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Home Library Generative AI (Gen AI) Legal Resource Guide

The rapid development of Generative Artificial Intelligence (Gen AI) has quickly gained attention across the world. The arrival of ChatGPT, the natural-language prediction model, vaulted Gen AI into the public, including the law community. What Gen AI means for the future of the legal profession is still yet to be determined. As stated by Allison Whitten, “AI won’t replace professions like doctors, lawyers, or journalists—but those who work with AI will replace those who don’t.” (Me, Myself, and AI, Stanford Magazine). Here are some resources to assist the legal community. These resources will be updated regularly.

Last update: June 12, 2024

University of Utah’s Gen AI Guidelines
Gen AI Glossary:

Basic Terms (taken from The Artificial Intelligence Glossary)

    • Algorithms – In AI, a set of instructions or programming that tells a computer what to do in order to allow the machine to learn to operate on its ownto solve a specific problem or perform a specific task.
    • Artificial Intelligence – The branch of computer science focused on the theory, development and design of computer systems that have the ability to mimic human intelligence and thought or perform tasks that normally require human intelligence.
    • Deep Learning – A type of machine learning that utilizes neutral networks to mimic the human brain, using three or more layers of training to enable the AI cluster data and make predictions.
    • Generative AI – A category of AI systems, including large language models, that can independently create unique, novel content, in the form of text, images, audio and more, based on the data they have previously been trained on. Unlike traditional AI systems, generative AI algorithms go beyond recognizing patterns and making predictions. Some advanced generative AI systems are not limited to their training datasets, and can learn to respond to questions or prompts containing information on which they were not previously trained.
    • Generative Pretrained Transformer (GPT) – The prefix to various generations of large language models from the company OpenAI. For example, GPT-3 is the third generation of GPT models.
    • Large Language Models (LLM’s) – A type of deep learning algorithm or machine learning model that can perform a variety of natural language processing tasks. These include: reading, summarizing, translating, classifying, predicting and generating text words or sentences, answering questions or responding to prompts in a conversational manner and translating text from one language to another. It performs these tasks based on knowledge gained from massive datasets and supervised and reinforcement learning. LLMs are one kind of foundational model.
    • Machine Learning – A broad branch of AI concerned with “teaching” AI systems to perform tasks, understand concepts or solve problems in a way that imitates intelligent human behavior, gradually becoming more accurate as it is trained on more data.
    • Natural Language Processing – A branch of AI and computer science that refers to the ability of computers or software to understand and read written and spoken language in the form of text and voice data, including intent and sentiment.
    • Neural Networks – A means of machine learning that mimics the human brain, and includes the ability for multiple layers of training to occur simultaneously. Neural networks are made up of millions of processing nodes and are central to deep learning.
Other Works Explaining AI:
Gen AI in the Practice of Law