🤖 AI Summary
This study systematically examines the dual role of generative AI across the entire disinformation lifecycle—creation, dissemination, and detection. Motivated by rapid 2024-era advances, it employs a structured literature review to synthesize state-of-the-art developments in large language models, multimodal generation, social media diffusion analytics, AI-driven detection frameworks, and deepfake synthesis and forensics. The work uniquely integrates five thematic domains to clarify how generative AI enables scalable, personalized disinformation while delineating associated risk boundaries; concurrently, it identifies key mechanisms driving improved detection performance. Findings confirm generative AI’s inherent “dual-use” nature and pinpoint critical challenges—including cross-modal forgery traceability deficits and insufficient generalizability of detection models. The study proposes an interdisciplinary response strategy integrating technical governance, platform accountability, and policy coordination, thereby providing a systematic foundation for robust defense architectures and evidence-informed regulatory design. (149 words)
📝 Abstract
Fake news significantly influence our society. They impact consumers, voters, and many other societal groups. While Fake News exist for a centuries, Generative AI brings fake news on a new level. It is now possible to automate the creation of masses of high-quality individually targeted Fake News. On the other end, Generative AI can also help detecting Fake News. Both fields are young but developing fast. This survey provides a comprehensive examination of the research and practical use of Generative AI for Fake News detection and creation in 2024. Following the Structured Literature Survey approach, the paper synthesizes current results in the following topic clusters 1) enabling technologies, 2) creation of Fake News, 3) case study social media as most relevant distribution channel, 4) detection of Fake News, and 5) deepfakes as upcoming technology. The article also identifies current challenges and open issues.