用户通过越狱暴露社交机器人，以非暴力方式遏制虚假信息传播。
Ignore All Previous Instructions: Jailbreaking as a de-escalatory peace building practise to resist LLM social media bots
- 用户主动越狱可疑AI账号，揭露其自动化行为
- 实证显示越狱可有效打断误导性叙事的传播链条
- 为对抗平台滥用提供草根级非暴力解决方案
大型语言模型加剧了社交媒体上政治话语的规模与策略性操控，导致冲突升级。现有研究多聚焦于平台主导的治理措施。本文提出一种以用户为中心的视角，将‘越狱’视为一种新兴的非暴力去激进化实践。在线用户通过与疑似由大语言模型驱动的账号互动，绕过其安全防护机制，暴露其自动化行为，从而破坏误导性叙事的传播路径。
原文摘要 · Abstract (English)
Large Language Models have intensified the scale and strategic manipulation of political discourse on social media, leading to conflict escalation. The existing literature largely focuses on platform-led moderation as a countermeasure. In this paper, we propose a user-centric view of "jailbreaking" as an emergent, non-violent de-escalation practice. Online users engage with suspected LLM-powered accounts to circumvent large language model safeguards, exposing automated behaviour and disrupting the circulation of misleading narratives.
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