AI Legal Research

The Role of AI in Legal Research

Erik Lindberg, Senior Director WestLaw Product Management, in an article titled “Looking for the right AI for legal research?” stated, "The best tools are always going to be a combination of the automation coming from the technology and the insights that a human editor can bring to the situation. The legal language is very, very nuanced. We’re not training computers to replace lawyers. So, automation is never going to get you the full picture, but it can eliminate some of the tasks and some of the work that you have to do along the way. It's that combination of the right people and the right technology that really will give you the best solution."

Artificial intelligence (AI) is the simulation of human intelligence processes by machines, especially computer systems. Specific applications of AI include expert systems, natural language processing, speech recognition and machine vision.

A vast volume of labelled training data is typically ingested by AI systems, which then examines the data for correlations and patterns before employing these patterns to forecast future states. In this way, by studying millions of instances, an image recognition tool can learn to recognise and describe objects in photographs, or a chatbot that is given examples of text chats can learn to make lifelike exchanges with people.

Race against time to discover the future

AI is significant because it can outperform people in certain types of activities and because it can provide businesses with previously unknown insights into their operations. AI technologies tend to get work done faster and with a lesser chance of error when compared to humans, especially when it comes to repetitive, detail-oriented activities like reviewing a large number of legal documents to ensure that the relevant fields are filled in appropriately.

In the legal field, legal research is a vital task that all lawyers need to perform while handling any case. It is a crucial and demanding endeavour that combines both art and science. The prophetic quality to sneak into the future by knowing the kind of responses which have to be used to offer direction to an inquiry and the poetic imagination to highlight the importance and relation of the result are both simultaneously required for effective research. 

The two challenges that lawyers encounter when conducting legal research are a lack of time and an uncertainty regarding the outcomes. Gaining trust in how a judge or other authority will see the research and argument that is being developed by an attorney or researcher is also no less than a nightmare for many. It takes a lot more time to conduct legal research in order to feel more certain about it. However, regrettably, given the time constraints, it remains unrealistic for any practising lawyer to be able to devote a significant amount of time to research.

Sorting and modifying the raw data to create acceptable legal research is also another herculean task.

Nowadays, Machine learning and Artificial Intelligence (AI) is making advancements in the field of legal study and research. When looking for relevant precedents, law students and law firm associates used to spend a lot of time browsing through case law volumes. This process has gone digital with the advent of personal computing, and attorneys nowadays conduct research using information sources namely WestLaw, LexisNexis, Manupatra, etc.

In addition to the aforementioned, a new generation has emerged in recent years with the same goal of transforming legal research through advancements in natural language processing and AI. These platforms go way above and beyond simple keyword searching to the extent of even being capable enough of highlighting the most pertinent existing law hidden beneath pages and pages of judgements and case laws. To name a few for illustration purposes: 

  • Casetext, which is a platform for legal research that uses AI to make finding cases for clients simple and rapid. It also analyses cases to ensure that they are relevant to the matter at hand.
  • Diligen, wherein by employing machine learning to review contracts for certain clauses, conditions, or modifications and by swiftly producing a useful summary, Diligen assists lawyers in conducting due diligence.
  • Casemine, company that wants to connect various case laws using artificial intelligence (AI), making it simpler for legal experts to undertake an in-depth study with CaseIQ. In order to conduct thorough legal research, this machine-learning software functions as a legal assistant by researching case laws, analysing the legal terminology, and acting as an assistant by pointing out any potential legal points that may be missing, suggesting alternative arguments, and highlighting pertinent verdicts and case laws thus highly improving the quality of the work result produced.

AI can be used in legal research to help lawyers quickly sift through large amounts of legal data and identify relevant information. This can include using natural language processing to analyse legal documents and contracts, as well as using machine learning algorithms to predict the outcome of court cases based on historical data. Additionally, AI can also be used to assist with legal research by identifying relevant cases, statutes, and regulations, and by providing summaries of key legal concepts. The goal of using AI in legal research is to make the process faster, more efficient, and more accurate, which can save time and resources for both lawyers as well as clients.

The potential

Gartner estimates that by 2023, more than 33% of large organizations will have analysts practicing decision intelligence, including decision modelling.

In our recent article, “Will ChatGPT Disrupt the Legal Industry?”, we discussed the potential of ChatGPT (OpenAI’s new offerings) and the potential it has to disrupt the legal industry. GPT models can be trained on legal text and used to generate summaries of legal documents, helping lawyers quickly find relevant information and make more informed decisions.

Theresa Coleman, in her recent article for The Week titled, “A.I. powered 'robot lawyer' will appear in a U.S. court for the first time” discussed an experimental step toward exploring the capabilities of increasingly sophisticated AI tools – ‘robot lawyer’. She talked about how DoNotPay, the Consumer advocacy tech company, recently caused a splash after announcing that its AI-enhanced "robot lawyer" would soon assist with a real-life traffic court case. The device, which runs on a smartphone, would listen to arguments in court and formulate a response that will be fed to the defendant via wireless headphones.

Will the future be predictable by AI?

According to Rita Sallam, Distinguished VP Analyst at Gartner, “[N]ow is the time to anticipate, adapt and scale the value of your Data and Analytics (D&A) strategy by monitoring, experimenting with or aggressively investing in key D&A technology trends based on their urgency and alignment to business priorities.”

AI tools and platforms offer a variety of functionalities and features to legal practitioners and in the coming years it will be a massive support to the legal sector. Particularly, when legal practitioners are conducting legal research, and leveraging these systems may provide significant gains in time and accuracy.

Practitioners, however, would probably need to spend the time and money to comprehend how a particular AI solution could help them and their clients. AI suppliers should also concentrate on educating practitioners about the advantages and, more significantly, the accuracy of such systems if they are to win the appropriate amount of trust from legal teams. The adoption of these AI platforms and tools will expand only after then. At present there is a massive scope for a large-scale deployment of AI in the legal sector especially in areas of contracts, litigation analytics, secretarial work and legal research. 

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Disclaimer:  The views and opinions expressed in this article do not necessarily reflect the official policy or position of Novum Learning or Legal Practice Intelligence (LPI). While every attempt has been made to ensure that the information in this article has been obtained from reliable sources, neither Novum Learning or LPI nor the author is responsible for any errors or omissions, or for the results obtained from the use of this information, as the content published here is for information purposes only. The article does not constitute a comprehensive or complete statement of the matters discussed or the law relating thereto and does not constitute professional and/or financial advice.

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