Human-AI Interaction for Augmented Reasoning: Improving Human Reflective and Critical Thinking with Artificial Intelligence
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3706599.3706719.pdf
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Author(s) • • • • • • • •
Danry, Valdemar
Pataranutaporn, Pat
Cui, Christopher
Hung, Jui-Tse
Blanchard, Lancelot
Bu?inca, Zana
Tan, Chenhao
Starner, Thad
Maes, Pattie
Date Issued
April 25, 2025
Publisher
ACM|Extended Abstracts of the CHI Conference on Human Factors in Computing Systems
Citation
Valdemar Danry, Pat Pataranutaporn, Christopher Cui, Jui-Tse Hung, Lancelot Blanchard, Zana Buçinca, Chenhao Tan, Thad Starner, and Pattie Maes. 2025. Human-AI Interaction for Augmented Reasoning: Improving Human Reflective and Critical Thinking with Artificial Intelligence. In Proceedings of the Extended Abstracts of the CHI Conference on Human Factors in Computing Systems (CHI EA '25). Association for Computing Machinery, New York, NY, USA, Article 787, 1–6.
Version
Final published version
Abstract
AI-Augmented Reasoning systems are cognitive assistants that support human reasoning by providing AI-based feedback that can help users improve their critical reasoning skills. Made possible with new techniques like argumentation mining, fact-checking, crowdsourcing, attention nudging, and large language models, AI augmented reasoning systems can provide real-time feedback on logical reasoning, help users identify and avoid flawed arguments and misinformation, suggest counter-arguments, provide evidence-based explanations, and foster deeper reflection. The goal of this workshop is to bring together researchers from AI, HCI, cognitive and social science to discuss recent advances in AI-augmented reasoning, to identify open problems in this area, and to cultivate an emerging community on this important topic.
Description
CHI EA ’25, Yokohama, Japan
MIT Department
Massachusetts Institute of Technology. Media Laboratory
Terms of Use
Article is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use.
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DOI of Published Version
https://doi.org/10.1145/3706599.3706719