Mitigating Political Bias in AI-Generated News: A Comprehensive Analysis of NLP and Algorithmic Strategies - Sun, Yiming; Lin, Zhuoer (International Journal of Social Sciences and Public Administration, 2024)
The application of artificial intelligence technology in news production is becoming more and more widespread, and this paper investigates the problem of political bias in AI-generated news. Through the comprehensive use of natural language processing, machine learning and quantitative analysis, the news generated by different AI models at home and abroad are systematically detected and evaluated to quantify their political tendencies, and the political bias exhibited by different models in news generation and its specific forms are analysed. A set of solutions to reduce bias is ultimately proposed, with improvements in terms of dataset construction, algorithm design, transparency and accountability mechanisms, supervision and integration of multiple values, aiming to enhance the fairness and objectivity of AI-generated news.