Legal AI as Your eDiscovery Force Multiplier
The language of business today is data, and legal practitioners trying to build a case or uncover key evidence in an investigation are drowning in it. There are simply not enough hours in the day or dollars in any budget to manage many of the datasets facing legal practitioners in a brute force linear way. Thankfully legal professionals do not have to go it alone, because they can rely on the force multiplier effect that artificial intelligence (AI) provides.
A wide variety of machine learning algorithms and AI-powered data visualizations help legal practitioners dramatically accelerate time to evidence by making connections across a wide variety, velocity, and volume of data in a way that the unaided human mind simply cannot. AI assists legal practitioners by uncovering key facts to aid in decision-making and amplifying findings made by case teams across vast data volumes. While there may be a few who still resist and fail to recognize the power of AI in Technology-Assisted Review (TAR) workflows, the force-multiplier effect is at work across the legal industry whether they know it or not. Some of the greatest impacts are being realized in the discovery process even before document review.
What is a Force Multiplier?
According to the Department of Defense, a Force Multiplier is a capability added or employed by a combat group that significantly improves their combat potential, enhancing mission success probability. This concept is often referenced when a smaller force is facing a larger one. What does the concept of force multiplier look like when applied to the law? Simply put, doing more with less. From parsing through millions of documents and bits of data to making connections across a wide and disparate variety of data, Legal AI is the single most powerful force multiplier for legal professionals today.
Understand Data Sooner
One of the first and most daunting challenges faced by a legal practitioner in a new matter is understanding what the heck is in their potentially relevant data set. AI-powered solutions help lawyers and the entire case team understand the composition, concepts, and formats of ESI within their data sets in a fraction of the time.
Early Case Assessment (ECA), the process of evaluating the risk in prosecuting or defending a legal case, is a commonly used and misused term in the legal industry. The term ECA is often applied in a blanket fashion to any analysis of a case's merits, data, and facts at the outset of a matter. When it comes to evaluating the digital and financial risk of a case where eDiscovery is likely to be a major component, there is a critically important step that practitioners ought to undertake known as Early Data Assessment (EDA) while performing the overall ECA.
Why is EDA such a critically important step to undertake? Well, budgeting in an eDiscovery matter is quite lumpy, with the large proportion of cost only coming into play once data is processed and ultimately sent for document review. Rather than walking blindly from the collection step to processing, many savvy practitioners conduct this assessment technique to better wrap their hands around the data volume, key custodians, concepts, and formats residing within a data set.
Unsupervised data visualization helps practitioners understand the concepts, custodians, and context of data before a single document reviewer must click responsive. Case teams can simplify and expedite their case strategy by using social network analysis, communication visualizations that show who is speaking to whom, to validate and prioritize custodians.
Lawyers and case teams also rely on unsupervised learning to identify key concepts and weed out non-relevant concepts prior to review. Known as concept clustering, this visualization is powerful in reducing the volume of data that manually must be reviewed by humans, this drastically accelerating time to insight and reducing cost.
The single most valuable resource for lawyers and case teams today is time, not money. Therefore, the unsupervised data visualization and early understanding of key facts offered by AI-powered tools are so critically valuable. While it is true that most CIO's and Law Firms are not facing big data in a traditional sense, the volume, variety, and velocity of data they deal with are certainly growing and increasingly unwieldy.
Case teams today are facing a sea of social media posts, collaboration tool channels, audio, and video content in addition to the usual suspects of email, text, and documents. The brute force linear approach is cost and time-prohibitive, so tools that help reduce the amount of data pulled into the collection for review are impactful. I like to think of it as moving from a triage approach to one that is more laparoscopic in nature. AI-powered insights on custodians to prioritize, key concepts, sentiment, or the defined interests will help practitioners refine their approach and triangulate to the most likely valuable and responsive information.
Connect the Dots
With the influx of new data types and formats, it is increasingly harder for humans alone to make sense across the many diverse communication streams. Why does this matter? Well, take me for example... just this morning I answered a slack message, commented on a LinkedIn post, sent a text message and WhatsApp message, pinged an email, and left a voicemail... all before getting out of bed. If I was a custodian in a case, you would need to track my communication footprints across the myriad of platforms to make heads or tails of what I was doing.
Algorithms in next-gen discovery tools, powered by AI, can connect the dots by organizing communication by custodian, concept, timing, and sentiment regardless of the channel they are sent on. This cohesive picture helps practitioners identify patterns, uncover key concepts, and connect the dots more than any unaided human could possibly hope to do on their own. Data models, sentiment analysis, and concept clusters alike are helping humans amplify their insights and accelerate time to key evidence.
Triangulate Key Evidence
For in-house and Law Firm legal professionals, the benefits of AI-powered technology are undeniable. Savvy legal professionals and legal technology providers understand that the force multiplier effect is amplified when, as discussed above, multiple tools are used to continually reduce the amount of data that requires human review. What does that mean in practice? Well with each successive tool applied, you bring insights and a reduced data volume to the next tool or workflow you apply, effectively triangulating the most potentially relevant data to then push for human review.
Amplify Legal Decisions
Increasingly, in electronic discovery, the heavy lifting is occurring before we even get to the human portion of document review, but that does not mitigate the importance of the human reviewer. The deployment of AI-powered technology does not stop once humans begin reviewing data. Rather, AI in the form of TAR and prioritized review takes each human coding decision and amplifies it across the entire dataset.
Additionally, more next-gen electronic discovery technology providers are increasingly aggregating the insights from past cases into pre-built AI models that legal practitioners can apply at the outset of a case to improve the algorithm's decision making and supercharge time to insight.
Your Legal Force Multiplier
Increasingly, Machine learning and AI-powered technology solutions are the norm and not the exception. Massive and complex data sets combined with pricing pressure and unwavering time pressures are making the use of AI to amplify legal professionals a necessity and not a luxury. From accelerating time to evidence to making connections beyond the realm of naked human cognition, AI-powered tech is helping legal professionals in the David vs. goliath fight against big data in eDiscovery.