This guide provides an overview of developments and tools in generative artificial intelligence (generative AI) as they relate to legal research, education, and practice. It will be regularly updated with new resources and insights. Law students are encouraged to check back frequently for up-to-date information and tools.
Generative artificial intelligence is a type of artificial intelligence (AI) that creates content—such as text, images, video, and computer code—by identifying patterns in large datasets. Unlike extractive AI, which focuses on analyzing and summarizing existing information, generative AI produces new content based on the data it has learned from.
A large language model (LLM) is a specific type of generative AI trained on massive amounts of text data to predict the next likely sequence of words in response to user prompts. Generative AI chatbots replicate patterns learned from human communication, making their responses sound sophisticated and human-like. However, they do not generate new ideas or assess the accuracy or relevance of their responses—they simply reassemble patterns based on their training. Popular examples of LLM-based tools include OpenAI's ChatGPT, Google's Gemini (formerly Bard), and Microsoft’s Copilot, discussed further in the section, What Generative AI Tools are Available?
The introduction of generative AI tools has impacted many industries, including legal education and practice. According to Lexis, generative AI tools help streamline tasks such as drafting legal briefs and client memos, conducting due diligence, and analyzing large volumes of documents. While generative AI brings exciting new capabilities, it also raises significant ethical and legal concerns. These are explored in the section, Risks and Ethical Considerations in Using Generative AI Tools.
When considering which AI tool to use for specific tasks, it's important to distinguish between the two main types: extractive and generative AI.
| Extractive AI | Generative AI |
|---|---|
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Extractive AI retrieves and summarizes existing information. It is useful for tasks like search, summarization, information retrieval, and knowledge management. Examples: Search engines like Google and Microsoft Bing, as well as legal research platforms like Westlaw and Lexis+, which retrieve and summarize case law, statutes, and secondary sources. |
Generative AI creates new content—such as text, images, video, and computer code. LLMs, a type of generative AI, generate content by predicting word sequences and completing tasks based on learned patterns. Examples: GPT-4 (which powers ChatGPT), Claude, Gemini, Grok, and LLaMA. In the legal field, Lexis+ AI integrates multiple LLMs with proprietary legal data to generate responses tailored to legal research and practice. |
Generative AI is beginning to transform many aspects of legal practice. Major law firms, bar associations, and courts across the United States have issued guidelines and policies specifically addressing the use of generative AI in legal work, reflecting its growing impact on the profession. This technology has the potential to assist lawyers with tasks like legal research, document drafting, and contract analysis. At the same time, it raises ethical and practical challenges around issues such as confidentiality, accuracy, and the unauthorized practice of law. As generative AI capabilities continue to advance rapidly, the legal profession is grappling with how to effectively integrate this technology while upholding core professional standards and responsibilities.
An August 2024 report from the ABA Task Force on Law and Artificial Intelligence examines the impact of AI, particularly generative AI, on the legal profession. It covers topics including legal ethics, court systems, legal education, access to justice, risk management, and AI governance as they relate to emerging AI technologies.
What Are the Risks in Using Generative AI for Legal Work?
When deciding whether to use Generative AI, one must carefully weigh numerous risks and considerations, which are discussed in greater detail in the section Risks and Ethical Considerations in Using Gen AI.