The role of artificial intelligence in news portal fact-checking systems

This article examines the application of artificial intelligence within the fact-checking systems of news portals. Its relevance stems from the rising volume of misinformation in digital environments and the limited capacity of manual verification. The novelty of the study lies in a comprehensive analysis of contemporary AI tools that not only isolate cl AI ms for verification but also perform multi-agent source retrieval—ensuring verdict transparency through citation of original data. The paper describes mechanisms for initial text analysis, corroboration searches, and detection of visual forgeries, and reviews implementation examples in the editorial workflows of Der Spiegel, FullFact, and Maldita [Der Spiegel; FullFact; Maldita]. Methods for assessing veracity using language models and computer-vision algorithms are explored, with special attention to model hallucination risks and the need for expl AI nable decisions. The study’s objective is to identify AI ’s potential for optimizing fact-checking processes and to develop recommendations for integrating these solutions into editorial practices. To achieve this, the authors employ comparative analysis, data systematization, and a survey of empirical case studies. The work builds on a comparative juxtaposition of empirical practices and theoretical models presented in the international literature. Artificial intelligence automates fact extraction, evidence retrieval, and multimodal verification to accelerate the fact-checking workflow on news platforms.