This article is written by Silvia M Jacob, BA LLB. 5th year at Kristu Jayanti College of Law, Bangalore, during her internship at LeDroit India
Introduction
India’s judiciary, the world’s largest, is often characterised by its profound caseload and procedural delays. Over 50 million cases are currently pending across Indian courts, from lower tribunals to the Supreme Court. With a rapidly modernising democracy and growing citizen expectations, the need for reform in the judicial process has grown to be greater urgent than ever.
Once thought to be the domain of science fiction, Artificial Intelligence (AI) has started to make considerable headway into India’s judicial system. By advocating for efficiency, openness, and public access, AI-driven solutions promise to transform the face of Indian justice. Along with passion comes caution, though especially about algorithmic bias and the issue: when AI goes astray, who bears the blame?
The article investigates how artificial intelligence is changing Indian courts, the nuances of algorithmic bias in legal technology, the real advantages of AI adoption, the growing argument on responsibility, recent developments, and persistent obstacles. It hopes to provide a clear, illuminating guide for lawyers, technologists, policymakers, and any citizen concerned about justice by concentrating on India’s distinct legal and social structures.
Understanding Algorithmic Bias in Indian Courts:
Algorithmic bias refers to the systematic and unfair discrimination that can arise from the way AI systems are designed or trained on data. Essentially, if an AI system learns from biased data or is set up by humans with unconscious prejudices, its outputs can perpetuate those same injustices, often at scale and speed unavailable to human actors.
For instance, if an AI judge-assist tool is trained mostly on precedents involving privileged urban litigants, its recommendations may not adequately reflect the realities of rural, marginalised, or non-mainstream communities. Algorithmic bias isn’t intentional, but its consequences can be severe, especially in a judiciary that upholds rights for the most vulnerable.
Sources of Algorithmic Bias:
- Historical Data Bias: Indian judgments, like anywhere, carry the imprint of their societal context. If this historical data contains gendered, caste-based, or class-based prejudices, AI systems may learn to repeat them.
- Feature Selection and Data Composition: Decisions about which variables to emphasise (such as economic background or geography) can introduce hidden bias.
- Translation & Linguistic Bias: India’s linguistic diversity means AI translation tools must be especially careful to maintain neutrality and precision, lest language becomes a marker for bias.
- Access Disparities in Data: The digital divide means many cases, especially from rural or under-connected areas, are underrepresented in digitised datasets, skewing AI learning.
Indian Context and Sensitivities:
India’s social structure, varied in caste, religion, language, gender, and financial status, requires sensitivity to bias. Data about caste-sensitive or conclusions on women’s credibility must be treated with great care, for example. Notably, any automation has to eliminate the chance of exacerbating past exclusions that the court system is charged to redress.
Example: Although India is not yet employing artificial intelligence for main judicial judgments like bail or sentencing, as in the United States, the worldwide conversation offers caution. In certain instances, algorithms learned on past police or court data have disproportionately denied bail to minorities in the US since historical data showed greater arrest and conviction rates among those groups. Translating similar technology without Indian-specific safeguards could reinforce established discrimination.
Benefits of AI in Indian Courts:
Despite these risks, the advantages of AI in the Indian judicial system are multi-fold and substantial, particularly given the scale and complexity of the country’s legal system.
- Case Backlog Reduction and Workflow Automation:
With over 50 million pending cases, India faces logistical and administrative backlogs of epic proportions. AI can Automate Case Management: Scheduling, prioritization, and resource allocation can be optimized using AI-powered dashboards, freeing up valuable judicial time. Smart Tracking and Defect Correction AI can flag case filing errors, track e-filings, and monitor case progress, reducing procedural delays.
- Speed and Efficiency:
- Real-time Transcription: Since 2023, the Supreme Court has piloted AI-powered transcription tools for complex oral arguments in Constitution Bench cases. This enables instant, searchable records and aids in appeals.
- Document Summarization & Precedent Search: AI can rapidly sift through legal documents, highlighting the most relevant statutes or case law, something that would take teams of lawyers days or weeks.
- Translation & Linguistic Access:
Language is a historic barrier in the Indian legal system. Key developments include:
- Judgment Translation: AI tools have translated more than 36,000 Supreme Court judgments into Hindi and over 17,000 into 16 other Indian languages as of August 2024, providing critical access for non-English speakers.
- Eased Communication: Multilingual chatbots and translation services can assist litigants and lawyers from rural and regional areas to navigate complex court documentation.
- Legal Research and Drafting:
AI Portals: Tools like SUPACE (Supreme Court Portal for Assistance in Court Efficiency) use AI to collect facts, search case histories, and present relevant suggestions to judges.
Chatbots: Virtual legal assistants answer process-related queries, helping the public and reducing administrative burden.
- Transparency and Predictability:
AI assists transparency by ensuring all cases are accessible, searchable, and managed consistently through a digitised, rule-based system. Automation in tracking and workflow minimizes arbitrary delays and corruption.
- Citizen Access and Inclusion:
Court websites and kiosks equipped with AI interfaces improve accessibility for remote or new court users, bridging divides in legal literacy and reach.
Who Shall Have Accountability?
As AI becomes embedded in Indian court routines, a profound policy and ethical question arises: Who should be held responsible when something goes wrong?
- Judiciary and Judges:
Indian courts firmly uphold that AI is only an “assistive” tool, not a decision-maker. Judges retain constitutional responsibility for all verdicts and judicial orders, and must exercise human judgment and independent reasoning. The recent Kerala High Court Policy (2025) explicitly bans AI-driven legal reasoning or verdicts, affirming that technology is for assistance, not replacement. Also, the Delhi High Court, 2023, ruled that while ChatGPT and similar tools can support research, they cannot be relied upon for facts or core reasoning.
- AI Developers and Vendors:
Where third-party vendors or public institutions develop AI tools, responsibility for errors in coding, data management, or software performance rests with them. This includes liability for defects (e.g., translation errors, misclassification of data) and the obligation to fix problems promptly.
- Government and Regulators:
The Ministry of Law & Justice, National Informatics Centre (NIC), and related regulatory bodies oversee the implementation, testing, and updating of AI tools in courts. The government funds audits, ensures data privacy, and sets national policies, acting as the ultimate steward for public trust in judicial automation.
- Litigation and Redress:
Indian law allows for judicial review: any party harmed by AI-enabled missteps can appeal and seek a human judicial remedy. The Supreme Court and High Courts have clarified that all decisions, whether AI-assisted or not, are subject to challenge on constitutionality, fairness, or process.
- Collaborative Accountability:
The consensus emerging from policy and practice is that accountability must be shared: Judges for decisions, developers for tools, and governments for overall regulation and safeguards. AI is not a separate legal actor; it is a tool wielded by humans and institutions responsible under India’s constitutional framework.
Recent Developments in AI Adoption in Indian Courts:
- SUPACE and Supreme Court Initiatives:
The Supreme Court Portal for Assistance in Court Efficiency (SUPACE), launched in pilot form, combines machine learning and natural language processing to help judges find facts, precedents, and key arguments from vast documents. SUPACE does not recommend legal outcomes but acts as an intelligent research assistant; it is carefully monitored for reliability and fairness.
- e-Courts Project Phase III:
The National e-Courts Mission is India’s flagship project for digital transformation, now entering its third phase with more than ₹7,200 crore ($870 million) allocated. Integration of AI is a top priority for:
- Case management automation
- Electronic filing (“e-filing”)
- Tracking, reporting, and smart dashboards for administrators
AI helps in defect detection and curing for electronic filings, improving document accuracy and speeding up workflows.
- AI-Driven Transcription and Translation:
Real-time transcription pilots in the Supreme Court have demonstrated substantial time and cost savings, while translation AI is breaking down longstanding linguistic barriers, making judgments accessible beyond English-speaking elites.
- Chatbots and Citizen-Facing Services:
High Courts and district courts, especially in Maharashtra, Gujarat, and Delhi, have adopted AI chatbots to automate information requests, guide users through civil and criminal procedures, and provide forms or assistance in local languages.
- High Court Policies on AI:
In the state of Kerala, in July 2025, it issued India’s first explicit policy on AI, banning its use for fact-finding or legal reasoning, confining it to clerical and research assistance. The policy calls for regular audits and encourages all AI adoption to be transparent and explainable. In Delhi, 2024, similar guidelines were issued, clarifying that only supporting/administrative roles are safe for AI. Also in the Manipur High Court, 2024: Used ChatGPT for legal context in a bail order, but clarified that final orders must be independently reasoned.
- AI and Blockchain Funding Surge:
Over ₹53 crore has been earmarked for AI and blockchain modernization in High Courts, with institutional partnerships involving IITs and NIC for tool development, bias audits, and data privacy
- Ongoing Ethical and Policy Debates:
The judiciary, legislature, and legal academia are debating a rights-based approach to AI in courts, proposing mandatory audits for bias, stronger privacy regulation, and public consultation on new deployments. Civil society groups have called for transparency, “explainable AI,” and the inclusion of marginalized voices in policy design.
Conclusion
AI in Indian courts stands at an exciting, pivotal crossroads. With its vast potential to increase efficiency, enhance access, and make the justice system more transparent, AI offers answers to many of the most enduring challenges facing India’s judiciary. Yet, the promises of technology are counterbalanced by serious responsibilities, particularly around bias, fairness, and accountability. India’s approach so far has been one of cautious adoption: embracing AI for process automation, legal research, transcription, and translation, while refusing to allow any substitution of human judicial reasoning. The Kerala and Delhi High Courts’ explicit bans on AI-driven legal decisions reinforce the commitment to human-centric justice. Regular audits, clear guidelines, and strong government oversight are becoming the norm. Algorithmic bias remains a real risk, especially in India’s complex social landscape. The onus is on policymakers, developers, and judicial leaders to ensure that AI advances do not replicate or deepen the divisions the court is meant to bridge. Data must be representative, audits regular, and equity a guiding star in every tool’s design. Accountability in the AI era demands a collaborative mindset: No single entity can or should bear responsibility. Judges, technologists, and the government must share oversight and consequences, knowing that in each case, the lives and liberties of Indian citizens are at stake. As India continues its digital justice journey, the principles of fairness, equality, and constitutional supremacy must remain paramount. With wise regulation and adaptive policy, AI can help create a judicial system that is not just faster and smarter but inclusive, just, and humane.
