There is a growing movement toward the use of data analytics, machine learning, and artificial intelligence technologies in a wide range of industries. In fact, many cutting edge technical prognosticators have begun proclaiming that artificial intelligence (AI) has reached breakthrough levels. David Brooks, for example, in a recent New York Times Op-Ed entitled “Our Machine Masters,” explains that these AI advances are driven by three underlying trends: “cheap parallel computation technologies, big data collection, and better algorithms.” Regardless of the underlying rationale, he concludes: “The business plans of the next 10,000 start-ups are easy to forecast: Take X and add A.I. This is a big deal, and now it’s here.”
In the legal industry, however, it’s been unclear whether AI is having a material impact. Certainly, the use of machine learning applied to the e-discovery process, often called technology assisted review (TAR) or predictive coding, has established a beachhead. But, there is scant data about what kind of actual adoption this use case has, never mind other interesting applications within the legal sphere. This includes information governance and other in-house use cases such as risk assessment, contract review, selection of outside counsel, matter management, billing, and budgeting.
This content has been archived. It is available through our partners, LexisNexis® and Bloomberg Law.
To view this content, please continue to their sites.
Not a Lexis Subscriber?
Subscribe Now
Not a Bloomberg Law Subscriber?
Subscribe Now
LexisNexis® and Bloomberg Law are third party online distributors of the broad collection of current and archived versions of ALM's legal news publications. LexisNexis® and Bloomberg Law customers are able to access and use ALM's content, including content from the National Law Journal, The American Lawyer, Legaltech News, The New York Law Journal, and Corporate Counsel, as well as other sources of legal information.
For questions call 1-877-256-2472 or contact us at [email protected]
