How the Right Legal Team, AI, and a Tech-Forward Mindset Can Optimize Review
To keep up with the big data challenges in modern review, adopting a technology-enabled approach is critical. Modern technology like AI can help case teams defensibly cull datasets and gain unprecedented early insight into their data. But if downstream document review teams are unable to optimize technology within their workflows and review tasks, many of the early benefits gained by technology can quickly be lost.
In a recent episode of Law & Candor, I was happy to discuss the ongoing evolution of document review—including the challenges of incorporating available technologies. We explored some of the most pressing eDiscovery challenges, including today’s data complexity, and how to break through the barriers that keep document review stuck in the manual, linear review model. We also discussed the value of expertise and where it may be applied to optimize review in various phases of a project. Here are my key takeaways from our conversation.
Increasing data complexity challenges and entrenched manual review paradigms
Today’s digital data—a wellspring of languages, emojis, videos, memes, and unique abbreviations—looks nothing like the early days of electronic information, and it is certainly a universe away from the paper world where legal teams had to plow through documents with paper cuts, redaction tape, and all. Yet, that “paper process” thinking—the manual, linear review model—still has a firm hold in the legal community and presents an unfortunate barrier to optimizing review.
The evolution is telling. As digital data began to take over, the early AI adopters and the “humans need to look at everything” review camps staked their ground. Although the two are moving closer together as time goes on, the use of technology is not as highly leveraged as it could be, leaving clients to pay the high costs of siloed review when technology-enabled processes could enhance accuracy and reduce costs. There are a variety of factors that can contribute to this resistance, but it may also be simply a matter of comfort; it’s always easier to do what you already know in the face of changes that may seem too difficult or complex to contemplate.
For the best result, know when and where to leverage available technologies in the review process
Human beings are certainly a core component of the document review process, and they always will be, but thinking about the entire review lifecycle strategically, from collection through trial preparation, is critical when it comes to understanding where you can gain value from technology. Technology should be considered a supplement to—not a substitute for—human assessment and knowing where to use it effectively is important.
When considering the overall document review process, two key questions are: Where can you get more value by using technology? And where are the potential areas of either nuanced or high-risk communications that may require a more individualized assessment? The goal, after all, isn’t to replace humans with technology, but rather to replace outmoded contract review factories with smarter alternatives that leverage the strengths of both technology and human expertise. A smaller review team, coupled with experts who can effectively apply machine learning and linguistic modeling techniques in the right place, is a much more efficient and cost-effective approach than simply using a stable of reviewers.
Technology buyers need to understand what a given tech does, how it differs from other products, and what expertise should be deployed to optimize its use
Ironically, the profusion of viable tech options that can applied to expedite document review may be off-putting, but this is a “many shades of gray” situation. Many products do similar things and it is important to understand what the differences are—they may be significant. Today’s tools are quite powerful and layering them alongside the TAR tools that document review teams have become more familiar with is what allows for the true optimization of the review process. These tools are not plug-and-play, however. You need to know what you’re doing. It takes specific expertise to be able to assess the needs of the matter, the nature of the data, the efficacy of the appropriate tools, and whether they’re providing the expected result.
Collaboration is still the critical core component of document review
And let’s not forget that document review is a collaborative process between client counsel, project managers, and the review team. Within this crucial collaboration, specific expertise at various points in the process ensures the best result, including:
• Expertise in review consulting to assess the right options for both the data that’s been collected and the project goals.
• Individualized experts in both the out-of-the-box TAR technology as well as any proprietary technology being used so that the tech can be fine-tuned to optimize the benefits.
• A core team of expert human reviewers with the appropriate skills.
Experimentation with technology can help bridge the divide
With so many products available to enhance the document review workflow, it makes sense to test potential options. Running a parallel process for a particular aspect of the review to get comfortable with a new product can be very helpful. For example, privilege review, which is an expensive part of the review process, could be a good place to test an alternate workflow.
An integrated approach works best
The bottom line is that an integrated approach, advanced technology, and human expertise, is the best solution. The technology to increase the efficiency and effectiveness of document review is out there and most of it has been shown to be low risk and high value. The cost-effectiveness of an integrated approach has been shown over and over again: In using the appropriate technology, budgets can be reduced, and savings reinvested in new matters.
It is up to the client and their legal and technology teams to work together in deciding what combination of tools makes the most sense for their organization and matter types. Just make sure to call upon those with the appropriate expertise to provide guidance.
For more examples of how AI and human expertise are optimizing review, check out our review solutions page.