THE ROLE OF AI IN COMBATING MISINFORMATION

ABSTRACT The rapid proliferation of misinformation in the digital age has emerged as a critical threat to public health, democratic processes, and societal cohesion. With the exponential growth of online content across social media platforms, news websites, and forums, traditional methods of misinformation detection have proven inadequate. Artificial Intelligence (AI) offers promising solutions through advanced Natural Language Processing (NLP), computer vision, and network analysis techniques that enable scalable and efficient identification of false narratives. This study investigates the role of AI in detecting, analyzing, and countering misinformation, with a focus on text-based classification using transformer models such as BERT and RoBERTa. A mixed-methods research design was adopted, combining a comprehensive literature review, case studies of real-world AI implementations (e.g., Facebook’s fact-checking program, Google’s Fact Check Explorer), and experimental analysis using the LIAR dataset. The proposed system architecture outlines a multi-layered approach involving data ingestion, preprocessing, AI modeling, fact-checking integration, and user feedback mechanisms. Performance evaluation of the fine-tuned NLP models demonstrated their effectiveness in classifying political statements into truthfulness categories, although challenges such as contextual understanding, model bias, and adversarial tactics were identified. Ethical considerations, including fairness, transparency, and privacy, were emphasized throughout the research to ensure responsible deployment of AI systems. The findings highlight that while AI significantly enhances misinformation detection capabilities, it is most effective when integrated with human oversight, continuous learning, and robust ethical frameworks. Recommendations include fostering human-AI collaboration, investing in diverse training datasets, promoting explainable AI, and enhancing digital literacy among users. Ultimately, this research contributes to the growing body of knowledge on AI-driven misinformation mitigation and provides actionable insights for developers, platform operators, and policymakers seeking to preserve the integrity of digital information ecosystems.