ArguMentor: Augmenting User Experiences with Counter-Perspectives
- URL: http://arxiv.org/abs/2406.02795v2
- Date: Thu, 13 Jun 2024 12:33:58 GMT
- Title: ArguMentor: Augmenting User Experiences with Counter-Perspectives
- Authors: Priya Pitre, Kurt Luther,
- Abstract summary: We designed ArguMentor, a human-AI collaboration system that highlights claims in opinion pieces.
It identifies counter-arguments for them using a LLM and generates a context-based summary of based on current events.
Our evaluation shows that participants can generate more arguments and counter-arguments and have, on average, have more moderate views after engaging with the system.
- Score: 4.84187718353576
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: Opinion pieces (or op-eds) can provide valuable perspectives, but they often represent only one side of a story, which can make readers susceptible to confirmation bias and echo chambers. Exposure to different perspectives can help readers overcome these obstacles and form more robust, nuanced views on important societal issues. We designed ArguMentor, a human-AI collaboration system that highlights claims in opinion pieces, identifies counter-arguments for them using a LLM, and generates a context-based summary of based on current events. It further enhances user understanding through additional features like a Q&A bot (that answers user questions pertaining to the text), DebateMe (an agent that users can argue any side of the piece with) and highlighting (where users can highlight a word or passage to get its definition or context). Our evaluation shows that participants can generate more arguments and counter-arguments and have, on average, have more moderate views after engaging with the system.
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