Should Computers Replace Humans In The Judicial Process?

U.S. Magistrate Judge Andrew Peck is helping to pave the way by supporting the use of “predictive coding”, a method in which technology is used to assist in document review during the discovery process.[1] Predictive coding reduces the need for lawyer review by “digitally sorting through a sample of documents, then refining the search algorithms to make sure the relevant documents in the sample are selected.”[2] Although this method does not completely eliminate the need for human review, it ultimately reduces the burden on lawyers to painstakingly review hundreds, if not, thousands of documents before determining which are relevant and ultimately presented to the opposing party.[3]

In a recent case decided in the Southern District of New York, Da Silva Moore v. Publicis Groupe & MSL Group, Judge Peck became the first to allow the use of “computer-assisted review” in the discovery process.[4] Judge Peck held that computer-assisted processes of searching for pertinent documents were judicially acceptable. [5] Furthermore, in a Virginia Circuit Court, Judge James H. Chamblin allowed the use of predictive coding over the objection that predictive coding is too radical in its deviation from traditional human review.[6] According to Thomas Gricks III from Schnader Harrison Segal & Lewis, the firm representing the defendant in the Virginia case, predictive coding is “the most effective way to find relevant documents with lower costs and much more quickly.”[7] While the cost of not applying the predictive coding method is estimated to be $60 per hour, applying predictive coding to the document review process could reduce that cost by over 50%.[8] Moreover, Gary Hebert, a specialist in the area of product liability stated that “any time you introduce a human element, you increase the likelihood of error.”[9]

On the other hand, there will still be many cases in which the traditional human review is the most appropriate.  For instance, predictive coding is only applicable to cases as demonstrated in Da Silva Moore where there were more than 3 million documents for review.[10] As Judge Peck pointed out, “the concept of predictive coding is not to achieve perfection . . . but rather to utilize a technique which is better than existing alternatives in terms of completeness and accuracy, and makes sense from a cost perspective.”[11] Furthermore, predictive coding will not replace human involvement.[12] Predictive coding still requires a human to manage the process which “involve[s] intuition, decision making, exercise of judgment, input from the parties, and intervention at various phases of the process.”[13] Because predictive coding still requires human involvement, Judge Peck stated that “it is the process used and the interaction of man and machine that the court needs to examine” and not necessarily the technology being used.[14]

As noted above, the decision to allow for predictive coding raises the question as to whether future courts will uphold this alternative method of e-discovery and whether this is the beginning of a more digitalized direction in the American litigation process.

[1] Richard Acello, Beyond Prediction: Technology-Assisted Review Enters the Lexicon (Aug. 1, 2012, 1:09 AM),

[2] Id.

[3] Id.

[4] Id.

[5] Da Silva Moore v. Publicis Groupe, No. 11-CIV-1279, 2012 WL 2218729, at *1 (S.D.N.Y. June 15, 2012).

[6] Acello, supra note 1.

[7] Id.

[8] Id.

[9] Id.

[10] Id.

[11] Id.

[12] Id.

[13] Id.

[14] Id.

Author: David Lee

David Lee is an Associate Editor with the Computer and Technology Law Journal. David has a Bachelor of Science Degree in Chemical Engineering from the University of Michigan and a Masters in Business Administration from the Johnson Graduate School of Management from Cornell University. He has over 12 years of consulting experience and has provided services to engineering, federal and local government, chemical and life science companies. At Rutgers David is also a member of the Moot Court Board. David is fluent in Korean and is a co-founder of the Michigan Alumni Golf Classic (MAGC) golf tournament.

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