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Natural Language Processing and Artificial Intelligence in the service of the legal sector

By Adv. Edo Bar-Gil.


In this article, we will discuss the (potential) impacts of Natural Language Processing (NLP) and Artificial Intelligence (AI) in the services of the legal sector, while focusing on one of the main aspects of the legal services - the legal research.

While there is no argument on the advantages of the innovation and the impacts of NLP and AI and many studies show (and even celebrate) that, in this article will point out some of the concerns and (potential) disadvantages / risks, as we should all be aware of them and take them into consideration.


Traditional Legal Research

Legal research lies at the heart of the legal profession. Any (proper) legal advice is (and should be) based on constitutional law and/or statutory law (as created by legislators) and/or case law (as created by courts). Legal research enables the attorneys to learn from previous (similar) incidents, understand the risks involved and even mitigate or eliminate them and make decisions based on previous precedents.


There are many examples of doing that – determining the limitation of liability cap in an agreement, drafting arguments for a litigation case, mapping the risks in a specific deal and so on.

Currently, most of the online legal databases are based on OCR (Optical Character Recognition) capabilities – i.e., based on the ‘images’ or ‘shapes’ of the words or phrases. While this capability dramatically improved the legal research and saved lots of time on looking for and reviewing endless documents, it is still limited and has one significant disadvantage.

This disadvantage lays in the fact that in many cases one might simply not find what one needs. The reasons for that are various, however we are going to focus on two of them:

  • misspelling a word or spelling it correctly, while such word is written in a different way in a specific document one wishes to find (for example, if one looks for a “non-assignment” clause and it is spelt “non assignment” without “-“ in a specific document, one will simply not find it).

  • in addition, in many current databases, one cannot search for a phrase or a set of words in a proper way, due to the same reasons. Such difficulty exists also in more “advanced” data bases, that enable to search a few key words, however if such words do not appear is a specific order or spelt differently, one might not find / miss the relevant document.

Bottom line, this may lead to missing crucial documents / cases / court decisions, which are necessary to provide a proper advice.


In order to prevent that from happening (and due to the fact that lawyers are liable for their advice), many attorneys tend to make broader searches (for example, instead of looking for non-assignment, they will search for “assignment”, so they do not miss anything), which take much longer time and cost their clients much more money (not necessarily with better results).

There is no doubt that this is not an ideal situation.

The Dual Challenge Attorneys Are Encountering

Having said that, one can easily understand the dual challenge attorneys’ encounter:


On the one hand, the amount of data and databases are constantly growing, among others due to the globalization, multi-national cases that are based on multi-national legal systems and publications of new legislation, orders, court decisions and regulations.

On the other hand, the capabilities of the attorneys to search for the proper data are limited and might end up in missing crucial data.


So, how can we improve this Catch-22 situation? By using NLP and AI.

What is NLP (Natural Language Processing)? NLP uses AI to streamline the research process and prevent / mitigate many of the potential errors of traditional legal research. NLP works by “machine learning” human language, using context, prior queries and results, in order to “predict” what attorneys might need in their searches.


A good example of NLP is the ’Google Search’ - if one starts typing “restaurant,” Google may automatically suggest “restaurants near me.” In addition, if one misspells “restaurant”, Google will recognize the misspelling and provide the correct search results.

While NLP and AI are used for years in other professional fields, such as (online) marketing and sciences, they have not been used broadly (and successfully) in the legal sector till recent days, even though their impact on such sector might be significant.


How Can NLP and AI Assist the Legal Sector and Specifically, the Legal Research?

Since legal research lies at the heart of the legal profession and any proper legal advice is (and should be) based on decent research, there is no doubt that NLP and AI can significantly assist. Below are some examples of that:

  • NLP and AI can ease the attorneys’ queries, in a simple and intuitive way, like they use the Google Search. For example, instead of looking for the phrase “non-assignment”, one can easily type “what is the most important principle in a non-assignment clause?” - Based on the context of the query and thousands of other related queries, the system would “predict” what exactly the attorney wants to find and even suggest keywords to fill out the search.

  • NLP and AI can help to streamline the searches, identify relevant cases (while eliminating irrelevant ones) and analyze the decisions of any given judge or court. By doing that, attorneys can tailor their arguments around what the judge / court will find most persuasive. It may also assist in “building” predictive models to help better understand how a judge or court may rule.

  • NLP and AI may also save time by directing the researcher to specific phrases in long documents. By doing that, attorneys can quickly decide which cases / documents are not relevant, dive in deeper on relevant cases / documents and get better search results.

  • NLP and AI enable analyzing huge amounts of data in a matter of seconds / minutes. By doing that, not only that attorneys can make faster and more accurate decisions, but they may also create intelligent analysis and useful Big Data databases.

  • Last but not least, by enabling to analyze huge amounts of data in a matter of seconds / minutes, NLP and AI may save lots of working hours and money to the clients.

The above-mentioned matters are only some of the advantages that may be achieved by using NLP and AI in the legal sector and specifically, in the legal research area.


In a recent study that explored the impacts of using AI in research platforms, the conclusions were decisive:

  • Attorneys using AI finished research projects, on average, 24.5% faster than attorneys using traditional legal research.

  • the results of the legal research done by attorneys using AI were, on average, 21% more relevant than those found doing traditional legal research.

  • 45% of the attorneys believed they would have missed important or critical precedents if they had only done traditional legal research instead of also using AI to find cases.

Bottom line, there is no doubt that NLP and AI have significant advantages and that they may revolutionize the way legal research is done. This is why it is not surprising that many legal-tech companies are starting to use NLP and AI and embed their capabilities in their solutions. This “trend” will only grow in the next few years.


However, Are There any Risks or Disadvantages In Using NLP and AI?

The answer is simply YES, as demonstrated on Timnit Gebru’s termination by Google case.


In a nut shell, Timnit Gebru is a respected artificial intelligence researcher that was employed by Google. In the past months, she coauthored, with four other Google scientists and the university of Washington researcher, a paper about the ethics of large language models.

These models help create search engines and digital assistants, that can better “understand” and “respond” to users. The paper raised questions about whether google was trying to conceal ethical concerns over a key piece of NLP and AI technology.


Google has declined to comment about Gebru’s departure, but it has referred to an email to staff written by Jeff Dean, the senior vice president in charge of Google’s AI research division, according to which the study didn’t meet the Google’s standards. Thousands of people, including over 2,000 Google employees, have signed an open letter protesting Google’s treatment of Gebru and demanding that the company explain itself.


The study dealt with many aspects of NLP and AI and we are not going to cover them in this article. However, we are going to point out some of the potential “risks” that Gebru and her team found in using NLP and AI, as we should all be aware of them:

  • Adverse Environmental Impacts training and running large language models is based on using huge servers. Such servers are consuming lots of electricity and have a significant carbon footprint. For example, the study mention that ‘BERT’ - Google’s own language model - produced, by one estimate, about 1,438 pounds of carbon dioxide, i.e about the amount of a roundtrip flight from New York to San Francisco.

  • Human Bias Since NLP models are trained on huge amount of text and data, they might include lots of existing “human bias”, particularly about gender and race. Such bias is extremely difficult to audit and test and it extremely difficult to audit and test and it may go undetected.

  • Significant Costs that May Lead to Biased Results the money and efforts spent on building language models might “affect” the results of the models. For example, if only large corporations may fund such models, they may - by their very nature - develop models that will be “suitable” to their own agendas and eliminate any criticism of their acts.

To Sum It Up, there are significant advantages in using NLP and AI in the legal sector and specifically, in the legal research area. It may lead to attorneys working smarter, in a more efficient and precise way and with better and faster results and, of course, to more satisfied clients. However, as it is applying to any other great inventions, with great power comes great responsibility and we should all be aware of the potential risks lying in using such capabilities in a “wrong” way.

About the Author Adv. Edo Bar-Gil is the CEO of LawFlex Designed Solutions, premiere Legal Operations company (https://www.lawflexds.co.il/)


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