arXiv:2601.21963 · v3
Industrialized Deception: The Collateral Effects of LLM-Generated Misinformation on Digital Ecosystems
摘要
Generative AI and misinformation research have evolved since our 2024 survey. This paper presents an updated perspective, transitioning from literature review to practical countermeasures. We report on changes in the threat landscape, including improved AI-generated content through Large Language Models (LLMs) and multimodal systems - addressing the adverse impacts of AI on information quality. This work focuses on our practical contributions: JudgeGPT, a platform to evaluate human perception of AI-generated news, and RogueGPT, a controlled stimulus generation engine for research. Together, these tools form an experimental pipeline for studying how humans perceive and detect AI-generated misinformation. Our findings show that detection capabilities have improved, but competition between generation and detection continues. We discuss mitigation strategies such as LLM-based detection, inoculation approaches, and the dual-use nature of generative AI.
作者备注：8 pages, 2 figures. Published in the Companion Proceedings of the ACM Web Conference 2026 (WWW Companion '26), pp. 295-302
期刊信息：Companion Proceedings of the ACM Web Conference 2026 (WWW '26 Companion), pp. 295-302