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Transforming Responsive and Privilege Reviews with AI By Brett Tarr incorporating AI tools, but only 7.5 percent have actually begun to use them. At the same time, 72 percent of respondents believe that the pace of change in the profession will only continue to increase. REDISCOVERING DISCOVERY

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“AI

” is a lofty term that doesn’t have a universal definition. And in fact, AI is not even new. The field of research in artificial intelligence was established at Dartmouth College in 1956. The term “machine learning” was coined three years later by Arthur Samuel, who taught a computer to play checkers. What is new is that a “perfect storm” convergence of advancements in the last decade — better algorithms, increased computing power, sophisticated processing techniques and the advent of big data — has brought AI out of theory and into

operation. The result is that industry after industry is being transformed. Last year, the AI researcher Andrew Ng announced that “AI is the new electricity,” and he joked that the only industry to be unaffected by AI might be hairdressing. Mr. Ng has since been proven wrong by L’Oreal, which recently launched a 3D hair color simulation app powered by AI. Legal leaders are left trying to sort through all the generalized AI hype so it can be put to work in practical ways. The adoption is happening slowly. Last year’s study from Altman Weil found that 29 percent of firms are exploring their options for

The implications of this change may be particularly profound in the areas of privilege and responsive reviews — areas where challenges are rapidly evolving. Electronically stored information (ESI) is appearing in huge scales and a proliferation of forms. With this growing volume, turnaround times become impossible without employing armies of reviewers. Ever since Judge Andrew J. Peck accelerated the adoption of technologically assisted review from the bench in Da Silva Moore v. Publicis Groupe, litigators and corporate counsel have been exploring what it means to introduce technology to discovery. For many of us, that has meant exploring predictive coding and technologyassisted review. However, this technique has two significant challenges that make it difficult to employ in practice. First, predictive coding requires a subject-matter expert to hand label documents to create a “seed set.” Typically, this expert is a senior attorney with practical matter experience who is unlikely to have the time to devote to this effort. Second, predictive coding is constrained to looking within the four corners of the document, which means that it doesn’t take into account any of the broader ecosystem of documents where the most valuable context lies. At Caesars Entertainment, where I serve as Chief Counsel for E-Discovery continued on page 62

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