AI-powered digital arbitration framework leveraging smart contracts and electronic evidence authentication

The rapid digitization of commercial, governmental, and legal transactions has created an urgent need for efficient, secure, and transparent dispute resolution mechanisms. Traditional arbitration systems often fall short when handling the complexity and volume of digital evidence, smart contracts, and cross-border interactions. This study proposes a novel AI-powered digital arbitration framework that integrates smart contracts, blockchain-based evidence authentication, and explainable artificial intelligence (AI) to automate and modernize the arbitration process. The framework comprises three core layers: (i) a smart contract-based agreement layer that encodes legal terms and self-executing arbitration clauses; (ii) a blockchain-based evidence management layer that ensures the integrity, authenticity, and traceability of submitted evidence; and (iii) an AI-based arbitration engine that classifies, interprets, and evaluates evidence using transformer and LSTM models, supported by SHAP and LIME for interpretability. A controlled experimental setup was implemented using Ethereum and Hyperledger Fabric testnets, with AI models trained on 1,200 annotated arbitration cases. Results demonstrate a 99.5% reduction in arbitration time, a 92.4% agreement rate between AI and expert rulings, and a 99% accuracy in tampering detection. Furthermore, 87.3% of AI-generated decisions were rated as interpretable and acceptable by legal experts. These findings confirm the system's ability to deliver fast, accurate, and explainable arbitration decisions while complying with legal standards. This research contributes a foundational blueprint for deploying autonomous arbitration systems in digital governance, offering scalable solutions for future applications in smart contracts, e-commerce disputes, and algorithmic legal infrastructure.