AI can help consumers by providing a kind of “legal service” to clients who otherwise could not afford a lawyer. The free DoNotPay service, created by a 19-year-old, is an AI-powered chatbot that allows users to dispute parking tickets in London and New York. In its first 21 months, it took on 250,000 cases and won 160,000, saving users more than $4 million in fines. The same program helps consumers file data breach lawsuits against Equifax up to $25,000 — though it can`t help them litigate their case. Every lawyer who has ever researched with Lexis or Westlaw has used legal automation. Find relevant cases in earlier eras that involved the laborious process of finding top note numbers and separating in paper volumes. But AI takes research to the next level. For example, Ross Intelligence uses the power of IBM`s Watson supercomputer to find similar cases. It can even respond to inquiries in plain English. The power of AI-powered research is staggering: using common search methods, a bankruptcy lawyer found in 10 hours a file almost identical to the one he was working on. Ross` AI found it almost immediately. Lex Machina`s legal analytics platform has a variety of features designed to help lawyers with their legal strategy. For example, the Timing Analytics feature uses AI to predict an estimated time when a case is heard by a specific judge.
For example, when lawyers use AI-powered software to review documents, marking certain documents as relevant, the AI learns what kind of documents to look for. Therefore, it can identify other relevant documents more accurately. This is called “predictive coding.” Predictive coding offers many advantages over old-fashioned manual document verification. Among other things: let us show you how to automate the extraction of key clauses and provide better legal services to your companies and clients. In one case, an international government investigation had to organize a review of 12.5 million multilingual documents within a tight production deadline. Using Reveal-Brainspace`s continuous multimodal learning (CMML), the client was able to significantly reduce the exam population from 1.8 million to 280,000 documents, which corresponds to an 85% reduction in assessment volume. In the end, the savings in this case amounted to approximately 19,000 exam hours and over $750,000. Other AI-powered contract review platforms that cover legal due diligence include: While almost every industry relies on ML for automation in one way or another, its large margin of error is particularly problematic for legal work. Unlike a commercial department, which would not suffer any consequences for the hunt for a bad lead, the stakes of the legal department for Swiss Cheese contracts are far too high. While sales are happy that their ML AI sends 70% of emails to the right people, Legal would explode if only 70% of contract clauses were valid. Legal must therefore take special precautions in its automation processes and use a more strictly controlled AI for document generation and analysis.
The legal industry has embraced AI to speed up processes such as due diligence, document review, and rapid analysis of contracts during litigation to determine quality, completeness, and relevance. This is done by establishing predefined criteria for training data models to predict case outcomes. That equates to 36,000 hours of legal work by its lawyers and loan officers, according to the company. COIN was developed after the bank detected an annual average of 12,000 new wholesale contracts with glaring errors. Every trial and court case requires careful legal research. However, the amount of links to open, cases to read, and information to consult can overwhelm lawyers who have little time to do research. Lawyers can use the natural language search feature of the ROSS Intelligence software by asking questions and obtaining information such as recommended reading, relevant case law, and secondary resources. As it stands, AI-powered software is improving the speed, accuracy, and efficiency of document review.
Once these documents are annotated, AI can search for additional documents and sort them through them much faster than humans. Other software products also combine machine learning and legal analysis to help lawyers with their legal research, but with limited coverage. For example: Luminance`s Legal Inference Transformation Engine (LITE), founded by mathematicians at the University of Cambridge, uniquely combines supervised and unsupervised machine learning to provide the most robust and powerful legal analytics platform available to lawyers. Luminance`s technology can read and understand legal documents in any language and jurisdiction, instantly displaying the most relevant information and significantly reducing document review time. Companies that don`t take advantage of AI efficiency may lag behind competing with those that do, at least to the extent that customers insist on fixed-rate billing. In other words, lawyers who understand technology and learn about the latest developments in legaltech. can have increasing value for their businesses. Predictive coding has been widely accepted by U.S. courts as a method of reviewing documents since the 2012 decision in Da Silva Moore v.
Publicus Groupe. Document creation and analysis are stages of the life cycle that require an artificial intelligence system to understand the content of a contract and the law itself. However, ML AIs aren`t trained to do this – they`re simply designed to recognize patterns and respond to them. The way an ML AI would learn to write and read contracts is by analyzing thousands of documents. However, no matter how smart AI is, it`s not possible to learn the whole law just by reading legal contracts. As a result, ML AI is quite unreliable when drafting or analyzing legal documents. Lawyers are already using AI to review documents during litigation and due diligence, analyze contracts to determine if they meet predetermined criteria, conduct legal research, and predict business outcomes. Another important issue is the lack of integration with existing platforms for reviewing legal documents.