A recent decision from Judge Kim in the Northern District of Illinois allowing the use of Technology Assisted Review (“TAR”) is wonderfully articulate in explaining the benefits of technology in handling both the woes of volume and the complexity of using search terms inherent in ediscovery. It’s concise, and worth a read.
In Livingston v. City of Chicago, the parties agreed, over a prolonged process, to search terms that would define the set of data to be identified and collected, then loaded into the review platform. The collection included 192,000 unique emails or a total of approximately 1.3 million pages of documents. Plaintiffs then wanted the City to produce all documents with no review or redaction subject to an FRE 502(d) order and objected to the City’s plan to use TAR to identify documents to be reviewed. Yes, you read that right. Judge Kim expressly rejected plaintiffs’ arguments that it 1) was entitled to all documents without review, 2) should be entitled to collaborate with the City in establishing the TAR protocol to be followed, and 3) that the City should go back to the beginning and use TAR to identify the initial set for review, and allowed the City to use TAR to cull the data identified by the search terms to provide responsive documents:
Plaintiffs’ insistence that the City must collaborate with them to establish a review protocol and validation process has no foothold in the federal rules governing discovery. Moreover, using TAR on the entire ESI collection—when, as Plaintiffs aptly point out, the parties spent nearly a year litigating the protocol for collecting and searching the City’s ESI—would be wasteful and unduly burdensome, and would further delay the resolution of this almost four-year-old case.
Also key to the Judge’s decision was that “the parties agree that generally TAR is a far more accurate means of producing responsive ESI than manual review or keyword searches.(R. 289, Pls.’ Mot. at 7; R. 300, Def.’s Resp. at 5.)”. It feels like plaintiffs’ shot themselves in the foot stating that outright. Judge Kim’s decision is the textbook argument to follow in advocating for the use of TAR, and the practice is good for all parties, and for the economics of litigation advocated by FRCP 1 calling for the just, speedy and inexpensive determination of every action.
Simply put, TAR can be an effective part of the process in identifying responsive information faster. Any good ediscovery attorney or legal professional can tell you that the only way to truly find responsive search terms is to 1) talk to the custodians that created, sent and received the ESI you are looking for, and 2) look at the data and see for yourself. Anything short of those two methods is just a big fat guess. Now, the more educated your guesses are, the better you may fare, but it’s more likely that the education you attain through trying to identify search terms will help you better craft RFP’s that require the responding party to look at data to find responsive information. The one exception to that rule is if a requesting party already has responsive data from some other source that provides insight into search terms.
The reality is that the responding party is in the best position to identify search terms that will identify responsive documents. But to compound the problem, it’s impossible to know responsive rates to hits on search terms until you get well into review. So, even if a responding party provides search term hit reports to opposing counsel to justify and negotiate search terms, there’s no way of knowing what percentage of those hits are responsive. Practically speaking, setting up a review takes time and a lot of money, and the other side doesn’t want to wait for that. We are constantly anxious to define the process so that everyone knows what to expect before we have all of the information. As a result, we are often putting the cart before the horse. A shortcut to helping truly identify responsive search terms and reduce non-responsive search term creep is to allow technology to assist with review.
Yes, as technology has advanced over the last decade since Judge Peck’s decisions in Rio Tinto, Technology Assisted Review has taken on new names — Computer Assisted Learning, Active Learning, TAR 2.0, etc. And there are variations in how each different technology you may employ works. But advancements in the process notwithstanding, the process of using the technology to assist in review is still just what it was called back in 2015. The technology allows a computer to begin identifying responsive documents using coding decisions from attorneys or legal professionals that are being applied. As the technology has advanced, it’s gotten better and more nuanced, and therefore more accurate at ranking documents with a score for responsiveness based on inputs received. In short, using TAR allows for 1) documents to be produced faster on a rolling basis, 2) less money to be spent on linear review of non-responsive documents, and 3) can allow attorneys to focus on the documents in the case vs. expending resources on non-responsive materials. These apply to both sides of the V, and even in asymmetrical litigation where one party has all of the discovery.
Judge Kim’s decision is just one of more than 55 decisions in eDiscovery Assistant (detailed by jurisdiction on the map above) on various issues in using TAR that have evolved since the process was accepted by Judge Peck in 2015. Courts are not just accepting of the process, they are digging into it and understanding the value and complexity of the process. For example, in Lawson v. Spirit Aerosystems, Inc., the court allowed for cost-shifting of TAR expenses where the plaintiff:
was unwilling to abandon the largely non-responsive ESI dataset and instead sought continued review via TAR that unnecessarily perpetuated and exacerbated ESI/TAR expenses. The TAR process ultimately yielded a responsiveness rate of only 3.3%. Even the documents that were technically responsive were of marginal (if any) relevance above and beyond what Spirit produced outside of the ESI/TAR process. Thus, ESI/TAR process became disproportionate to the needs of the case.
These more recent decisions on TAR advocate for what most ediscovery professionals have been saying for years — the volume and complexity of ediscovery demands that technology be applied effectively to make decisions based on data. The framework of the Federal Rules, while not without loopholes, is sufficiently in place to handle the issues presented by the use of technology. The courts are on board. You need to be too. Whether that means the use of analytics at the outset of collecting data, TAR after collection, or analytics to analyze a production you received, not using technology today is doing your client an injustice. You learn more, save more and do a better job with technology.
