ANALYSIS: First-Year Associates—To Be a Star, Learn About TAR – Bloomberg Law

First-year associates are often anxious to impress from day one. And legal tech proficiency can be a key component in laying the foundation of success early in an associate’s career.

One area of legal tech that first-year associates should learn about is technology assisted review (TAR), a machine learning process in which algorithms categorize electronic documents, including emails, presentations, and word processing, based on input from reviewers in litigation and other legal matters. Understanding how to utilize TAR can increase efficiency and consistency in discovery and reduce review costs—outcomes that can go a long way to advancing a new associate’s career and impressing firm leadership.

Opportunity Amid Tech Hesitancy

According to Bloomberg Law’s 2021 Legal Technology Survey, only 13% of law firm respondents who reported using e-discovery technologies said they use some version of TAR, compared to roughly one-third or more who say they use certain other technologies.

This isn’t surprising; much of the the legal industry is, by and large, conservative, which explains lawyers’ natural aversion to and slow adoption of emerging technologies—especially those that hand the keys over to an artificial intelligence (AI) algorithm. Many lawyers may also feel threatened by any tool that could drastically reduce their workload, making it more difficult to reach their annual billable hour requirements. (Of course, it’s also possible that respondents are unknowingly using TAR but not recognizing “technology assisted review” by name, thereby skewing the results downward.)

But law firms also have to evolve with the times. And, 50% of law firm respondents in the survey reported that a shortage of tech-savvy users is a barrier their firm faces in their attempts to utilize legal tech. So the fact that so few respondents are using TAR only highlights the valuable opportunity that new associates have to fill the tech expertise gap by demonstrating their knowledge and proficiency.

Moreover, considering that 74% of in-house counsel respondents in the 2020 version of the survey reported that they expect outside counsel to increase their use of legal tech and become more efficient, new associates can further leverage their knowledge of TAR with clients and potentially boost the firms’ ability to attract new business.

Three Things to Know About TAR

To begin learning about the technology whose utilization has been notably referred to by Magistrate Judge Andrew J. Peck as “black letter law”, keep the following TAR facts in mind:

1. TAR comes in two primary methods.

There are multiple other versions of TAR in existence and being developed, but understanding these basic types will get you started.

TAR 1.0 consists of a subject matter expert (SME) conducting an initial review (usually for relevancy, responsiveness, or privilege) of “seed sets” of documents, and their review decisions are subsequently used to train the software. The software then reviews and categorizes documents based on the coding decisions of the SME.

TAR 2.0, or continuous active learning (CAL), also includes an initial review by attorneys (though not necessarily SMEs), but the software continues to learn after the initial coding decisions are integrated. There is no clear line of demarcation between training and review going forward. They are concurrent: Attorneys review documents and the software integrates the coding decisions into its algorithm at the same time, speeding up the review process.

2. While precision is important, recall is the key metric.

Precision gauges the TAR software’s ability to accurately classify specific documents in a database. Recall, on the other hand, measures how well the TAR software retrieves all documents of a specific type in a database. For the purposes of litigation, the ability to capture all the relevant documents in a universe of electronically stored information (ESI) is worth its weight in gold, making high recall (generally considered to be at least 80%) a desirable measure for a robust TAR software program.

3. TAR doesn’t replace humans; it just enhances our efforts.

Attaining billable hour requirements for the year is critical, but relax: Implementing TAR doesn’t signal an AI takeover. What it does do is afford greater speed, accuracy, and efficiency in the review process, so that the computer software does the heavy lifting instead of tired human eyes that are prone to making mistakes.

Knowledge of TAR May Carry You Far

While some lawyers may shy away from using AI, first-year associates should view that reluctance as an open door to learn a technology that is becoming an indispensable tool in the practice of law. Doing so may very well prove an important factor in gaining responsibility that can distinguish new lawyers as they embark on a rewarding career.

Bloomberg Law subscribers can find more information about Technology Assisted Review on our Litigation Intelligence Center’s Core Litigation Skills Toolkit page.

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