
- 预警的有效性在那些从事更有意识的认知处理的人群中尤其显著.
- 这些发现凸显了用户意识和认知风格在导航人工智能生成内容中的重要性.
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