Extract from an article by Leonard Deutchman
Artificial intelligence (AI) tools can be used in reviews of a substantial or overwhelming number of files to decrease the number of reviewers needed and spot errors or omissions. A typical AI tool can work by having a knowledgeable reviewer (or two or more, depending upon the size of the dataset and the deadline for review to be completed) review a quantity of files. The AI tool will then automatically review the next files, of the same quantity, and tag them as the reviewer did the initial set (e.g., responsive, nonresponsive, privileged, needs redaction, etc.). The reviewer reviews the set done by the AI tool and makes corrections, thereby “teaching” the AI application. The AI application will then review the third set, which the reviewer will review and correct. Each review set done by the AI application should contain fewer errors than the previous one, until AI review produces virtually no errors. Once the AI application has, then, thoroughly “learned” how to review, the reviewer can simply let the application review all remaining files. The reviewer(s) can then spot-check the entire set and, unless a problem with the AI review has been detected, complete redactions and produce responsive documents. One additional benefit of AI review is that reviewers can easily include firm counsel knowledgeable of the issues in the matter. If such counsel understands how to use AI applications, they can simply go ahead; if they need assistance, they can work with managed review provider counsel, who can initially instruct them and then oversee their work as the review progresses. Once review is complete, the production to opposing counsel can be finished by the e-discovery provider or by the firm if such is done in-house.
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