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Natural Language Processing Law Firms

Law has language at its core, so it`s no surprise that software that works with natural language has long played a role in some areas of the legal profession. But in recent years, interest in applying modern techniques to a wider range of problems has grown, so this article explores how natural language processing is used in the legal sector today. Natural language processing (NLP) is one of the most practical areas of AI today. This technology is the driving force behind chatbots, smart speakers and spell checkers, and it could go even further. Many law firms have begun to recognize NLP`s potential. A typical strategy for new and small players seems to be to focus first on very specific types of documents, such as NDAs, real estate leases, and privacy policies, and then expand the scope of covered documents as the company gains customers and traction. Leverton, from DFKI (funded in 2012; Financing €15 million)19 focuses mainly on real estate documents. It is aimed at companies with large real estate portfolios and deals with contracts in 20 languages. Other smaller players include eBrevia (founded in 2012, with $4.3 million in funding), Eigen Technologies (founded in 2014, funding UKP13M), LegalSifter (founded in 2013, with $6.2 million in funding), and Luminance (founded in 2003, with $13 million in funding), but there are many more. NLP combines linguistics, AI, and machine learning to teach computers to process human languages and overcome ambiguities. NLP learns human language, uses context and previous queries and results to predict what lawyers need in their research. A clear example of NLP is the use of Google Search. For example, if a user types “restaurant,” Google can automatically suggest “restaurants near me.” The more the user searches for Google, the more Google can predict what the user is looking for when they say “Stay…” If the user misspells “restaurants near me,” Google recognizes the spelling error and returns the correct search results.

The same goes for AI in legal research. Like Google, NLP improves legal search results because lawyers use online search tools. Here are some ways AI legal research streamlines and simplifies legal research. The most innovative platforms can conduct reviews and provide advice in a fraction of the time a lawyer should spend on review. In some cases, state-of-the-art contract review and negotiation technology such as LexCheck can return a fully marked contract in just a few minutes, ensuring that all contract terms are clear and free of ambiguous wording. Natural language processing techniques promise to automate an activity that is at the heart of many lawyers` professions, namely the extraction and processing of information from unstructured texts. Relevant methodologies are a key ingredient for current and future applications of legal technologies, and their potential and limitations will determine how successful legal technology is to revolutionize the legal services market. This chapter provides a non-technical introduction to a selection of natural language processing techniques that are expected to play an important role in legal technology. In addition, the promises and pitfalls of natural language processing tools are critically discussed in this context, using technological verification in case outcome detection and predictions as examples.

There are also ethical implications to consider. Digitizing data to submit it to an NLP algorithm could expose it to cybercrime and compromise customer privacy. Law firms and their clients who are not aware of this risk can inadvertently make sensitive data vulnerable. E-discovery is the process of identifying and collecting electronically stored information in response to a request for disclosure in connection with a dispute or investigation. Given the hundreds of thousands of files that might reside on a typical hard drive, a key problem is separating that content into what is relevant (or “responsive” in domain terminology) and what is not. In a recent patent dispute with Apple, Samsung collected and processed approximately 3.6TB, or 11,108,653 documents; The cost of processing this evidence over a 20-month period has been estimated at over $13 million. Other legal NLP models examine contracts for questionable terms. Some can analyze around 500 common terms and contract types in multiple languages.

This analysis helps identify potential omissions, loopholes or small print that a lawyer`s client should be aware of. LexCheck uses natural language processing to perform legal document checks that ensure stricter and less ambiguous contracts. To see how it works, request a demo or contact us by email at Ross Intelligence (founded in 2014, funded to the tune of $13.1 million), which uses IBM Watson, and vLex (founded in 1998, funded to the tune of 4 million euros) with a product called Vincent provide natural language query interfaces so that “you can ask your research questions as if you were talking to another lawyer”. LexisNexis (then simply called LEXIS) first appeared in the early 1970s and initially offered a full-text search in the jurisdiction of Ohio and New York. And from that moment on, it only grew. In the late 1970s, lawyers were able to access the database via dial-up services from dedicated terminals via 1200 baud modems. In the late 1990s, the data was on the Internet.

Today, Lexis Nexis claims to have more than 30TB of content. Westlaw, another major player in the world of legal databases, was also founded in the mid-1970s and acquired by Thomson Corporation (now Thomson Reuters) in 1996. Add Wolters Kluwer and Bloomberg Law and you have the top four established providers in the space. Most law firms subscribe to some or all of these services. Natural language processing (NLP) is a technological innovation that is driving change in various industries. As machines gain a more complex understanding of language and context, they can perform tasks previously performed by often overworked employees. NLP contributes to applications ranging from translation to word processing, and more recently, technology has also reached more complex sectors. For example, the application of natural language processing to legal documents is revolutionizing legal and procurement services for businesses.

Law firms process huge amounts of data and information on a daily basis. This is where NLP software can be extremely effective. It can sift through information quickly and completely. Simply put, NLP helps the software understand natural language. It uses tools to understand the basic techniques of defining words, sentences, sentences, texts and syntax (knowledge of the meanings of words and vocabulary) and semantics (understanding the combination of sentences). It also develops applications such as machine translation (MT), answer questions (QA), data retrieval, discussion, document creation, and recommendation program, to name a few. There are three key areas of legal activity in which NLP plays an active role: legal research, electronic disclosure and contract review. Interestingly, generic NLP suppliers are also popping up in space. OpenText has launched an eDiscovery platform called Axcelerate. and SDL, known for its translation products and services, offers a multilingual eDiscovery solution that provides access to foreign language case content through translation.

NLP is a subset of AI that processes natural human language, whether in text or voice. Some of the most well-known examples include Google`s predictive search suggestions, spell checkers, and speech recognition. NLP is a promising industry that is expected to be worth $27.6 billion by 2026 and has a significant impact on the legal sector. The legal industry`s reliance on precise language makes it the perfect place to use NLP.

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