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Artificial Intelligence and Judiciary

Posted on March 7, 2022 by admin1  1344

In News

  • Recently, an unstarred question in the Lok Sabha during the first part of the Budget session of Parliament was asked with reference to artificial intelligence and its use in judicial processes to reduce the pendency of cases.

Pendency of Cases

  • Law Ministry data: The High Court’s (57.39 lakh cases) and the subordinate courts (1, 08, 36,087 cases) together have conducted 1.65 crore virtual hearings till 2021.

Artificial Intelligence

  • It is a field of computer science which makes a computer system that can mimic human intelligence.
  • It is composed of two words “Artificial” and “intelligence“, which means “a human-made thinking power.
  • The Artificial intelligence system does not require being pre-programmed, instead, they use such algorithms which can work with their own intelligence.
  • It involves machine learning algorithms such as Reinforcement learning algorithms and deep learning neural networks.

Machine Learning

  • It is about extracting knowledge from the data.
  • It enables a computer system to make predictions or make some decisions using historical data without being explicitly programmed.
  • Machine learning uses a massive amount of structured and semi-structured data so that a machine learning model can generate accurate results or give predictions based on that data.

 

Benefits of integrating AI & ML in Justice delivery

  • While implementing phase two of the eCourts projects, under operation since 2015, a need was felt to adopt new, cutting edge technologies of Machine Learning (ML) and Artificial Intelligence (AI) to increase the efficiency of the justice delivery system.
  • The Supreme Court of India has constituted an Artificial Intelligence Committee which has mainly identified application of AI technology in Translation of judicial documents; Legal research assistance and Process automation.
  • ML-based applications in Judiciary: AI powered tools like SUPACE will not only help organise cases, it will also bring references into the judgment at a speed not seen so far.
  • AI will present a more streamlined, cost effective and time bound means to the fundamental right of access to justice.
  • Tools derived from AI could help expedite the case-flow management which in turn helps in lowering delays and pendency in courts.
  • The use of software to analyze thousands of previous cases and create a ‘judge analytics’.
  • Over the course of the COVID-19 pandemic, the use of technology for e-filing, and virtual hearings has seen a dramatic rise which can be solved via this technology.

ML-based applications in Judiciary

  • SUVAS is a language learning application being used to translate judgments.
  • SUPACE can draft a legal brief, comprise the initiatives being undertaken in the Indian judiciary as part of incorporating ML-based applications

 

Issues and Challenges associated with AI in Judiciary

  • The use of ML in India’s legal sphere has so far been restricted to automating back-end work, and is still a very long way from being used as a decision-making tool for the judiciary.
  • Many of the judgments, particularly in the lower courts, are yet to be fully digitized.
  • Going by global trends, greater adoption of these tools in the Indian legal system is inevitable.
  • AI and ML should assist but do not replace human decision making.
  • The ethical and responsible use of AI and ML for the advancement of efficiency enhancement can be increasingly embedded in legal and judicial processes. 

Way Forward

  • Automated systems, controversially, were being used to decide bail applications in some parts of the United States, and other countries such as Estonia have incorporated AI and ML in a major way.
  • But the Indian judicial system is generally “more conservative”, and a lot more work remained in making India’s legal data amenable to ML formats.
  • AI and ML can be tried in tribunals where there is no need for oral evidence and cross examination.
  • Consumer courts are an area where AI can be helpful.
    • But in criminal cases where oral evidence and cross examination are key processes, we have to rely on regular human intervention.

Source: TH

 
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