![]() And using enhanced search capabilities, Westlaw Edge can harness this data to tell you many things that in the past, lawyers had used their experience and word of mouth to try to capture, often providing little more than the proverbial wild ass guess. Westlaw has been quietly compiling a database that houses all filings from federal dockets and many from state dockets. Westlaw Edge reportedly does this by using machine learning with the help of its with editors and researchers.īut its in the field of data analytics the Westlaw Edge really shines. Westlaw Edge is trumpeted as having improved search capabilities providing not only simple term matching but a better understanding of text and context in which legal concepts are discussed and weeding out that’s which is non responsive. The researcher can then click through the cases that are discovered and get more detail. Westlaw Edge uses AI to not only address the issue the researcher has specifically asked it to address, but then to spot similar wording and issues in other cases. ( A recent study found lawyers frequently miss cite cases or fail to cite cases that are on point). ![]() This makes research time consuming and often inaccurate. Part of the problem with legal research is that different courts may use different terms to describe the same legal concept and terms can mean different things to different courts. But other than a few early adopters, AI has not caught on in the mainstream legal community. Westlaw Edge has two main components: an enhanced legal research prong which basically better harnesses machine learning and natural language processing-AI-to the legal research field.ĪI legal research has been trumpeted for years by start ups and technolgy companies as a more efficient and better way to do research. It has 100s of researchers and editors on staff to provide the muscle to harness the data it has. This plus the fact that Thomson Reuters/Westlaw has tons of data about cases, lawyers and the legal field from its collection over the years of cases and its keynote system. Hutton commercial: When Westlaw talks, lawyers listen. who have not used and relied on the Westlaw keynotes in doing research. I dare say there are probably few, if any, lawyers in the U.S. Lawyers have relied for years on the Westlaw for legal research. ![]() It developed the keynote model where important points of a case are summarized and grouped with similar points in other cases for research purposes. For years, it has been the preeminent publisher of legal materials, case books and statutory digests. Westlaw is one of the most familiar names in the lawyer industry. ![]() Plus, lawyers aren’t technologists so when it comes to evaluating technology, they look, a) to whether it’s being offered by an entity with which they are familiar and b) who among their peers is using the product. While books could be and have been written analyzing all the reasons for this-from the law firm structure and the billable hour model to lawyers’ personalities-one key component for this slowness is the fact that the technology being offered is not intuitive and takes valuable (billable) time away from the lawyer to learn and use it. Some background: lawyers are notoriously slow to adopt new technologies. One reason for the slowness of lawyers to adopt technology is that the technology being offered is not intuitive and takes valuable (billable) time away from the lawyer to learn and use the technology If true, then Thomson Reuters’ new Westlaw products announced today may be the event that takes AI and data analytics into the mainstream for the legal profession. And all this is especially true in the legal profession. This is particularly the case where the product saves time, is easy to use and produces a better result. This is in part true because our behaviors are influenced by our peers, how widespread we think the use of a particular product is and how well known the provider of the product is to us. Standard innovation theory tells us that we move from an early adoption phase to mainstream very quickly.
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