Fostering User Engagement in the Critical Reflection of Arguments

TL;DR

This paper introduces a chatbot system designed to promote unbiased critical reflection during argument exchange by intervening when users are overly focused on their pre-existing beliefs, supported by a user study.

Contribution

It presents a novel model to estimate user reflective engagement and demonstrates its effectiveness in fostering unbiased, critical thinking in dialogue systems.

Findings

Significant increase in user reflection levels.

Reduced user focus on pre-existing opinions.

Validated intervention mechanism effectiveness.

Abstract

A natural way to resolve different points of view and form opinions is through exchanging arguments and knowledge. Facing the vast amount of available information on the internet, people tend to focus on information consistent with their beliefs. Especially when the issue is controversial, information is often selected that does not challenge one's beliefs. To support a fair and unbiased opinion-building process, we propose a chatbot system that engages in a deliberative dialogue with a human. In contrast to persuasive systems, the envisioned chatbot aims to provide a diverse and representative overview - embedded in a conversation with the user. To account for a reflective and unbiased exploration of the topic, we enable the system to intervene if the user is too focused on their pre-existing opinion. Therefore we propose a model to estimate the users' reflective engagement (RUE), defined as their critical thinking and open-mindedness. We report on a user study with 58 participants to test our model and the effect of the intervention mechanism, discuss the implications of the results, and present perspectives for future work. The results show a significant effect on both user reflection and total user focus, proving our proposed approach's validity.