AIGC标签对用户对自动化新闻的看法的影响:来自EEG的证据
Yuhan Liu1,2, Shuining Wang1,2, Guoming Yu1,2,3
1School of Journalism and Communication, Beijing Normal University, Beijing, China.
Frontiers in psychology
|January 8, 2024
概括
人工智能产生的内容 (AIGC) 标签线索降低了新闻的可信度,但增加了认知处理. 当AIGC标签存在时,用户被推动更深入地审查信息质量,影响AI新闻感知.
科学领域:
- 人与计算机的交互
- 媒体心理学 媒体心理学
- 认知科学 认知科学
背景情况:
- 生成性人工智能越来越多地用于新闻制作,这引发了关于它对观众感知的影响的问题.
- 刺激理论为理解微妙的线索,如标签,如何影响用户行为和判断提供了一个框架.
- 了解用户对人工智能生成内容 (AIGC) 的反应对于导航不断变化的媒体环境至关重要.
研究的目的:
- 调查AI生成内容 (AIGC) 标签线索对用户对自动化新闻的看法的影响.
- 检查标签如何影响感知可信度和认知处理,使用nudge理论.
- 探索AIGC标签对描述性和评估性新闻的影响的差异.
主要方法:
- 一个主体内部实验,具有2 (作者身份披露提示:有或没有AIGC标签) ×2 (自动化新闻类型:描述性或评估性新闻) 的设计.
- 32名参与者评估了自动新闻的可信度,并进行了EEG记录.
- 脑电图数据分析了与任务相关活动 (TAR) 一起的三角,三角,α和β频段的功率光谱密度 (PSD).
主要成果:
- 披露AIGC标签显著降低了对描述性和评估性新闻的可信度.
- 脑电图数据显示,AIGC标签披露的delta,theta,alpha和betaPSD显著更高,与没有披露的相比.
- 在描述性新闻条件下,TAR在AIGC标签下更高,表明认知处理增加.
结论:
- 虽然AIGC标签线索降低了可信度,但却增强了注意力集中和认知处理.
- 用户被AIGC标签推动分配更多的认知资源,以重新评估信息质量以进行审慎判断.
- 结果提供了对透明披露推动的理论见解,以及人工智能时代内容监管的实际指导.
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