Mitigation Strategies for Misinformation in AI-Generated Content

Abstract

Artificial Intelligence (AI) has significantly transformed the way information is generated and disseminated. While AI-powered content generation has enabled efficiency and scalability, it has also introduced a substantial risk of misinformation. This paper explores various mitigation strategies to combat misinformation in AI-generated content, focusing on technical, regulatory, and educational measures. We analyze the mechanisms through which AI models generate and propagate misinformation, the consequences of such misinformation on individuals and society, and the effectiveness of different mitigation techniques. The paper presents an experimental analysis of filtering mechanisms and bias reduction strategies to assess their efficacy in reducing misinformation. The results indicate that a combination of robust data verification, model fine-tuning, and user awareness campaigns can significantly reduce misinformation risks. This research contributes to the growing discourse on ethical AI use and offers actionable insights for policymakers, developers, and users.