Artificial Intelligence can help reduce pendency of cases, increase efficiency of judiciary. But before its adoption in the legal system, challenges related to privacy, data protection and other ethical issues must be addressed.
Artificial Intelligence (AI) seems to be catching the attention of a large section of people, no doubt because of the infinite possibilities it offers. It assimilates, contributes as well as poses challenges to almost all disciplines including philosophy, cognitive science, economics, law, and the social sciences. AI and Machine Learning (ML) have a multiplier effect on increasing the efficiency of any system or industry. If used effectively, it can bring about incremental changes and transform the ecosystem of several sectors. However, before applying such technology, it is important to identify the problems and the challenges within each sector and develop the specific modalities on how the AI architecture will have the highest impact.
In the justice delivery system, there are multiple spaces where the AI application can have a deep impact. It has the capacity to reduce the pendency and incrementally increase the processes. The recent National Judicial Data Grid (NJDG) shows that 3,89,41,148 cases are pending at the District and Taluka levels and 58,43,113 are still unresolved at the high courts. Such pendency has a spin-off effect that takes a toll on the efficiency of the judiciary, and ultimately reduces peoples’ access to justice.
The use of AI in the justice system depends on first identifying various legal processes where the application of this technology can reduce pendency and increase efficiency. The machine first needs to perceive a particular process and get information about the process under examination. For example, to extract facts from a legal document, the programme should be able to understand the document and what it entails. Over time, the machine can learn from experience, and as we provide more data, the programme learns and makes predictions about the document, thereby making the underlying system more intelligent every time. This requires the development of computer programmes and software which are highly-complex requiring advanced technologies. Additionally, there is a need of constantly nurturing to reduce any bias, and increase learning.
One such complex tool named SUPACE (Supreme Court Portal for Assistance in Court Efficiency) was recently launched by the Supreme Court of India. Designed to first understand judicial processes that require automation, it then assists the Court in improving efficiency and reducing pendency by encapsulating judicial processes that have the capability of being automated through AI.
Similarly, SUVAS is an AI system that can assist in the translation of judgments into regional languages. This is another landmark effort to increase access to justice. The technology, when applied in the long run to solve other challenges of translation in filing of cases, will reduce the time taken to file a case and assist the court in becoming an independent, quick, and efficient system.
Through these steps, the Supreme Court has become the global frontrunner in application of AI and Machine Learning into processes of the justice system. But we must remember that despite the great advances made by the apex court, the current development in the realm of AI is only scratching the surface.
Over time, as one understands and evaluates various legal processes, AI and related technologies will be able to automate and complement several tasks performed by legal professionals. It will allow them to invest more energy in creatively solving legal issues. It has the possibility of helping judges conduct trials faster and more effectively thereby reducing the pendency of cases. It will assist legal professionals in devoting more time in developing better legal reasoning, legal discussion and interpretation of laws.
However, the integration of these technologies will be a challenging task as the legal architecture is highly complex and technologies can only be auxiliary means to achieve legal justice. There is also no doubt that as AI technology grows, concerns about data protection, privacy, human rights and ethics will pose fresh challenges and will require great self-regulation by developers of these technologies. It will also require external regulation by the legislature through statute, rules, regulation and by judiciary through judicial review qua constitutional standards. But with increasing adoption of the technology, there will be more debates and conversations on these problems as well as their potential solutions. In the long-run all this would help in reducing the pendency of cases and improving overall efficiency of justice system.
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