Train Yourself as an LLM: Exploring Effects of AI Literacy on Persuasion via Role-playing LLM Training
Qihui Fan, Min Ge, Chenyan Jia, Weiyan Shi

TL;DR
This paper introduces LLMimic, a role-playing AI literacy tutorial that enhances understanding of AI persuasion, reduces susceptibility to AI influence, and promotes responsible AI interaction through an interactive, gamified approach.
Contribution
The study presents LLMimic, a novel role-play-based AI literacy tool that effectively improves AI literacy and reduces persuasion success in various scenarios.
Findings
LLMimic significantly increased participants' AI literacy ($p < .001$).
It reduced persuasion success across scenarios ($p < .05$).
It improved truthfulness and social responsibility in the hotel scenario ($p<0.01$).
Abstract
As large language models (LLMs) become increasingly persuasive, there is concern that people's opinions and decisions may be influenced across various contexts at scale. Prior mitigation (e.g., AI detectors and disclaimers) largely treats people as passive recipients of AI-generated information. To provide a more proactive intervention against persuasive AI, we introduce , a role-play-based, interactive, gamified AI literacy tutorial, where participants assume the role of an LLM and progress through three key stages of the training pipeline (pretraining, SFT, and RLHF). We conducted a between-subjects study () where participants either (1) watched an AI history video (control) or (2) interacted with LLMimic (treatment), and then engaged in one of three realistic AI persuasion scenarios: (a) charity donation persuasion, (b) malicious money…
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