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Litigation boutiques are accustomed to going to battle against even the biggest firms — and emerging victorious despite being outnumbered and metaphorically outgunned when it comes to navigating the tsunami of potentially relevant data. Shrewd litigation boutique lawyers have long leveraged technology to get a leg up in cases even when facing long odds. As data volumes continue to grow at a breakneck pace, with no signs of abating, these practitioners are well positioned to leapfrog less tech savvy law firms. The right technology can be a secret weapon that makes them faster, smarter and more impactful for their clients. 

There is a concept in military strategy that sums up how many litigation boutiques are able to match even the biggest, baddest firms and emerge victorious: the force multiplier. The Department of Defense defines “force multiplier” as “[a] capability that, when added to and employed by a combat force, significantly increases the combat potential of that force and thus enhances the probability of successful mission accomplishment.” In the business context, the definition is even simpler: tools that amplify your effort to produce more output. 

Consider the difference between a military of cavalrymen with muskets and that of trained Navy Seals. The right tools amplify and empower a human to make more impactful actions and decisions. Applying AI and machine learning to legal technology reduces the cognitive burden to enable rapid, accurate decision-making in a fraction of the time a more traditional approach requires. It also amplifies these decisions so fewer discrete decisions must be made. The result is greater data classification, with increased accuracy in a shorter period of time. 

AI and ML as a Force Multiplier 

This is not the first or the last time that you will hear the phrase force multiplier in the context of advanced machine learning and AI. In fact, the DoD started the Joint Artificial Intelligence Center (JAIC) as the DoD’s AI Center of Excellence to provide a critical mass of expertise to harness the game-changing power of AI. The DoD sees technology, including machine learning (ML) and AI, as a force multiplier as powerful as the musket or tank in prior centuries. The organization released the DoD AI strategy, which highlights the threat mitigation, force multiplication, and environmental factors driving advanced investigation and adoption of AI to protect the nation. 

One quote from the strategy that is especially chilling and insightful: 

AI is poised to transform every industry and is expected to impact every corner of the [Defense] Department, spanning operations, training, sustainment, force protection, recruiting, health care and many others...With the application of AI to defense, we have an opportunity to improve support for and protection of U.S. service members, safeguard our citizens, defend our allies and partners and improve the affordability and speed of our operations.

The DoD and many industries outside of legal see the impending impact of AI and ML as well as the strategic benefits of adopting broadly and early. This, to their mind is not something that can be ignored. No amount of burying our heads in the sand will change the adoption of technology and fundamental ways data is changing the world around us, so even the historically glacial pace of the federal government has had to catch up. 

Applying Force Multipliers in Ediscovery

What does the military concept of force multiplier look like applied to a litigation boutique? In the most basic terms: doing more with less, a theme near and dear to many a boutique practitioner’s heart. In the context of ediscovery, this means leveraging fewer people and less money to surface key evidence and begin fact-driven case development. There are three major ways that technology is helping legal professionals gain insights and access to evidence with less human effort required.

Early Case Assessment

Force Multipliers: TAR 2.0, automated batch refresh, advanced data visualization

One area practitioners are seeing a force multiplier effect is early stage culling. Advanced early case assessment (ECA) dramatically reduces the number of man-hours necessary to get key evidence in even the largest data set. Additionally, tools like active learning models, automated batch refresh, and advanced data visualization enable a handful of practitioners to delve through larger volumes of data — that previously took a basement full of reviewers — in a fraction of the time. 

Prior to the review phase, advanced data visualization enables case teams to identify gaps in their collection, prioritize key custodians and topics, and eliminate non-relevant information in a fraction of the time and expense of prior models. Rather than waiting for a human to touch each and every document, broad decisions are amplified across the entire data set to dramatically reduce the volume of data that even has to be reviewed. For a litigation boutique, this means a lean case team can match and surpass the insights of literally hundreds of review attorneys taking a morte linear approach on a large data set. 

Data Investigation

Force Multipliers: Active learning, data visualization, social network analysis, conceptual clustering, AI model sharing

Advanced data parsing and visualization that capitalizes on AI and unsupervised learning models allows practitioners to gain insights into their data set in a fraction of the time. Social network analysis (who communicated with whom and with what frequency) assists with custodian prioritization; data visualization and clustering assist in scoping and prioritization of a review; and active learning models amplify these insights across the entire data set, surfacing increasingly relevant data at the outset of a matter. 

Additionally, new developments like AI model sharing allow practitioners to port lessons learned in prior matters or different data sets into their new matter. So rather than starting at zero, they have the benefit of prior insights and review hours to jump start their analysis. The sum total is better information to establish case development and settlement posture earlier, without expending substantial time and money. 

Document Review

Force Multipliers: Active learning, data visualization, social network analysis, conceptual clustering, AI model sharing

One of the most common examples of force multiplier at work in law is in the document review phase of ediscovery. Just a few short years ago, it was not uncommon to have thousands of contract attorneys in a room going through millions of documents in a linear document review. 

Whether the team is using the insights from other matters by leveraging AI model sharing or starting further along in developing their insights through social network analysis and concept clustering, the result is a drastic reduction of time to insight. Further, the AI-powered prioritization afforded by deploying Active learning compounds this reduction of time to evidence. 

For the litigation boutique case team, this translates to an increase in review rates of more than 60% compared to linear methods (that’s 88 docs/hour), and are able to more accurately get through volumes of documents. In the dated linear review approach, a review attorney would only get through 50-60 documents an hour and there was limited ability to accelerate the timeline, aside from throwing more bodies at the problem which is not time or cost effective. The results have been so impressive that DISCO even guarantees an on-time on-budget result of managed review. 

The future 

Much in the way a tank amplifies human capacity in battle when compared to a person on foot or horse, advanced analytic tools are broadly allowing leaner teams to reduce time to insight and dramatically reduce the cost associated with ediscovery. This trend is only on the rise, but litigation boutiques have been ahead of the curve in deploying these game-changing methods.

While not every case today takes advantage of even the most basic technological benefits (think email threading and AI-driven prioritization at a minimum), the day is not too far away when there will be a shift to the minority of cases NOT taking advantage of these — and even more advanced — tools. Savvy boutiques can gain a substantial strategic advantage by embracing next-gen technology that provides these force multipliers while the competition is late to the party.


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