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Alexander Loth
Alexander Loth
@xlth@mastodon.social  路  activity timestamp 15 hours ago

Our paper "Industrialized Deception: The Collateral Effects of LLM-Generated Misinformation on Digital Ecosystems" has been accepted at ACM TheWebConf '26 (WWW '26)! 馃帀

We built JudgeGPT and RogueGPT to study how well people can spot AI-generated news. Spoiler: it's harder than you'd think.

Paper: https://arxiv.org/abs/2601.21963
Code: https://github.com/aloth/JudgeGPT

#WWW2026 #misinformation #GenAI #LLM #AcademicMastodon

GitHub

GitHub - aloth/JudgeGPT: JudgeGPT: An empirical research platform for evaluating the authenticity of AI-generated news. (arXiv:2601.21963 and arXiv:2601.22871)

JudgeGPT: An empirical research platform for evaluating the authenticity of AI-generated news. (arXiv:2601.21963 and arXiv:2601.22871) - aloth/JudgeGPT
arXiv.org

Industrialized Deception: The Collateral Effects of LLM-Generated Misinformation on Digital Ecosystems

Generative AI and misinformation research has 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. Central to this work are our practical contributions: JudgeGPT, a platform for evaluating 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 the competition between generation and detection continues. We discuss mitigation strategies including LLM-based detection, inoculation approaches, and the dual-use nature of generative AI. This work contributes to research addressing the adverse impacts of AI on information quality.
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