Enhancing online dispute resolution through natural language processing: a case study of kleros
摘要
The growing significance of Online Dispute Resolution (ODR) lies in its capacity to provide efficient, accessible, and cost-effective solutions for resolving disputes outside traditional courtrooms. This study focuses on enhancing the functionality of Kleros, an innovative ODR platform, by integrating Natural Language Processing (NLP). Kleros faces challenges such as procedural inefficiencies, user comprehension difficulties, and the interpretation of complex legal terms, which hinder its broader adoption. By leveraging NLP, this paper proposes solutions to automate case analysis, simplify legal jargon, provide contextual explanations, and enhance the interpretation of user intent. These improvements aim to make the dispute resolution process more efficient and accessible for all parties involved. The findings highlight how NLP-driven enhancements can streamline ODR processes, improve juror experiences, and expand Kleros’ applicability to a broader range of disputes.