Biased by Design: Leveraging AI Biases to Enhance Critical Thinking of News Readers
Zavolokina, Liudmila, Sprenkamp, Kilian, Katashinskaya, Zoya, Jones, Daniel Gordon
–arXiv.org Artificial Intelligence
This paper explores the design of a propaganda detection tool using Large Language Models (LLMs). Acknowledging the inherent biases in AI models, especially in political contexts, we investigate how these biases might be leveraged to enhance critical think ing in news consumption. Countering the typical view of AI biases as detrimental, our research proposes strategies of user choice and personalization in response to a user's political stance, applying psychological concepts of confirmation bias and cogniti ve dissonance.
arXiv.org Artificial Intelligence
Dec-1-2025
- Country:
- Asia
- Japan > Honshū
- Kantō > Kanagawa Prefecture > Yokohama (0.04)
- Middle East > Jordan
- Amman Governorate > Amman (0.06)
- Japan > Honshū
- Europe
- North America > United States
- New York > New York County > New York City (0.04)
- Asia
- Genre:
- Questionnaire & Opinion Survey (0.93)
- Research Report
- Experimental Study (0.68)
- New Finding (1.00)
- Industry:
- Education > Educational Setting (0.46)
- Media > News (0.68)
- Technology: