Evaluating an Automated Mediator for Joint Narratives in a Conflict Situation
Massimo Zancanaro, Oliviero Stock, Gianluca Schiavo, Alessandro, Cappelletti, Sebastian Gehrmann, Daphna Canetti, Ohad Shaked, Shani Fachter,, Rachel Yifat, Ravit Mimran, Patrice L. (Tamar) Weiss

TL;DR
This paper introduces an automated mediator system designed to facilitate joint narratives in conflict resolution, showing it can match human mediators in supporting positive social interactions.
Contribution
It presents a novel automated mediator with a cognitive tutor for conflict-related storytelling, demonstrating comparable effectiveness to trained human mediators.
Findings
Automated mediator supports conflict resolution effectively.
System achieves outcomes similar to human mediators.
Automated approach enables remote, language-inclusive interactions.
Abstract
Joint narratives are often used in the context of reconciliation interventions for people in social conflict situations, which arise, for example, due to ethnic or religious differences. The interventions aim to encourage a change in attitudes of the participants towards each other. Typically, a human mediator is fundamental for achieving a successful intervention. In this work, we present an automated approach to support remote interactions between pairs of participants as they contribute to a shared story in their own language. A key component is an automated cognitive tutor that guides the participants through a controlled escalation/de-escalation process during the development of a joint narrative. We performed a controlled study comparing a trained human mediator to the automated mediator. The results demonstrate that an automated mediator, although simple at this stage,…
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