Can technology defuse the ticking pendency bomb for the Indian Judiciary system?

As per the recent National Judicial Data Grid (NJDG), with over 44 million pending court cases, India has the largest number of cases pending in the world as of early 2022. According to PRS Legislative Research, 41% of the cases in high courts are pending for five years, while 21% cases are pending for over 10 years whereas in subordinate courts, 23% for over five years, while 8% cases are pending for over 10 years. With record-breaking cases of 1,05,560, the graph has been constantly upward with the rate of 60% for more than 30 years. Amazingly, the longest-running case recorded in the history of IJS is of 175 years, which indicates the agony of seeking justice. Every single minute, there is an addition of 23 cases in the pendency list. Mathematics says, “it takes more than 324 years to clear the backlog only!” Human resource-wise, the number of Judges per million population in India is 20.91, compared to 107 for the USA, 75 in Canada, and 41 in Australia. The current limitation of IJS, a bench can hear as many as 66 cases per day, which is not scalable by itself. Hence, the problem statement is that “The Indian Judicial System (IJS) is sitting on a ticking pendency bomb.”

Often said, “Justice delayed is justice denied.” I would responsibly amend this statement to – “Justice delayed is injustice.”

So, what is the bottleneck here? Well, some may argue to recruit the human capital at the subordinate level. However, I don’t buy into an idea of merely increasing manpower of the IJS, but to equip them with advanced technology tools would prove “call to action” for that matter.

The real question is – “How to defuse the ticking pendency bomb for IJS?” Being an entrepreneur in technology domain for over two decades, I strongly believe that technology is at our disposal and systematic innovative approaches can help IJS. By its nature, technology is neutral, objective and scalable. Artificial Intelligence (AI), Machine Learning (ML), based on the foundation of Big Data (BD) are doing wonders in diverse fields globally. By definition, artificial intelligence (AI), is a self-learning algorithm that performs tasks associated with intelligence being but artificially. On the other hand, human intelligence (HI), is the natural intuitive ability of reasoning and problem solving, and to learn from daily experiences.

Let’s have a look at some of the AI-based examples in the judicial domain worldwide.

  1. Argentina has built an AI system titled ‘Prometea’, which accelerates repetitive mechanical bureaucratic processes, data-mine through huge volumes of files quickly, further analyse and prioritise them by sensing the urgency of the matter. ‘Prometea’ AI is a great helping hand to spare more time on the core task of the judicial system.
  2. Brazil has developed AI technology named “VICTOR”, which does natural language processing (NLP) to analyse documents, reducing the burden on the supreme court.
  3. Estonia has installed AI judges to clear the backlog of disputes of small claims
  4. Canada, AI deals with small property disputes and minor motor vehicle claims
  5. British Columbia, ‘expert system’ is the AI system being used in the Civil Resolutions Tribunal (CRT).
  6. China has deployed hundreds of robots called ‘Xiaof’ to provide legal assistance and guidance including business law or labour-related disputes to common people in public places.
  7. The US is using an AI system called ‘COMPAS’ to access the recidivism risk alert mechanism.
  8. The UK is implementing AI called H.A.R.T. to forecast reoffending criminals.
  9. China, Russia, and Mexico are making use of AI to offer legal advice and approve the proposals of pensioners.
  10. Malaysia is using AI technology to support sentencing decisions.
  11. Austria taking AI assistance for document management systems.
  12. Colombia and Argentina are setting priorities of the cases based on AI identification techniques of the urgent cases.
  13. Abu Dhabi does predictions of the probability of settlements using AI.
  14. Singapore used to transcribe the court hearings using AI in real-time.
  15. University College London scientists have developed AI judges that proved 79% of the accuracy by delivering the verdict of 584 cases for the European Court of Human Rights.
  16. UNESCO is developing an AI-based multilingual online simulation program to train judicial operators which have worked successfully for over 100 countries globally.

Unfortunately, IJS is the least beneficiary vertical of digital governance. Having said that, the government of India has also echoed AI potential and walked the steps of the advanced world.

  1. Supreme Court Portal for Assistance in Court Efficiency (SUPACE) is an AI-based tool that has reduced the chances of misplacement of important statements and evidence is greatly improving processes of the IJS.
  2. Supreme Court Vidhik Anuvaad Software (SUVAS) is an ML and AI is a translation tool.
  3. IIT Kharagpur has developed an AI-based methodology that automates the process of reading legal case judgments.
  4. The National E-Vidhan Application (NeVA) is an initiative by the government of India that is an excellent effort towards paper-free assembly also called e-Assembly which automates the handling and sharing of documents and speeds up the law-making process by tracking decisions of different levels.
  5. Justice Technologies Private Limited is an Indian start-up that has developed an online private digital court using AI and blockchain as the backend is emerging as alternative dispute resolution (ADR) mechanisms for specific commercial and civil cases.
  6. Intelligent Trial 1.0 is an AI-based scrutiny mechanism, that delivers only relevant electronic court documents and case materials to the courts.

Sounds good! But what about the challenges of AI in the judicial system? Well, unlike HI, the current state of AI has limitations with reasoning and cognitive thinking, complex litigations are far away from the scope of AI judges. Accuracy of the data and objectivity is the key to the effectiveness of the prediction of AI. From IJS point of view, India is a culturally diverse country with multiple languages, which is another limitation of AI with a standardisation approach for most of its automation. Just like any other field, IJS is no exception to challenges like privacy, data security, human rights, and relevant ethical issues.

However, the self-regulation for technologists, mandatory external regulation by legislatures will be the contributing factors towards the improvement of AI-backed IJS as a whole. Getting a boost from ML, AI can handle complex dynamics of different relationships, compared to past, future, and real-time data points by making use of IoT-like technologies. Just like one versus many minds, brainstorming together can lead to reasonable decisions, AI can gather, compile, extract input data from billions of used cases in real-time and compare and analyse to the current scenario for the most accurate of justice. The best part of AI is its self-learning ability. With the usage of AI and the advancement of technology, AI will be more accurate and efficient.

In a nutshell, how can AI turn just as a gift for IJS?  There is a lot of tedious and time-consuming preparation to be followed before any case appears before the court. Those repetitive and mechanical tasks such as document collections, data analysis, scheduling of hearings, filings, tracking case flow, stakeholder communication, and docket management are otherwise performed by legal professionals and can be handled by AI technologies in order to save valuable time. Prior to court matters, parties can make use of AI to find out possible alternatives to resolve the conflicts by themselves, saving on money and time will be the value addition. It may even evaluate alternatives for resolution or suggest options with mediation mechanisms. The work in progress jobs of legal professionals like assessing damages, screening of the matters, estimating the costs, accessing alternative disputes, finding possible options, suggesting resolution systems like mediation, arbitration, conciliation, recording eyewitnesses online, etc. which can certainly ensure speedy delivery of the justice with technology and innovations. Going further, AI tools can be made handy for the public towards the mass awareness of the laws.

The future of AI in the judicial system seems promising. “Predictive Justice”, as the name suggests, is promising by predicting the justice upfront which can ultimately help reduce the cost, the pendency of the cases, and increase the efficiency of the system. An example of such predictive AI is the Supreme Court of the United States (SCOTUS) is working with an accuracy rate of 70.2%. With the advancement of sensory technologies to sense and recognise unpredictable speech patterns, temperature changes of the body, heart-bits, sweat analysis, body language, and eye movements during the process which otherwise tricky to catch by human eyes will process information in real-time to give error-free judgments. With the appropriate regulatory framework, AI can expedite justice delivery by assisting lawyers and judges with “legal research, analysis of factual proposition, determination of appropriate legal provisions and other similar mechanical skills. AI in the legal domain can provide judges extraordinary resources so that they can focus on legal arguments leaving non-judicial facts to be taken care of by themselves.

And finally, the myth that “AI will replace the judges”, in my opinion – is totally baseless! Since the introduction of computers and with the advancement of technology, technology has always been proved assistive, never alternative. AI In IJS, can assist the justice-making process, save time, rather create new job opportunities, but never necessarily meant to replace the human judges.

Conclusion: –

“The sense of urgency and magnitude of the call demands for timely recognition of the potential of the technology. Creations of new job opportunities will be the bonus in our basket for Indian brains. In short, AI, ML, IoT, BD, and HI together hold the potential to defuse the ticking pendency bomb for the IJS!”

Abbreviations are used frequently in the above article;

HI = Human Intelligence

AI = Artificial Intelligence

ML = Machine Learning

BD = Big Data

IoT = Internet of Things.

IJS = Indian Judicial System

@ About Author – Sunil Khandbahale is a MIT Sloan Fellow Boston, Technologist, Impact Innovator and Grass-root Indian Entrepreneur, best known as the founder of KHANDBAHALE.COM – India Translation Dictionary digital platform. Read more at my personal blog website 

Article was originally published at Vedhas

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