The evolution of artificial intelligence (AI) over the last decade has been nothing short of revolutionary. Innovative technologies have been developed leveraging AI that have drastically shifted the way we carry out tasks, research, and analysis. One of the fundamental shifts that has occurred in the realm of AI involves moving from extractive AI to generative AI. Think of Siri or Amazon's Alexa. Answers given by them were based on pattern-matching user queries to relevant information in existing databases, this is extractive AI. However, technology has seen a surge as AI learns to generate or create responses and content, rather than just extracting them. That's generative AI for you. To truly appreciate the changes happening in the legal field thanks to AI, we need to understand how these technologies function and what they bring to the table.
Extractive AI and generative AI are two different types of artificial intelligence that handle data in unique ways, especially in the legal field that involves a lot of textual data. Imagine you're a lawyer looking for a specific law or past case to support your argument. Extractive AI works like a super-powered search engine: you give it a question or topic, and it sifts through vast amounts of legal documents to 'extract' exact chunks of text that contain the answer or relevant information. This is commonly done using Natural Language Processing (NLP) techniques that allow the system to understand and find information based on context(a paragraph or a document) and keywords. For example, if you ask an extractive AI for cases involving "intellectual property rights," it will pull up exact excerpts from cases where these words appear, much like highlighting sentences in a book that directly answer your query.
Back in 2017, when the legal tech industry was only scratching the surface of AI technology, CaseMine was leading the pack with the introduction of CaseIQ. This AI-powered tool demonstrates what extractive AI is capable of. CaseIQ identifies relationships between words and concepts, targeting key passages directly from an extensive database of primary and secondary legal sources. The importance Matrix within CaseIQ sifts through judgments to spotlight the pivotal sections by tracking their citation frequency, offering a visual guide to the most influential parts through a nuanced, colour-coded relevance scale. CiteText complements CaseIQ by distilling the interpretation of legal precedents, employing extractive AI to present the crux of how subsequent courts have applied and understood a judgment, thus streamlining legal research by highlighting authoritative applications of case law.
Generative AI, on the other hand, is like an inventive assistant that can draft documents or create new content. If you provide it with a prompt, such as "write a contract clause for intellectual property protection," it doesn't just find and copy an existing clause; instead, it 'generates' a new one tailored to your needs. It uses Large Language Models (LLMs) to produce text that is coherent and contextually relevant based on a given prompt. This AI uses what it has learned from a large database of legal texts to generate original content, which can sometimes seem as though a human lawyer has written it. Its creation doesn't recycle exact text from its database but combines its learned knowledge in new and unique ways, reflecting current legal standards and practices.
Following CaseIQ's remarkable success, CaseMine moved a step further in 2023 by introducing AMICUS, showcasing the full potential of generative AI. This intelligent assistant allows for conversational research(not only fetches on-point case laws and statutes but intelligently reasons their applicability, ensuring you receive the most pertinent answers to your complex legal questions), legal document drafting(drafting of complex legal documents with precision and speed, ensuring compliance and reducing the margin for human error), and summary generation(generate concise, real-time summaries with unparalleled accuracy, transcending conventional headnotes and ensuring no critical information is overlooked or misinterpreted). Amicus is not just an improvement but a game-changer. Built on a vast repository of premium legal content, this AI assistant provides vetted, comprehensive legal results, authenticated with verifiable and citable authorities.
In legal research, both extractive and generative AI play pivotal roles that complement each other to enhance efficiency and thoroughness. Extractive AI excels in navigating through extensive and complex legal documents to identify and extract key pieces of information, which is essential given the detailed and dense nature of legal texts. By quickly pinpointing relevant facts, statutes, and precedents, extractive AI saves researchers from the time-consuming task of manually reviewing each document. On the other hand, generative AI leverages the information extracted to create coherent summaries, draft legal documents, and predict possible legal outcomes. This application of AI not only streamlines the writing process but also offers insightful perspectives by synthesising vast amounts of data that might otherwise be overwhelming for a human to analyse. Therefore, when extractive and generative AI work in tandem, legal professionals can harness their combined strengths—effective information retrieval and sophisticated data processing. This synergy ensures comprehensive research and high-quality document creation, ultimately leading to more informed decision-making and a more efficient legal process.
Disclaimer - This is a sponsored post by CaseMine.