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.

为支持公平且无偏见的意见建立过程，我们提出了一种与人类进行审议对话的聊天机器人系统。与说服性系统相反，这个聊天机器人旨在提供多样且代表性的概述——嵌入在与用户的对话中。为了实现对话中用户的反思和无偏见的探索，我们使系统能够在用户过于专注于他们已有意见时进行干预。因此，我们提出了一个估计用户反思参与的模型（RUE），该模型被定义为用户的批判性思维和开放性思维。我们报告了一项涉及58名参与者的用户研究，以测试我们的模型和干预机制的影响，讨论结果的影响，并提出未来工作的展望。结果表明，我们提出的方法在用户反思和总体用户关注度方面具有显著效果，证明了该方法的有效性。

促进用户在批判性论证反思中的参与