Making a Case for Machine Learning to Legal Departments

Since we released our text summarization resources, the legal technology community has shown interest in leveraging summarization technology to support litigation document review, deposition digests, and contract analysis. Data scientist interest to use machine learning to mine legal document corpuses and support legal strategy was also one factor motivating our summarization research. The time is therefore ripe for data scientists to apply new text analytics capabilities for legal use cases. But to be effective, data scientists must first understand how lawyers think: what problems they're trying to solve, how their processes are structured, and, perhaps most importantly, what fears may hinder the adoption of new technologies. This guest blog post from Dean Gonsowski, kCura's VP of Business Development, provides tips to help data scientists explain the value of machine learning to lawyers. Electronic discovery software helps manage the exchange of electronically stored information, documents that could be used as evidence in various forms of litigation like investigations or contract reviews.