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Artificial Intelligence (AI) In Judicial Processes- UPSC Current Affairs
Mar 13, 2022
Read today’s edition of the Current Affairs Dialog box wherein we will talk about Artificial Intelligence in Judicial Processes and how this topic constitutes an essential part of the IAS Preparation.
Click here to read yesterday's edition of Current Affairs.
For Prelims: eCourts project, Machine Learning (ML) and Artificial Intelligence (AI), SUPACE, SUVAS
For Mains: Use of Artificial Intelligence in Judiciary, data protection, privacy.
Why in the News?
During the budget session of parliament, the Law Minister said that while implementing the eCourts projects, 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.
What are the challenges associated with integrating AI & ML in the Justice delivery system?
Supreme Court on AI in Judiciary: To explore the use of AI in the judicial domain, the Supreme Court of India has constituted Artificial Intelligence Committee.
The committee has identified application of AI technology in Translation of judicial documents, Legal research assistance and Process automation.
Additional Information: Over the course of the COVID-19 pandemic, the use of technology for e-filing, and virtual hearings has seen a dramatic rise. From the beginning of the lockdown in 2020 until January 2022, the Supreme Court of India emerged as a global leader by conducting 1,81,909 virtual hearings.
About AI and ML:
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.
Example (Use): Self-driving cars.
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.
Potential Benefits of Integrating AI & ML in Justice Delivery
Improving administrative efficiency: Administrative efficiency can be improved by using Artificial intelligence to automate daily processes of the registry. For this, task-specific, narrowly tailored algorithms, trained through ML, can be deployed to aid in run of the mill administrative functions, from something as simple as scheduling hearings and creating causelists.
Improving Decision Making: ML algorithms can be conceptualised, designed and deployed for intelligent analytics and research work.
A significant amount of work for a lawyer or a judge involves legal research, analyses of factual propositions, determination of appropriate legal provisions and other similar mechanical skills can be made easy with AI/ML.
It will assist legal professionals in devoting more time in developing better legal reasoning, legal discussion and interpretation of laws.
Increases Speed: AI powered tools like SUPACE will not only help organise cases, it will also reduce the time taken to file a case and assist the court in becoming an independent, quick, and efficient system.
Lowers Pendency: Tools derived from AI could help expedite the case-flow management and it has the capacity to reduce the pendency and incrementally increase the processes.
Strengthens Right of access to Justice: AI will present a more streamlined, cost effective and time bound means to the fundamental right of access to justice.
Tribunals and Consumer Courts: 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.
Global Survey: Some of the Use Cases of AI Across the World
AI has been used in Estonia to adjudicate small claims through a robot judge.
In China, Russia and Mexico to provide legal advice and approve pensions, in Malaysia to support sentencing decisions.
In Austria as a sophisticated document management system,
In the USA, AI has more prominently been used for designing risk assessment tools. COMPAS or Correctional Offender Management Profiling for Alternative Sanctions has been used to assess recidivism risk and thus, inform parole and sentencing decisions.
HART (Harm Assessment Risk Tool) has also been used by the UK to forecast which criminals are most likely to reoffend and suggest what kind of supervision a defendant should receive in prison.
In Brazil, an AI tool called VICTOR is being used to conduct preliminary case analysis to reduce the burden on the court.
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Challenges While Using AI for Justice Delivery
Restricted to automating back-end work: 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.
Ethical Concern: The ethical and responsible use of AI and ML for the advancement of efficiency enhancement can be increasingly embedded in legal and judicial processes.
Unemployment: Since AI powered tools are intended to do what the human mind can do, but much more efficiently and methodically, there is apprehension of job losses which authorities need to take care of.
Transparency and explainability: With AI-driven technologies there are instances where the inputs and outputs are known, but the system by which they are transformed to the other is unknown.
This lack of transparency leads to an allied problem of explainability.
Law stagnating and immune to evolution: In the longer term, there is a risk of the law stagnating and becoming immune to necessary revision and evolution, thus, limiting the possibility of necessary changes in legal disposition to align with the evolving values and beliefs in the society.
AI and ML should not replace human decisionmaking, rather assist in decision making.
AI powered tools help aid access to material but should remain non-intrusive when it comes to decision making.
The Indian judicial system is generally “more conservative”, and a lot more work remains in making India’s legal data amenable to ML formats.
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.
Use of Technology in Justice Delivery System:
eCourts: The eCourts Project was conceptualized on the basis of the “National Policy and Action Plan for Implementation of Information and Communication Technology (ICT) in the Indian Judiciary – 2005”
Objective: 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 in 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.
Conducting of e-Lok Adalat: Online Lok Adalat popularly known as E -Lok Adalat is one such innovation of Legal Services Institutions where technology has been used to its maximum advantage and has become a platform to deliver justice at the doorstep of people
The purpose of initiating e-Lok Adalat is to facilitate online platforms for the litigants to decide their cases during the Pandemic situation.
Virtual Courts: Virtual Court is a concept aimed at eliminating the presence of litigants or lawyers in the court and adjudication of the case online. The facility is provided for Litigants to file the complaint electronically through e-Filing and also pay the Court Fees or Fine online
SUPACE (Supreme Court Portal for Assistance in Court Efficiency):
SUPACE was recently launched by the Supreme Court of India.
It is 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.
SUVAS: SUVAS is an AI system that can assist in the translation of judgments into regional languages.
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