AI AND THE LEGAL WORLD

INTRODUCTION

Artificial intelligence is a word that might be misleading, at least when it comes to how it operates in the legal sector. Maybe a better description, and one that's taking on, is cognitive computing instead of being programmed, cognitive tools are trained to complete activities that were previously completed by people. The emphasis is on detecting patterns the data to the test, and determining or providing findings. Or, as I like it, an excursion companion who can search through the sundeck and explain how it is set up. Why is this major? Due to the 2.5 quintillion bytes of data that are generated daily, according to IBM for those of you who are not up to date on a quint, that's bytes daily basis. The definition of an insolvable problem is any being's capacity to evaluate and understand that position of data without assistance. The use of artificial intelligence (AI) by lawyers and the legal sector as a whole is still in its infancy. How will the legal profession be affected by this technology? The adoption of artificial intelligence, especially by in-house lawyers, will be the driving force behind a revolution in legal practise within the next few years. AI will become commonplace, changing how we conduct business every day, just like email did. For practically all lawyers, it will be a necessary helper. Those who do not adapt and embrace change will fall behind. Those who do so will eventually find themselves with more time to do the two things for which there consistently appears to be insufficient time: thinking and writing.

ACQUAINTANCE WITH THE TECHNOLOGY

Artificial intelligence is a field of technology that allows machines or computer systems to process data and make judgments. At their core, computers are still dependent on humans, and they require a great deal of data to create a pattern and then perform tasks based on the information that has previously been fed to them in the form of data. The most common misconception about AI technology is that it can automate all tasks; however, this is not the case. Artificial intelligence is classified into two types: Artificial narrow intelligence and Artificial general intelligence are two types of AI. The first technique is currently much more practical since, given technological improvements, we can only teach a computer to perform a certain activity using artificial intelligence, such as speech processing, language translation, and other similar tasks. To achieve artificial general intelligence, we would have to instruct machines to presume in the same way that humans do and to perform all of the tasks, which is currently not possible because we have not figured out how the human mind works.

Ø MACHINE LEARNING

Algorithms in machine learning are used to identify data-driven trends and make forecasts or choices without being supervised by machine learning. It is critical to recognise that obtaining 100% validity from an algorithm based on machine learning is unattainable. If a machine learning algorithm can achieve near 95% accuracy, it is suitable for deployment. However, this level of precision should be achieved on a substantial amount of test data This technology is based on the concept of A to B mapping, in which the machine is first fed data for both inputs and outputs, and at the test phase it is asked to finish the assignment by entering data A, for which it returns the outputs. Which is B. For example, if we feed a machine learning algorithm relevant information on which emails are spam and which ones are not, we must first provide information on both forms of emails and predict which of them is junk mail and which isn't, and then at the testing phase, we will enter a mail and the machine output will demonstrate whether it is a fraudulent mail or not depending on the information that was fed to the algorithm.

Ø DATA SCIENCE

Data science is a field that extracts information and conclusions from organized and unstructured data using scientific methodology, procedures, algorithms, and devices. It entails data collection, cleaning, analysis, and interpretation, as well as the application of various techniques to extract meaningful insights, such as statistical research, deep learning, and visualisation. As a result, making informed decisions becomes easier.

Ø DEEP LEARNING

It's a type of technology used in cognitive computing. It is a technology for creating and training large neural network models, which allows the machine to perform the task for which the network was created. This technology was inspired by how the brain operates in humans, but their mechanisms are totally unconnected.

AUTOMATED LEGAL WORK

→ AI CHATBOTS

Lawyers can be too involved in representing their clients in court to sit down with them and resolve every single issue. This issue of their clientele can be settled by the artificial intelligence program, which can be an alignment of 2-3 projects such as civil law suit prediction and actively helping in the enrolment of intellectual property laws discussed earlier in this article, and on the basis of that, the software can actually create highly customized responses for some particular questions that are likely to occur for most of the clients and assist them in getting answers, which can help them calm their minds because dealing with legal actions can be challenging at times.

→ LITIGATION PREDICTION

When legal professionals are talking to their clients about a civil lawsuit, among the most popular queries the clients have is about the likelihood of winning the case. Lawyers forecast the result of civil lawsuits with the aid of their expertise and understanding of human psychology. Occasionally people just file a lawsuits in order to benefit from filing a suit. These suits can be diminished if we have a methodology that can predict the result based on previous judgements in similar cases. This has the possibility of significantly lowering the cases that are filed and, as a result, the judiciary’s liability.

→ DUE DILIGENCE

When a business transaction is made, the prime objective is to carry out due diligence. In this task, law firms work on their client’s behalf to investigate the other party's past history and paper trail. It includes searching for certain things, such as previous civil lawsuits, and if they are discovered, they must be discussed before any further decisions to move the deal forward are made. With the use of technology, this task can be very well managed by replacing manuals and normalising what must be verified and where it must be verified.

CURRENT PROJECTS

1. SMITH.AI

This is a startup that has attempted to help law firms by providing them with a "virtual receptionist" through the use of an AI chatbot that aides in signing and transferring the calls that a law firm receives on a daily basis. It is a company that offers services to legal professionals in their area.

2. DILIGEN

This software aids law firms in performing due diligence by partially automating the process. This software uses machine learning algorithms to look for specific clauses, provisions, or changes in contractual agreements, as well as to produce a quick and easy-to-read overview of the clauses in the documents.

3. CHATGPT:

ChatGPT is an artificial-intelligence chatbot developed by AI research company Open AI. Released in November 2022, it can have conversations on topics from history to philosophy, generate lyrics in the style of Taylor Swift or Billy Joel, and suggest edits to computer programming code. ChatGPT is trained on a vast compilation of articles, images, websites and social media posts scraped from the internet as well as real-time conversations—primarily in English—with human contractors hired by Open AI. It learns to mimic the grammar and structure of writing and reflects frequently used phrases. It also learns to recognize shapes and patterns in images, such as the contours of a cat, a child or a shirt. It can match words and phrases to those shapes and patterns as well, allowing users to ask about the contents of an image, such as what a cat is doing or the color of the shirt.

CONCLUSION

Numerous innovative legal industry developments have been made to increase judges, lawyers and jurist’s whose productive capacity through legal services software and other methodologies the system advanced and eventually lead to bring down the pendency of cases. However, none of the AI-powered software aims to replace attorneys; rather, it seeks to enhance the precision and accuracy of judgement and analysis. The legal sector in India is still expanding, and more AI-based and digitalized techniques are on the way. These machine-learning automated support programmes will not replace the legal profession's analysis, differences, and decision-making; rather, they will significantly increase solicitors' effectiveness and expertise while automating many clerical tasks. Artificial intelligence is now a reality. It cannot replace humans, but it can help them with various tasks they perform on a daily basis. All tasks in which decision-making is based on some kind of pattern recognition and is quantifiable in some way imply that artificial intelligence can substitute some of the tasks that rely on the intelligent quotient (IQ), but today's technological standards cannot replace the tasks that rely on the emotional quotient (EQ). This uniqueness in our imaginative styles cannot be accepted by modern technology, and the legal system as a profession deals with human emotions as well as behavioural science. As a result of such intelligent automation, a new paradigm emerges, which now dictates not only how businesses operate, but also who does the job. Many manufacturing plants can now be fully automated with robots and no human workers. Artificial intelligence is now bringing previously unseen and unexpected innovations to the business world, which many organisations will need to incorporate in order to remain competitive and move further ahead of competitors.

~Kaynaat Rana