AI-Enabled Restorative Justice: Reconstructing Mediation Systems through Algorithmic Facilitation and Digital Governance

This paper examines the integration of artificial intelligence into restorative justice practices, focusing on the development of innovative mediation systems supported by algorithmic technologies. It argues that AI has the potential to transform traditional dispute resolution mechanisms by enhancing efficiency, accessibility, and data-driven facilitation. However, the study highlights that the use of AI in mediation processes raises complex legal and ethical challenges, particularly regarding fairness, neutrality, transparency, and the preservation of human-centered justice values. It critically analyzes the extent to which algorithmic systems can support or influence negotiation dynamics and conflict resolution outcomes. Adopting a legal-analytical approach, the research proposes a hybrid model of AI-assisted restorative justice, combining technological facilitation with human oversight and procedural safeguards. The model is grounded in principles of explainability, accountability, and participatory justice. The paper contributes to Legal Tech scholarship by bridging restorative justice theory with AI governance, offering a forward-looking framework for designing mediation systems that align innovation with fundamental legal and ethical standards.