Affirmative Large Language Model-Based Dialogue Robots for Broadening or Deepening the Perspective of Children
摘要
This study aims to establish a method for designing dialogue robots that can broaden or deepen the perspectives of children. Previous research has suggested that artificial intelligence (AI) can broaden or deepen perspectives by facilitating critical dialogues. Critical thinking emphasizes not only counterarguments, but also appropriate evaluations and affirmations. However, the development and validation of AI and robots that consider this aspect has been insufficient. Therefore, this study hypothesizes that robots that affirm the opinions of children while presenting new perspectives can broaden or deepen their viewpoints. We introduced dialogue robots in primary school science classes to verify this hypothesis. Both subjective evaluations by the children and objective evaluations by third parties confirmed that the proposed approach promotes broadening or deepening the perspectives of children and improves the impression of the robot (anthropomorphism, likeability, and perceived intelligence). Furthermore, we found that, through the medium of likeability, the subjective evaluation of broadening or deepening the perspective is enhanced, and also the objective evaluation might be improved. This study provides valuable insight into the design of dialogue robots that can broaden or deepen the perspective of children.