Context: In July 2025, the Kerala High Court issued India’s first policy on the use of Artificial Intelligence (AI) in the district judiciary, highlighting both its potential to tackle the backlog of over 5 crore cases and the risks of errors, bias, and accountability gaps.
Relevance of the Topic: Mains: Use of AI in Judiciary: Promises and Challenges.
AI in Judiciary
The judiciary faces longstanding challenges such as case backlogs, language barriers, and the need for digital modernisation.
- AI in Judiciary including Machine Learning (ML), Natural Language Processing (NLP), Optical Character Recognition (OCR), and Predictive Analytics are being leveraged to automate administrative tasks, improve case tracking, and enhance crime prevention.
- Initiatives like e-Courts Project Phase III, AI-assisted legal translation, predictive policing, and AI-driven legal chatbots are reshaping the legal landscape, making processes faster, smarter, and more transparent.
- The Kerala High Court’s July 2025 guidelines on AI use in district judiciary marked the first official policy in India addressing AI adoption in courts.
Promise of AI in Judiciary:
- Speed and Efficiency:
- Translation of documents into regional languages can help judges and litigants overcome language barriers.
- Automated transcription of oral arguments and witness depositions saves manual effort.
- Defect identification in filings ensures faster case listing and reduces delays.
- Enhanced Legal Research: AI enables quick scanning of vast legal databases, saving time and supporting more focused, substantive legal analysis.
- Improved Accessibility: AI-based tools can simplify judgments into easy-to-read summaries for litigants. Translation features enhance access to justice in regional languages.
- Administrative Support: AI can assist registries in case classification, docket management, and scheduling, helps reduce the burden on court staff and ensures smoother case flow.
- Potential Cost Reduction: By saving time and resources in transcription, research, and filing checks, AI can lower litigation costs, making justice more affordable.
Problems with AI in Judiciary
While AI promises efficiency and accessibility, its deployment in the judiciary raises serious legal, ethical, and technical concerns.
- Translation and Transcription Errors: E.g., “Leave granted” translated as “holiday approved” in Hindi. In Noel Anthony Clarke vs Guardian News & Media Ltd. (2025), the claimant’s name “Noel” was repeatedly transcribed as “no.” Such errors, though small, can distort meaning and impact case outcomes.
- AI Hallucinations: A study published in theJournal of Empirical Legal Studies found that legal Large Language Models (LLM) can make up case laws and cite incorrect sources to substantiate claims. E.g., OpenAI’s Whisper has been reported to “hallucinate” entire phrases or sentences, especially when speakers pause during speech.
- Search Engine Bias: AI-powered legal research may reflect user behaviour patterns, not objective comprehensiveness. Risk of “invisibilising” important precedents, skewing legal arguments and judgments.
- Loss of Human Nuance: Judicial decision-making requires context, empathy, and balancing of equities. Over-reliance on AI risks reducing adjudication to mechanical rule-based inferences.
- Data Privacy and Security: Use of sensitive, non-public, or personal data in AI systems lacks a clear framework. Risk of data leaks, misuse, or surveillance by private vendors supplying AI tools.
- Infrastructure Deficits: Many courts in India still rely heavily on paper-based processes. Weak internet connectivity, lack of digitisation, and poor hardware are major obstacles to AI deployment.
Courts are not just service providers; they are custodians of justice. Over-reliance on AI risks undermining fairness, transparency, and human judgment. Hence, AI must be adopted with caution, transparency and safeguards.
