In the Financier Worldwide article “AI in e-discovery,” Jordan Blumenthal discusses the evolution of AI’s use in eDiscovery and highlights the need for attorneys who understand and can clearly explain the mechanisms of emerging AI-dependent technologies to clients and courts.

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According to Jordan C. Blumenthal, counsel at Redgrave LLP, over the last several years technology-assisted review (TAR) has moved beyond basic predictive coding workflows, sometimes called TAR 1.0, in which attorneys train an algorithmic model to rank documents for responsiveness before review begins in earnest.  “Those workflows significantly increased efficiency by allowing for attorney-informed automated prioritisation of large document sets and defensible productions without 100 percent eyes-on review,” he explains.  “That process can still be useful in certain cases, for many of the same reasons.

“But newer workflows that employ continuous active learning – or TAR 2.0 – allow for even greater efficiency and accuracy in many cases by largely eliminating the need to spend significant time training the model at the outset, allowing review to begin immediately, and integrating new information over time such that the model adapts to developments in a case.  Attorneys that are educated and comfortable with TAR 2.0 workflows can often save their clients significant time and money,” he adds.

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At present, however, deployment of AI in e-discovery is less prevalent than it could be.  “One of the most significant obstacles is the one faced by all new technologies in the law: attaining critical mass for acceptance,” says Mr. Blumenthal.  “For instance, although practitioners and even some courts have touted the value of TAR for a decade or more, litigators still often face pessimism and distrust of anything less than 100 percent eyes-on review.

“Given this challenging background, there is a distinct need for lawyers who not only understand these new technologies, but who can also explain their mechanisms, and their worth, in terms non-experts can appreciate.  Lawyers and technical experts working closely together can build on each other’s strengths to educate and benefit clients and courts, and to advance the profession’s acceptance of new technology,” he adds.

For Mr. Blumenthal, there are also pressing questions around how OpenAI’s ChatGPT, or other large language models (LLMs), may give rise to unethical misuse.

“Some lawyers have already found themselves in hot water after using such services and discovering too late that chatbots can invent information that sounds very real,” he says.  “Beyond the occasional lying chatbot, though, lawyers also need to be wary of other ethical pitfalls presented by their professional use of AI.  For example, a publicly available chatbot may well scoop up and retain any client information a guileless lawyer offers it, and could even potentially spit that confidential or even privileged client information out to a third party if given precisely the right user prompt.

“None of these ethics concerns are new, they are just new applications of the rules requiring truthfulness and confidentiality,” he continues. “Still, another long-established ethical obligation is to maintain the knowledge and skill necessary to represent a given client, particularly in sizeable, sophisticated litigation and transactions.  That expertise increasingly requires not just an understanding of but an ability to harness the full gamut of AI’s potential.”

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