How the Advent of AI is Revolutionizing Class Action Lawsuits

Class action lawsuits have long been a cornerstone of the legal system, allowing individuals with similar grievances to collectively seek justice. However, the landscape of class action litigation is undergoing a profound transformation with the advent of technology. According to Statista, the global legal tech sector was $28 billion in 2022 and is expected to reach over $35 billion by 2027.

One such technology that has revolutionized the legal sector is artificial intelligence (AI). As AI technologies continue advancing, they are reshaping how legal professionals approach, analyze, and litigate class action cases.

In this article, we will explore how AI is revolutionizing class action lawsuits, from case identification to settlement distribution.

Understanding Class Action Lawsuits

A class action lawsuit is a legal proceeding in which a group of individuals collectively brings a claim against a defendant or defendant. This legal mechanism is employed when many people share similar grievances against a common party. Typically, these cases involve product liability, securities fraud, consumer protection, or employment disputes.

One key feature of class actions is the appointment of a representative plaintiff, who acts on behalf of the entire class. This representative must have a typical claim of the class members and adequately represent their interests. The court must certify the class before the lawsuit can proceed as a class action.

There have been several examples of such class action lawsuits. For instance, the tobacco settlements for $206 billion and the BP Gulf of Mexico Oil spill for $20 billion are examples of class action lawsuits.

There are also multidistrict litigation (MDL) lawsuits that work with a similar approach. MDL is a legal procedure that efficiently handles complex civil cases involving multiple parties and common issues. The primary goal of MDL is to consolidate pretrial proceedings and streamline the litigation process, avoiding duplicative efforts and promoting judicial efficiency.

One example of an MDL is the ongoing Camp Lejeune water contamination lawsuits. According to TorHoerman Law, several lawsuits filed by military and their family members have been consolidated into an MDL. This MDL, numbered 2911, looks after several Camp Lejeune lawsuits.

In fact, these cases have increased so much that even the government had to intervene to ensure justice for the victims. The Congress had passed the Camp Lejeune Justice Act of 2022 to help the victims. It aims to offer monetary reimbursement for health care and disability benefits to individuals impacted by the water contamination in Camp Lejeune.

AI in Case Identification and Triage

One of the most significant challenges in class action litigation is identifying potential class members and determining the viability of a case. Traditionally, legal professionals had to manually sift through vast amounts of data, a time-consuming and resource-intensive process. Enter AI, with its ability to rapidly analyze massive datasets, identify patterns, and extract relevant information.

AI-powered tools are now employed to streamline the initial phases of class action lawsuits. Natural Language Processing (NLP) algorithms can quickly review legal documents, emails, and other sources to identify key information. This accelerates the case identification process and ensures a more comprehensive review of relevant documents.

The legal NLP community is on a growth spurt. Class I papers have decreased today, from 92.59% earlier to 48.70% in 2022, whereas the percentage of Class III papers increased from 3.70% to 39.13% in 2022. These figures demonstrate the Legal NLP community's growing dedication to reproducibility.

Moreover, machine learning algorithms are increasingly utilized for case triage, helping legal professionals prioritize cases based on their likelihood of success. By analyzing historical case data, AI models can objectively assess a case's merits. They can guide legal teams to allocate resources efficiently and focus on cases with higher chances of success.

Predictive Analytics in Class Certification

Class certification is a critical juncture in class action litigation, determining whether a case can proceed as a class action. AI-powered predictive analytics are invaluable in assessing the commonality and typicality of class members' claims at this stage.

Machine learning models can analyze past rulings, legal precedents, and case outcomes to predict the likelihood of a court certifying a class. This predictive capability enables legal professionals to better strategize their approach to class certification, improving their chances of success.

A TechCrunch article talks about such a company named Darrow. It has developed an AI-based data engine that takes a large amount of data to search for class action litigation requirements. It searches across areas such

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