Removing AI's sentiment manipulation of personalized news delivery
发布时间：2022-12-20
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- DOI码：
- 10.1057/s41599-022-01473-1
- 发表刊物：
- [Nature] Humanities & Social Sciences Communications
- 摘要：
- Artificial intelligence (AI) is empowering personalized online news delivery to accommodate people’s information needs and combat information overload. However, AI models learned from user data are inheriting and amplifying some underlying human prejudice such as the sentiment bias of news reading, which may lead to potential negative societal effects and ethical concerns. Here, substantial evidence shows that AI is manipulating the sentiment orientation of news displayed to users by promoting the presence chance of negative news, even if there is no human interference. To mitigate this manipulation, a sentiment-debiasing method based on a decomposed adversarial learning framework is proposed, which can reduce 97.3% of sentiment bias with only 2.9% accuracy sacrifice. Our work provides the potential in improving AI’s responsibility in many human-centered applications such as online journalism and information spread.
- 合写作者：
- Tao Qi,Wei-Qiang Zhang,Xing Xie
- 第一作者：
- Chuhan Wu
- 论文类型：
- 期刊论文
- 通讯作者：
- Fangzhao Wu,Yongfeng Huang
- 是否译文：
- 否
- 发表时间：
- 2022-12-20