AI in the Indian judiciary: 8 solutions to our current struggles
AI in the Indian judiciary: 8 solutions to our current struggles

The Indian court system is under more pressure than ever, with a massive number of pending cases. As of November 2019, there were 59,867 cases pending in the Supreme Court alone and a further 4,475,000 in high courts. The paralysing shortage of judges (over 8,000 are understood to be needed to clear the backlog) is undoubtedly a main cause of this problem, but with immense inefficiencies rife throughout the system it is clear that the solution (or solutions) cannot rely on human correction alone. Can the use of artificial intelligence (AI) in the Indian judiciary make a difference? I believe it can, and here are eight ways in which I think that can happen:

  1. Improving access to fundamentally-important legal information

    The development of AI chatbots that lead people with legal questions towards legal answers should be an efficient way to reduce the burden on courts. These chatbots can provide coordinated guidance for a person without the support of a lawyer, thereby reducing the information gap and, accordingly, the need to proceed to litigation. This is especially useful for factually and legally straightforward situations, usually relating to a lack of legal knowledge or practicality, such as traffic fines or simple compensation claims.

  2. Better functioning legal search engines 

    AI has also been used to develop legal search engines that help to simplify legal research.

    A good example is, which claims to be the ‘Google of law’. They use big data and machine learning to collate the largest collection of French law available for free. The key issues addressed here are that French law is now not only accessible free of charge to the general public, but also simplified and therefore understandable to the lay citizen.

    This addresses important gaps in the current legal framework as the content and scope of law expands exponentially while the expectation for citizens’ abiding by the law remains unchanged. The divergence between these two phenomena makes it increasingly unfair to citizens; indeed, how can people be expected to follow laws that they are unable to learn about? 

    Another dilemma in legal research is that the, often online, search for a specific answer is directed to a mass amount of information and data. The AI used by is set to reverse this problem. A search for legal answers on will lead clients to focussed and relevant results, not a mass of (for the most part unsorted) information.

    This technology is useful for reducing strain on the judiciary because citizens will be able to access legal answers without going through a tedious legal process first. More time and energy can, therefore, be directed to answering complex and novel legal issues in courts.

  3. Creation of new strategic tools

    In addition to introducing new solutions into the Indian legal system, it is also important to reform its current internal processes. Much can be achieved here simply in adopting new strategic tools that offer more efficiency.

    A good example would be everis’ knowler. This award-winning knowledge management solution uses ontology and AI to organise a company’s structured and unstructured data to create meaningful knowledge. This can be accessed on a platform used to manage and share knowledge, with AI algorithms that recommend relevant information and a comprehensive system tailored to a company and its particular industry.

    This is useful for the judiciary as it enables the organisation (and reorganisation) of masses of data, whether relating to court schedules, judgments, or personnel. Admittedly, adopting this kind of system would be a complete reform in the internal processes, requiring time to learn and adapt to a new system. However, these efforts should be compensated by long-term improvements in efficiency, avoiding the continued accumulation of pending cases.

  4. Reducing reliance on agents (lawyers) and increasing self-representation 

    AI could easily direct unrepresented individuals through the process of a civil court case by ‘advising’ on options and ‘instructing’ how to submit various documents. This would serve as a game-changing tool for those who cannot afford expensive legal fees, and in doing so, it would help to improve the overall quality of justice received by low-income participants.

  5. Active and intelligent case management

    AI is already improving case management, and this will continue unabated in the coming years. Latvia is one example of a jurisdiction considering the use of machine learning for the administration of justice. By processing court statistics, the allocation of human and financial resources amongst cases can be improved.

    This ‘predictive justice’ can be adopted by the Indian judiciary so that their resources are used more efficiently. And getting there shouldn’t be too problematic. The judiciary already has a real-time case analysis system displaying and analysing data for pending cases, and this system can be adapted for predictive analysis.

  6. Case analysis and legal validity prediction

    AI can help analyse the quality of a legal claim and any relevant evidence. This is an area where the judiciary can benefit from use of big data. AI can automatically organise a list of pending cases, the chronology of events in a case, and detect patterns in claims. This could facilitate assessments of the quality of an argument by analysing its legal validity and strength against competing claims.

  7. Ensuring similar judgments for similar cases

    Judicial supervision is a controversial topic, but AI could find a home in that arena. In this regard, AI in the Indian judiciary could serve as a means of supervising judges to ensure the consistency of case judgments. China’s Supreme People’s Court promotes the system of ‘similar judgments for similar cases’, meaning that judgment criteria amongst similar cases from the same court or higher courts should be consistent.

    With the information about previous cases and an effective supervisory mechanism, this can greatly reduce the average time spent on cases.

  8. Judicial decision-making  

    Finally, AI could readily be used to predict how a case will be decided and to propose ways to settle it. In the Australian Family Law courts, the Split-Up system has been adopted to predict outcomes for property disputes in divorce and other family cases. The system uses rules-based reasoning along with neural networks to make predictions. The results are then used by judges to support their decision-making, as they are able to identify assets of marriages that should be included in a settlement and allocate appropriate percentages to each party.

A bright future for AI in the Indian judiciary

Reducing the pending caseload and improving long-term efficiencies are just two of the many ways that AI in the Indian judiciary is set to make waves. The full gamut of improvements surely will only become apparent in time, but I, for one, am confident that AI’s potential will soon be realised not just in the courts, but in the lives of those that the courts are meant to serve. In this regard, we need to remember that AI is not just a tool for operational efficiency, but that it could be the crux of efforts to ensure better access to justice across India.

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