Last updated:December 10, 2024, 14:23 IST
The use of artificial intelligence should not be seen as a replacement for human judgment, but as an “assistance” tool. Over-reliance on automated processes may violate principles of discretion and fairness
Globally, AI is also advancing in the justice system. (Shutterstock file)
As a lawyer, one of the oldest professions in the world, when we look at society and its myriad human relationships and complexities, the role of lawyers becomes extremely important. As our society grew, the legal profession became organized. As a result, we are facing an epidemic-like situation where cases remain unresolved.
According to the National Judicial Data Grid (NJDG), as of 2024, India faces a severe case backlog in the judicial sector, with over 44 million pending cases, including 82,989 in the Supreme Court alone. There is. Despite a disposal rate of nearly 94.92 percent, the backlog remains high and cases continue to rise due to disruptions caused by the COVID-19 pandemic. The Supreme Court currently presides over a large number of cases, including 1,130 cases in three-judge courts, 274 cases in five-judge courts, and other cases in larger courts. To address this, a special Lok Adalat was organized in July-August 2024 and successfully resolved 1,100 of the 2,200 cases listed.
This backlog not only delays individual justice, it also impedes economic development and increases the need for innovation. However, there is growing optimism surrounding the rapid development of artificial intelligence (AI). AI provides tools that have the potential to revolutionize the way courts operate, reducing delays and increasing access to justice for millions of people.
The potential of AI to address pending situations
AI refers to computer systems designed to perform tasks that typically require human intelligence, such as learning, problem-solving, and decision-making. Unlike human intelligence, AI relies on algorithms and vast data sets to identify patterns and make predictions. The Supreme Court has taken the first steps toward AI integration. Launched in 2019, SUVAS (Supreme Court Vidhik Anuvaad Software) employs machine learning to translate Supreme Court judgments into nine regional languages. It aims to remove language barriers and make justice more accessible.
Another notable tool is SUPACE (Supreme Court Portal for Court Efficiency Support), which was launched to provide digital infrastructure to support the digitalization of court processes. SUPACE helps reduce time spent on daily tasks by reading case files, extracting relevant facts and arguments, and presenting them in a concise manner to judges and researchers. It also helps in creating daily documents, effectively improving efficiency and streamlining judicial procedures. Additionally, SUPACE incorporates machine learning capabilities that can mimic human behavior, similar to the algorithms used by platforms such as YouTube, and suggest videos similar to previously viewed videos. By automating administrative tasks, SUPACE frees up judges’ time to focus on resolving cases quickly.
Several high courts in India are experimenting with AI applications. In Jasinder Singh v. State of Punjab (2023), the Punjab and Haryana High Court seeks input from ChatGPT to understand broader global views on granting bail in cases involving atrocities This was an unprecedented move. The Delhi High Court is further speeding up the judicial process by introducing AI Saransh, a tool that generates summaries of legal arguments that help judges quickly understand the key issues in a case.
Globally, AI is also advancing in the justice system. Argentina’s Prometea automates repetitive bureaucratic tasks, extracts relevant information, and even prioritizes cases based on urgency. Brazil’s VICTOR system uses natural language processing (NLP) to analyze documents, significantly reducing the Supreme Court’s workload. In Estonia, AI judges are resolving small claims disputes, and in Canada, AI is being used to process small property and auto claims.
assignment
AI is starting to be integrated into the Indian judiciary, but bias is one of the biggest concerns arising from the datasets used to train the algorithms. If data reflects existing social biases, AI systems can perpetuate or exacerbate these biases, leading to inequitable outcomes. A study by the University of Pennsylvania found evidence of “in-group bias” within Indian law enforcement, particularly against Scheduled Caste and Scheduled Tribe individuals. The introduction of AI systems trained on such biased data could exacerbate these inequalities and further disadvantage already vulnerable communities. The COMPAS system has been found to be biased against African Americans, raising concerns about its potential to perpetuate racial discrimination. Disparity.
Another key challenge is the “black box” nature of many AI systems. A lack of transparency in the decision-making process of AI systems can undermine public trust and make it difficult to ensure accountability. Australia’s Supreme Court has expressed similar concerns. The potential for AI-based predictive models to perpetuate existing biases against Indigenous communities, for the Director of Public Prosecutions in Western Australia v Mangoramara.
The possibility of AI “hallucinations” also poses a significant risk. Generative AI systems can fabricate information, which can lead to inaccurate legal advice. In Roberto Mata v. Avianca Airlines (2023), a federal judge in Manhattan fined a lawyer $5,000 for presenting fictitious facts. Moreover, the legal research created by ChatGPT with the purpose of misleading the court was also carried out in the Delhi High Court case regarding Christian Louboutin. Judge Pratibha M. Singh refused to use the ChatGPT-generated answers, citing concerns about potential inaccuracies, fictitious case law, and imaginary data generated by AI chatbots.
suggestion
The Supreme Court’s experimentation with AI tools like SUVAS is a positive step towards reducing translation errors in critical documents such as FIRs and witness statements, which often result in long delays in case processing. AI can also play a key role in better case management and prioritization. When used for random case assignment, it eliminates the need for manual intervention and ensures that the process remains unbiased and fair. By analyzing data, AI can predict the outcome of cases and identify cases that are likely to be resolved quickly and those that require urgent attention, allowing courts to prioritize cases that require immediate attention. can be attached. Additionally, incorporating AI into routine and simple matters such as civil violations, DUIs, and dishonored checks can lead to faster resolutions and lower overall backlogs.
Incorporating AI into the justice system offers a variety of practical benefits, but caution is essential. The use of AI should be seen as an “assistance” tool, not as a replacement for human judgment. Excessive reliance on automated processes can be inconsistent with the principles of discretion and fairness. There are legitimate concerns about biased datasets and potential risks. Improving the efficiency of the justice system must not come at the cost of compromising the human dimension of justice and justice. Therefore, AI implementation must be carefully considered and approached with care.
The author is a senior advocate of the Supreme Court and a former Additional Attorney General of India. The views expressed in the article above are personal and solely those of the author. They do not necessarily reflect the views of News18.
