On Feb. 24, 2012, Judge Andrew Peck issued his opinion in Da Silva Moore v. Publicis Groupe, 287 F.R.D. 182 (S.D.N.Y. 2012), the first case to approve the use of predictive coding in a litigation matter. Many legal commentators declared that this was a death knell for the use of traditional human document review to identify relevant documents in litigation. Predictive coding could replace human intelligence with artificial intelligence, allowing relevant documents to be identified more quickly, less expensively, and perhaps even more accurately than human review. Some companies and law firms (including our own) invested in predictive coding software.
Now, three years later, human document review remains very much alive—indeed, far more prevalent than predictive coding. Given all of the reputed advantages of predictive coding, why is that still the case? This article explores seven barriers that have slowed the adoption of predictive coding as a substitute for human review.
Not Enough Documents
This content has been archived.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]