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Artificial Intelligence in Judiciary

  • 08 Mar 2022
  • 7 min read

For Prelims: eCourts project, Machine Learning (ML) and Artificial Intelligence (AI), National Judicial Data Grid (NJDG), SUPACE

For Mains: Use of Artificial Intelligence in Judiciary, data protection, privacy.

Why in News?

Recently, the Law Minister has said that for implementing phase two of the eCourts project, there is a need to adopt new, cutting edge technologies of Machine Learning (ML) and Artificial Intelligence (AI) to increase the efficiency of the justice delivery system.

  • Also, to explore the use of AI in the judicial domain, the Supreme Court of India has constituted an Artificial Intelligence Committee.
  • The committee has identified application of AI technology in Translation of judicial documents, Legal research assistance and Process automation.

What is eCourts Project?

  • About:
    • It was conceptualized with a vision to transform the Indian Judiciary by ICT (Information and Communication Technology) enablement of Courts.
    • It is a pan-India Project, monitored and funded by the Department of Justice, Ministry of Law and Justice, for the District Courts across the country.
  • Objectives of the Project:
    • To provide efficient & time-bound citizen-centric services delivery.
    • To develop, install & implement decision support systems in courts.
    • To automate the processes to provide transparency and accessibility of information to its stakeholders.
    • To enhance judicial productivity, both qualitatively & quantitatively, to make the justice delivery system affordable, accessible, cost-effective, predictable, reliable and transparent.

What is the Need of Technology in Judiciary?

  • Pendency of Cases: 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.

What are Examples of Use of Technology in Judiciary?

  • Virtual Hearing: Over the course of the Covid-19 pandemic, the use of technology for e-filing, and virtual hearings has seen a dramatic rise.
  • SUVAS (Supreme Court Vidhik Anuvaad Software): It 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.
  • SUPACE (Supreme Court Portal for Assistance in Court Efficiency): It 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.
  • Similar Global Initiatives:
    • US: COMPAS (Correctional Offender Management Profiling for Alternative Sanctions).
    • UK: HART (Harm Assessment Risk Tool).
    • China/Mexico/Russia: Giving legal advice, approving pensions.
    • Estonia: Robot judge for adjudicating small claims.
    • Malaysia: Supporting sentencing decisions .
    • Austria: Sophisticated document management.
    • Argentina/Colombia: Prometea (Identifying urgent cases within minutes).
    • Singapore: Transcribing court hearings in real-time.

What are the possible uses of AI & ML in the Judiciary?

  • Increasing efficiency of Judiciary: 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.
  • Creating Judge Analytics: After “training” the application on a huge historical set of precedents, the application is capable of highlighting key points that are relevant in specific contracts.
    • This will help analyse thousands of previous cases and create a ‘judge analytics’.

What is AI and ML?

  • Artificial Intelligence:
    • It describes the action of machines accomplishing tasks that have historically required human intelligence.
    • It includes technologies like machine learning, pattern recognition, big data, neural networks, self algorithms etc.
    • AI involves complex things such as feeding a particular data into the machine and making it react as per the different situations.
    • It is basically about creating self-learning patterns where the machine can give answers to the never answered questions like a human would ever do.
    • AI technology helps in analyzing data and thus can improve the efficiency of systems like power management in cars, mobile devices, weather predictions, video and image analysis.
    • Example (Use): Self driving cars.
  • Machine Learning:
    • Machine learning (ML) is a type of artificial intelligence (AI) that allows software applications to become more accurate at predicting outcomes without being explicitly programmed to do so.
    • Machine learning algorithms use historical data as input to predict new output values.

Way Forward

  • Side-effects of AI: 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 the judiciary through judicial review and constitutional standards.

PYQ

Q. With the present state of development, Artificial Intelligence can effectively do which of the following? (2020)

  1. Bring down electricity consumption in industrial units
  2. Create meaningful short stories and songs
  3. Disease diagnosis
  4. Text-to-Speech Conversion
  5. Wireless transmission of electrical energy

Select the correct answer using the code given below:

(a) 1, 2, 3 and 5 only
(b) 1, 3 and 4 only
(c) 2, 4 and 5 only
(d) 1, 2, 3, 4 and 5

Ans: (b)

Source: TH

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