Artificial Intelligence in Judiciary: Applications & shortcomings

Artificial Intelligence in Judiciary
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Introduction to AI:

Artificial Intelligence is everywhere nowadays. Can we use Artificial Intelligence in Judiciary as well? This article examines the applications and shortcomings of AI in Judiciary. Although the acronym is used interchangeably with the terms “Artificial” and “Augmented” Intelligence, the terms are not synonymous. The distinction between these two interpretations of artificial intelligence is both subtle and significant. While “augmented” denotes the ability of technology to augment human capabilities; the term “artificial” carries an unsettling connotation, connotation of something phoney or hastily concocted to resemble a more expensive but a desirable alternative.

Due to the fact that AI processes and Algorithms can be cloaked in complexity or protected by intellectual property laws, Artificial intelligence may appear to be a ruse to conceal something more sinister. Obviously, this would be undesirable. Intelligence that has been “augmented” is both more accurate and more palatable. For courts, AI refers to Augmented Intelligence, the application of technology to accomplish tasks that humans do faster and better.

Application of Artificial Intelligence in Judiciary:

Numerous parts of the justice delivery system can be significantly impacted by an AI application. It is capable of minimizing the pendency of processes while gradually increasing their quantity. According to the latest National Judicial Data Grid (NJDG), 3,89,41,148 cases remain unresolved at the district and taluka levels, while 58,43,113 cases remain unresolved at the high court level. Pendency has a cascading impact, lowering the judiciary’s efficiency and, ultimately, people’s access to justice.

Contracts can include a clause saying that in the event of a dispute, the issue will be addressed by artificial intelligence. AI’s role will be to assess the facts and evidence and then forecast the case’s outcome or to estimate the amount of harm suffered by the party seeking compensation. The parties must determine whether to accept or reject the Judgment. As a result, the chamber used to approach the court would remain open at all times. Ultimately, financial savings related with the appointment of costly arbitrators and proceedings will be realised.

Human intelligence and emotion are required for criminal decision-making, civil matters involving a little sum can be handled by AI. Apart from issuing judgements, the court may address other issues such as joining parties, mis-joinder, and identifying the matter’s territorial jurisdiction. Machine learning can be used to supply data regarding when parties are joined and which matters fall outside the territorial jurisdiction of the court. All of these concerns waste the court’s time; however, the AI can perform this function, which saves time as well. Numerous judges are assigned administrative responsibilities; imagine if these responsibilities could be done by a computer and monitored by any other qualified individual other than a judge. Then those judges can be deployed more effectively.

Shortcomings of AI:

According to a research paper released by Vidhi Center for Legal Policy (an independent think tank), AI can mistakenly or actively perpetuate biases and is susceptible to attack or hacking. Individuals frequently use computer systems to alleviate the work associated with decision-making rather than to improve the quality of their own decisions. As a result of the enormous pressure of caseloads and insufficient resources, there is a risk that judges will employ supporting systems based on AI without applying their own ideas. “It is thus feasible that the deployment of decision assistance technologies in the judiciary will exacerbate, rather than improve adjudication,” the paper cautioned.

“Because these algorithms are frequently trained on huge datasets, they frequently reproduce the biases seen in the original datasets. Similarly, personal biases of algorithm developers may exacerbate this problem,” the paper stated.

Recent Happenings:

SA Bobde, India’s former Chief Justice, presented a vision for the judiciary’s employment of artificial intelligence (AI). During that speech, he expressed his joy at the establishment of the Supreme Court Portal for Court Efficiency (SUPACE). ManCorp Innovations Lab (MCIL), the creator of this AI-powered system, has already assisted the Jharkhand and Patna High Courts with comparable solutions to meet the judiciary’s challenges.

In a interview with Bar & Bench, the CEO said they discovered a judge shortage and a significant volume of criminal cases when they studied the Jharkhand High Court’s concerns. Two pieces of technology were developed by the company:

1. Optical Character Recognition (OCR) – transforms scanned documents to machine-readable text, corrects for orientation, and so forth.

2. ChatBot – operated via voice and text commands.

Similarly, SUVAS is a machine-learning system that assists in the translation of judgements into regional languages. This is another game-changing project aimed at increasing access to justice. When applied to other aspects of case filing in the long run, the technology will reduce the time required to submit a case and aid the court in becoming an autonomous, quick, and efficient system.

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