No, artificial intelligence (AI) doesn’t mean you’ll have robots examining boxes of documents in the near, or even distant, future, but it does have true potential to transform legal services. In law, most often “AI” means machine learning: a computer’s ability to digest large amounts of information, learn from it and apply that knowledge in a variety of ways.
Contract Review: Machine learning technology is being increasingly applied to contract review, with transformative results. Algorithms parse contract information into clauses, sections and keywords, rendering them available for search and comparison. Review teams can extract and organize information from thousands of documents in minutes, saving legal departments cost and time in a world where a merger or acquisition could now contain millions of documents.
Technology-Assisted Review: Despite the digitization of review sets, e-discovery can still be arduous and time-consuming. Technology-assisted review (TAR) is often hailed as a solution, encompassing an array of e-discovery practices and technologies that can expedite and simplify review. One example is predictive coding, a practice in which review teams take a “seed set” of documents and use it to train a machine to recognize relevance patterns applicable to the larger document set. The technology can also decipher information based on context. For example, it can determine whether a document is relevant based on the parties involved or on overall language, rather than an individual term. Deduplication, another aspect of TAR, aims to eliminate unnecessary duplicate copies of discoverable information.
Legal Research: ROSS Intelligence’s application of IBM’s Watson technology has made research the hottest area in legal AI. And while some criticize ROSS as just a powerful search engine, its ability to skillfully search through information using everyday language rather than legalese is indicative of its potential. A nonlawyer, for instance, can use machine learning research technology to case information applicable to a dispute.
Other tools have applied AI technology to different practice areas. For instance, DoNotPay, a free “chatbot” application, can answer users’ simple questions about parking tickets in New York and the United Kingdom, provide documents and send appeals.
Analytics: With advanced algorithms that can condense vast amounts of information into tangible metrics—for example, the likelihood of winning a copyright dispute by jurisdiction, or the potential financial value of a settlement—analytics is reshaping the way lawyers make decisions.
Virtual Assistants: One particularly advanced application of AI can be found in “virtual assistants,” a concept familiar from engines such as Apple’s Siri and Microsoft’s Cortana. Applying this concept in legal practice takes things a step further, from handling simple tasks like answering phones and bookkeeping to creating work flows and automating tasks. In the case of Riverview’s KIM, this may even mean analyzing an attorney’s case, showing potential results according to jurisdiction, then providing alternative approaches.