One of the more important facets of adapting to machine learning in today’s legal sphere is knowing when not to use it. At the “Re-designing Legal Processes in the Age of Machine Learning” panel at the Corporate Legal Operations Consortium (CLOC) 2019 institute in Las Vegas, a group of law firm attorneys discussed how important it is not to develop a solution and then go looking for a problem.

But what exactly does it mean? While machine learning can be useful for repetitive process-level work such as separating relevant documents from a set, not every problem merits the type of investment necessary to properly bring it to bear.

This content has been archived.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

Why am I seeing this?

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]