FairCourt: A System to Evaluate Fairness in Legal Judgments
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Date
2026
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Publisher
New Horizon College of Engineering
Abstract
The Indian judiciary, though constitutionally mandated to uphold justice and equality, faces critical challenges that undermine its effectiveness and credibility. These include inconsistent judicial interpretations, prolonged delays due to case backlogs, and growing concerns over biases related to caste, religion, gender, and socioeconomic status. Additionally, the lack of transparency in judicial appointments and perceived instances of corruption have contributed to a decline in public trust. To address these systemic issues, there is a pressing need for a data-driven, transparent, and scalable solution that can objectively evaluate the fairness of court judgments. FairCourt is an Al-powered framework designed to assess judicial fairness using advanced Natural Language Processing (NLP), fairness metrics, and explainable Al. The system architecture consists of six core modules: data acquisition from public legal platforms such as Indian Kanoon, NJDG, and eCourts, preprocessing to clean and structure unstructured legal texts, semantic analysis using transformer-based models like BERT and LegalBERT; fairness assessment through metrics like statistical parity and equality of opportunity; explainability using tools such as SHAP and LIME to provide interpretable justifications, and a dashboard to visualize fairness trends across judges, regions, and case types. By identifying patterns of bias and inconsistency in judgments, FairCourt aims to promote judicial accountability, improve public trust, and support policy reforms. Aligned with Sustainable Development Goal 16, the project advances the rule of law, reduces bias and corruption, and supports the development of transparent and inclusive judicial institutions