This blog is authored by Debmalya Biswas, 3rd Year Student, KIIT SCHOOL OF LAW, KIIT Deemed to be University, Bhubaneswar
AI is the study of cognitive processes utilising computer science’s conceptual frameworks and techniques. Al emerged in the mid-fifties as a separate topic in computer science. Machine learning (‘ML’) that can increase its capabilities without the need for humans to reprogram it is what Microsoft roughly defines AI as. The construction of an AI model for thinking based on the idea of precedent is an illustrative example. AI has advanced to the point where it now permeates practically all service industries, producing multi-billion-dollar businesses. Professional software that is used daily is solely AI-based. Law is one of the most crucial service fields. According to CBRE’s latest assessment of London law firms, 48% are currently employing AI, and another 41% want to do so shortly. In addition, according to a Deloitte report, 100,000 legal positions will be automated by 2036, and law firms will confront a “tipping point” for a new talent strategy by 2020. As a result, legal firms that are slow to adopt AI capabilities risk slipping behind their more forward-thinking competitors.
Development of AI-Based Legal Technology
Artificial intelligence (AI)-based legal technologies are rapidly being utilized to assist lawyers today. However, technology has not progressed to where attorneys could be replaced. These AI-based legal systems mostly use machine learning and Natural language Processing (NLP). This is a frequently utilised technology for personal assistants in a variety of disciplines and industries. This technology analyses the user’s speech, breaks it down for optimal comprehension, and processes it accordingly. This is a relatively new and successful strategy, and as a result, it is in great demand in today’s market. Natural Language Processing is a new subject that has already seen significant advancements, such as interoperability with smart gadgets and interactive human conversations. AI applications in NLP focused on knowledge representation, logical reasoning, and constraint fulfilment.
Technology-assisted review (‘TAR’) is one of the numerous uses of AI in providing legal services. It allows users to classify papers to make document review more efficient. Lawyers identify relevant documents and upload them to a review database to generate the master set, which serves as the source for future searches, just as they would with a manual document review. Through interactive testing, TAR enlists the help of a lawyer to lead the review process. To produce a seed set, the lawyer might utilize search terms or define parameters for judgmental sampling. The seed set is used to compare the entire collection of recorded data. The AI created a heat map, which highlights aberrations from the norm.
There are additional programs that keep track of compliance and highlight red flags. AI is being used in specific existing legal research tools and new apps to assist with natural language legal research. Document automation systems are improving by the day, utilizing artificial intelligence to assist in the creation of everything from simple notifications to complex commercial contracts. Specific programs use natural language processing (NLP) to sift through court dockets to forecast decision outcomes, find favourable jurisdictions to file a lawsuit, and suggest potential successful motions and arguments before certain judges. With the use of AI, electronic billing has also been enhanced. These apps have resulted in fewer line item conflicts, more accurate client modifications, more precise reporting, monitoring, and lower paper expenses. Intellectual property searches and claims are the focus of certain apps.
Leveraging AI to the Legal Sectors
In a report, the Ministry of Electronics and Information Technology has mentioned improving the Legal System’s Efficiency. With many years of processing experience, the Indian court system has amassed an enormous quantity of judgment records. Some are in English, while others are in various Indian languages. Therefore, it is necessary to make them accessible across languages using different language processing technologies (OCR, Search, Machine Translation, and so on).
Legal systems can use AI algorithms to govern a defendant’s “risk,”. It includes anything from the risk of a person committing another crime to the likelihood of a defendant showing up for their court date. These computational results influence bail sentencing and parole decisions. A potential remedy to this judicial concern has arrived, thanks to bipartisan interest in criminal justice reform and the rise of big data. Recidivism risk assessments are increasingly being included in presentencing investigation reports (PSIs), which traditionally provide background information on convicts to sentencing judges. These assessments calculate the likelihood of a person with the offender’s record committing another crime based on a study of actuarial data.
This risk assessment technology was used in Wisconsin v. Loomis’s case, where The Wisconsin Supreme Court ruled that a trial court’s use of an algorithmic risk assessment in sentencing did not violate the defendant’s due process rights, despite the fact that neither the court nor the defendant was given access to the technique utilised to create the assessment.
Judicial awareness increases people’s faith in the justice system by raising their awareness of the judiciary, including the procedure, facts, and interpretation. This can also help reduce the number of possible disagreements due to a lack of awareness. AI and information technology can assist in scaling such a successful public awareness campaign to a wider audience.
AI Improving the Modern Legal System
According to the National Judicial Data Grid (NJDG), 3.81 crore cases are still unresolved in district and taluka courts. More than a lakh of the cases are over 30 years old. In 2018-19, the High Courts’ pendency rate climbed by 20.20% and 5.29%, respectively. From 2019 to 2020, the backlog in various district courts increased by 18.2 %. From 60,469 cases on March 1, 2020, to 66,727 cases on March 1, 2021, the Supreme Court’s pendency rate increased to 10.35%.
In order to reduce the backlogs, on April 6, 2021, the Supreme Court’s Artificial Intelligence Committee opened its artificial intelligence platform, SUPACE (Supreme Court Portal for Assistance in Court). SC is already using Suvas, a machine-learning tool for language processing, to translate its decisions into regional languages. SUPACE is a new AI-assisted composite tool that processes case files, extracts essential information, produces case documentation, and manages task apportionment. The Supreme Court plans to employ machine learning to analyse the massive amounts of data gathered when filing cases through the portal. It is designed to behave like an individual user, learning from and mirroring user behaviour. This makes it even more efficient because the system ‘learns’ to gather relevant information and present it so that the judge or legal researcher can understand.
The system also contains a chat box that provides an overview of the case and answers questions. The chatbox is constantly learning, allowing it to improve its responses to both factual and contextual queries. SUPACE’s use is also projected to speed up procedures in both the high courts and lower courts. It will close infrastructural gaps by giving lower courts instant access to case law established by SC judgments in an intelligible format. SC created SCI-Interact software to make its 17 benches paperless. LIMBS, E-Courts, and other efforts have also been developed.
Conclusion
AI holds a lot of potential as a technology. It makes use of data platforms, AI algorithms, and AI apps. It is being used in various fields, especially if a vast amount of data is accessible or projected to be available. AI is made available in sectors ranging from agriculture and food to water resources, education, transportation, legal, finance, and governance. Artificial Intelligence in the legal system is helping in the automation of routine procedures. The legal teams would have to cope with a lot of data and information processing. AI implementation will be beneficial in lowering wait times and offering faster and better information processing. In contrast, many critics questioned the use of AI-based SUPACE in decision-making. Justice Bobde stated that the SC would not use AI once all of the information had been analysed. It would be done to preserve the judge’s discretion in resolving the case. Artificial intelligence and technology are two areas of life that never stop to captivate and astonish us with new concepts, topics, discoveries, and products, among other things. It should take a practical approach to regulation and create flexible guidelines for attorneys’ use of technology. It would be foolish to rely only on self-regulation by the legal services business.
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