用AI教普通人识别逻辑谬误，提升抗骗力
Tackling the Root of Misinformation by Teaching Laypeople about Logical Fallacies via Socratic Questioning and Critical Argumentation
- 通过苏格拉底式提问引导反思，培养批判性思维
- 实验证明该系统比普通AI更有效识别谬误
- 适合想提升逻辑分析能力的普通用户
识别日常对话中的逻辑谬误对许多人来说具有挑战性，这一问题在大语言模型（LLMs）时代尤为突出，因为恶意实体可利用谬误论据大规模传播虚假信息。本文提出LFTutor——一种基于LLM的智能辅导系统，通过意图驱动的苏格拉底式提问和批判性论证原则，主动引导非专业学习者反思自身推理过程。经自动评估与人工评估验证，该系统显著优于缺乏教学策略的基线LLM。本研究展示了将大模型与教育支架结合，在人工智能时代提升公众批判性思维与论辩素养的巨大潜力。
原文摘要 · Abstract (English)
Identifying logical fallacies in everyday discourse is challenging for many people. This challenge is amplified in the era of Large Language Models (LLMs), where malicious agents can deploy fallacious arguments to disseminate misinformation at scale. In this work, we explore the potential of LLMs as part of the solution. We introduce LFTutor, an intelligent tutoring system which uses LLMs to tutor laypeople and help them learn about logical fallacies. LFTutor integrates intent-driven Socratic questioning and critical argumentation principles to actively engage learners to reflect on their reasoning. Through both automatic and human evaluations, we demonstrate that LFTutor significantly outperforms baseline LLMs lacking these pedagogical strategies. This work highlights the promise of combining LLMs with pedagogical scaffolding to foster critical thinking and argument literacy in the age of AI.
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