Artificial intelligence (AI) in legal work can seem like a complex, tech-heavy topic. However, understanding the terminology, the layers and hierarchy of the terms, and how it applies to the legal field is critical for every lawyer practicing today. Here, Gavel's founder and CEO, who practiced law for many years and now runs a legal software company, breaks the AI terminology down into digestible sections, explaining their relevance and use cases for lawyers.

AI Generally: What is the Broader Concept, and How Does it Apply to Law Firms

What is AI and legal AI?

AI, or artificial intelligence, is a broad term that dates back to the 1950s. It refers to the capability of a machine to imitate intelligent human behavior. In essence, AI encompasses any technology that mimics or simulates human intelligence. AI can also be a rules-based system that can give intelligent answers based on rules. For lawyers, AI can streamline tasks such as document review, legal research, and client management. Tools like ROSS Intelligence use AI to perform legal research by sifting through vast amounts of legal texts to identify relevant information. Kira Systems utilizes AI to assist with contract review and due diligence by extracting and analyzing key clauses from documents. Gavel uses AI to automate any area of the law, allowing users to automatically generate work product.

Machine Learning: A Subset of AI and Helping With Predictive Analytics in the Law

Machine learning is a subset of AI. Unlike traditional rule-based systems where you configure “if this…then that” logic rules, machine learning involves teaching computers to make predictions or decisions based on data. These algorithms improve their performance over time through experience and data analysis, without being explicitly programmed for each task.

In the legal field, machine learning can be used for predictive analytics, such as forecasting case outcomes or identifying trends in case law. Lex Machina uses machine learning to provide insights into litigation trends and outcomes, helping lawyers develop case strategies based on historical data. Everlaw leverages machine learning for e-discovery, identifying relevant documents and predicting case timelines.

Generative AI: Going Deeper to Generate Text, Workflows, and Intake Information

Generative AI is a type of machine learning that generates new content. It can produce text, images, videos, or code based on the data it has been trained on. Generative AI can be particularly useful in automating the drafting of legal documents. There are several software companies in this space that use generative AI to create contract templates and draft legal documents. Other software tools employ AI to review and approve contracts, ensuring they meet specific legal standards and compliance requirements.

Generative AI can also be used to intake documents and information and automatically build rules based workflows. Gavel uses generative AI in this way.

Large Language Models (LLMs): A Specific Type of Generative AI

LLMs, or large language models, are a specific type of generative AI focused on generating natural language text. They are trained on extensive datasets of text to learn the style, structure, and content of the training data, enabling them to produce coherent and contextually relevant text. LLMs can assist in drafting legal briefs, generating client correspondence, or providing legal advice in plain language. Casetext’s Compose uses LLMs to help lawyers draft legal briefs by suggesting arguments and language based on case law. DoNotPay employs LLMs to generate legal letters and assist with small claims cases.

Specific LLMs: GPT, Claude

GPT (Generative Pretrained Transformer):

GPT, developed by OpenAI, is a prominent example of an LLM. ChatGPT is a version designed for conversational responses, making it particularly useful for interactive legal research tools or virtual legal assistants.

Claude, developed by Anthropic, is another LLM with capabilities similar to GPT. It can be used for generating legal text, automating routine tasks, and enhancing legal research. Anthropic's Claude offers similar functionalities, tailored to legal applications.

Bard, developed by Google, is a chatbot version of an LLM. It can assist with legal research, document drafting, and client interactions by generating accurate and relevant text responses based on user queries. Google’s Bard is being integrated into various legal tech platforms to enhance their natural language processing capabilities.

Our video here explains the hierarchy of AI terminology and how it applies to lawyers, all explained by a Big Law attorney with experience practicing law and building software:

Understanding the hierarchy of AI and its subsets, such as machine learning, generative AI, and LLMs, can help lawyers leverage these technologies effectively and build more profitable firms that continue to thrive and capture more market share. While AI can significantly boost efficiency and productivity in legal practice, many firms forget how the productivity can also lead to additional revenue through scale. And that scale is the future of legal services.

Follow Gavel's CEO on Instagram (@dorna_at_gavel) to learn more about technology tips for lawyers, AI and legal tech terminology, and how to run a future proof law firm. Want to start autoating your law practice today? Start a free trial at www.gavel.io.

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