We hope that you like your Geek in Review with a little extra geekiness this week because we dive in with CaseText’s Chief Product Officer Pablo Arredondo on their innovative search tool, WeSearch. This completely unique method of indexing texts into what Arredondo calls a “sublimely complex, 768-dimensional vector space” creates a truly beautiful, and useful method of searching not just the words in the documents, but the concepts and meanings of those documents. Unlike the Artificial Intelligence tools many of us in the legal industry currently use, there’s no need to spend weeks or months training the system to understand the documents. The Neural Net techniques developed by the likes of Jacob Devlin, Google Researcher, and BERT author, allows the system to train itself, and the folks at CaseText have turned it loose to learn American case law.
While this new method of research opens many potential usages (and we brainstorm a few in the interview), but it also opens up some issues that aren’t unique to the legal industry, but are common in this industry. Issues such as acceptance of cloud-based utilities, what can and what cannot be accessed by the neural net tool, and perhaps the biggest issue we discuss, and that is the black box issue. Traditionally, when vendors provide search tools with AI and Natural Language Processing (NLP), there are Intellectual Property issues of the “Black Box” of the tool. While the methodology of how the system works is known by the vendor, just like the formula for Coke, it isn’t something they are willing to share. When it comes to this tool, the neural net and vectors work in ways that can be explained on a basic level, but after the system is trained, it begins functioning in a way that can’t be explained. This will be an issue that law librarians and academics may need to dive into in the not-so-distant future.
The WeSearch tool is available to test out. Let us know what you think.
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Continue Reading The Geek in Review Ep. 114: Pablo Arredondo on CaseText’s New WeSearch Tool and How the Neural Net Is Making Its Way Into Legal Information