Chatbots to strengthen democracy: An interdisciplinary seminar to train identifying argumentation techniques of science denial
Ingo Siegert, Jan Nehring, Aranxa M\'arquez Ampudia, Matthias Busch, Stefan Hillmann

TL;DR
This paper proposes an interdisciplinary seminar where students develop AI chatbots using Large Language Models to identify science denial techniques, aiming to enhance critical engagement and resilience against misinformation.
Contribution
It introduces a novel educational approach employing LLM-based chatbots to train users in recognizing and understanding science denial arguments.
Findings
Development of AI chatbots simulating science denial
Evaluation of chatbot effectiveness in educational settings
Feasibility of using LLMs for argumentation training
Abstract
In recent times, discussions on social media platforms have increasingly come under scrutiny due to the proliferation of science denial and fake news. Traditional solutions, such as regulatory actions, have been implemented to mitigate the spread of misinformation; however, these measures alone are not sufficient. To complement these efforts, educational approaches are becoming essential in empowering users to critically engage with misinformation. Conversation training, through serious games or personalized methods, has emerged as a promising strategy to help users handle science denial and toxic conversation tactics. This paper suggests an interdisciplinary seminar to explore the suitability of Large Language Models (LLMs) acting as a persona of a science denier to support people in identifying misinformation and improving resilience against toxic interactions. In the seminar, groups…
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Taxonomy
TopicsMisinformation and Its Impacts · AI in Service Interactions · Artificial Intelligence in Healthcare and Education
