Understanding and Utilizing Legal Large Language Models

From tools like Harvey that assist with legal research and document review to AI tools for lawyers that serve as AI legal assistants, and more, legal large language models are on the rise in the legal industry. But what impact will emerging large language models tailored to the legal sector have on how legal professionals work—and what concerns should they be watching out for?

According to this year’s Legal Trends Report, 79% of legal professionals use AI—including legal large language models—in some capacity in their legal practice. While it’s increasingly clear that large language models have the power to help make legal work more efficient, cost-effective, and accessible, they also come with certain risks and limitations that must be considered.

With this in mind, we’ll explore the growing impact of large legal language models on the legal industry—and their benefits, challenges, and potential for the future.

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What are large language models?

Large language models (LLMs) are AI systems that use vast training datasets of text, often made up of terabytes of data, to understand and generate responses based on human language. By using a large number of parameters, LLMs can be trained and fine-tuned to perform specific tasks like answering questions or summarizing information.

So, when a user gives an LLM like ChatGPT a specific prompt (i.e., an instruction), the LLM generates a text output response. For example, a lawyer may use ChatGPT prompts to request an overview of legal precedents in a specific area of law.

The importance of legal large language models

While using general LLM tools like ChatGPT is becoming increasingly commonplace to answer questions or help with tasks in our day-to-day lives, LLMs tailored for legal purposes are emerging as tools that can help legal professionals.

Put simply, LLMs can review massive quantities of text data quickly and efficiently on a broad spectrum of topics—including those related to the law. Because many legal tasks rely on reviewing, searching through, and generating large quantities of documents, LLMs that have been trained on legal-specific datasets and parameters can lessen the burden of time-consuming, repetitive work for legal professionals.

How are LLMs used in law?

With their own supervision and human oversight, legal professionals can use LLM tools to assist with a variety of tasks, such as legal research, document analysis, drafting, and case summarization.

Legal professionals can benefit from using large language models in legal processes by:

• Saving time and effort when completing repetitive tasks and analysis.
• Freeing up more bandwidth to dedicate to higher-value legal work and client service.
• Passing on cost and time savings to clients as a way to increase access to justice for more people seeking legal advice.

Applications of legal large language models

While using large language models for legal requires law firms to ensure they meet their ethical obligations and maintain data privacy and confidentiality (more on this later), there is an increasing number of ways legal professionals may effectively use legal LLMs in their practices.

How can law firms integrate LLMs into their practices?

With appropriate human oversight, law firms may integrate legal LLMs into their practices in many ways, including:

• Making legal research and document analysis more efficient: Legal LLM tools can review, analyze, and generate summaries of large volumes of text—such as case law and court decisions—for legal professionals. They can also help provide summaries of complex text in plain language and identify and highlight relevant sections of documents for lawyers to review. 
• Automating contract drafting and review: By automating initial drafts of contracts and assisting with contract review (for example, by identifying relevant terms or risks), legal LLMs can streamline contract lifecycle timelines. 
• Powering legal chatbots and virtual assistants: Using AI-powered chatbots can allow lawyers to delegate certain processes related to client interaction like client intake and client communication (for example, by providing answers to common questions). Legal LLMs can also act as virtual assistants by supporting lawyers with tasks like creating initial drafts of emails or letters or translations.

Challenges and considerations of legal large language models

While law large language models have the potential to provide many time-saving and practical uses for legal professionals, these new technologies must be handled carefully and responsibly. 

Although the use of AI in legal is relatively new, it’s important for lawyers to understand the ethical considerations related to AI in law and meet any obligations and responsibilities outlined by their bar association’s rules of professional conduct.

While firms and lawyers must stay up-to-date with their responsibilities in this ever-changing realm, some key concerns to consider include:

Ethical obligations of using AI in the legal domain

Staying current with and abiding by ethical obligations and professional regulations are key for lawyers in all areas of their work, including the use of AI.

For lawyers in the US, for example, the American Bar Association (ABA) released Formal Opinion 512 on general artificial intelligence tools. The opinion outlines how lawyers have a duty to consider their ethical duties when using AI—including competence, client confidentiality, supervision, and reasonable fees. 

Accuracy of legal LLMs and legal hallucinations

While legal LLMs are trained on datasets of legal data, that doesn’t always mean that the responses they provide will be accurate. 

As demonstrated by the newsworthy case of two lawyers submitting a legal brief citing cases that didn’t exist, LLMs can “hallucinate” false, inaccurate, or irrelevant outputs. The existence and variability of legal hallucinations highlight the importance of human input and supervision when using legal LLMs to ensure accuracy.

Bias and fairness in legal LLMs

The potential for bias is a significant consideration when using legal LLMs. Because legal LLMs are trained on specific datasets, biases present in those datasets—systemic, latent, or otherwise—can emerge in the LLM’s output. 

For legal professionals using legal LLMs, these biases can lead to a wide range of consequences, such as unfair treatment, the reinforcement of inequalities, or discrimination.

This is why human oversight when using AI is crucial for mitigating the impact of biases inherent in the data that AI systems and legal LLMs rely on, as criminal justice reform advocate Judge Victoria Pratt discussed at the 2024 Clio Cloud Conference.

“AI can assist us, but we need to critically analyze its results,” Judge Pratt said. “It’s vital to have the common sense to look beyond the data and consider other factors that ultimately predict human behavior.”

Ensuring data privacy and confidentiality

Law firms and lawyers have a professional obligation to protect sensitive case information and client details at all times—including when using AI systems like legal LLMs. 

To ensure data privacy and confidentiality when considering the use of legal LLMs and help mitigate the risk of common AI legal issues, law firms and legal professionals must ensure, at minimum, that:

• They are up-to-date with their ethical and regulatory obligations related to the protection of client data and the use of AI tools—including alignment with applicable data protection laws such as GDPR, HIPAA, or local bar association rules.
• Any systems they use are secure, have policies in place for data handling and sharing, and follow strict data privacy regulations.
• There are systems in place to ensure human oversight when using legal LLM tools.
• Sensitive client information is never shared or inputted into a legal LLM, and any data exposed to legal LLMs is anonymized to prevent even accidental disclosure of identifiable details or client information.

Learn more about the intersection of AI, cybersecurity, and privacy.

It’s also notable to consider how lawyers’ duty of confidentiality can impact legal LLM training. As this blog post explores in more detail, legal LLMs need to be trained on the diverse and jurisdiction-specific legal data in order to become more competent and accurate with their responses. However, because legal professionals are bound by their confidentiality obligations, they are not able to ethically disclose those case details to AI systems without express permission from clients.

Looking to the future of legal large language models

This year’s Legal Trends Report reinforces the suggestion that early fears of whether AI will replace lawyers have been replaced with enthusiasm. Specifically, the report found that the vast majority (79%) of lawyers have adopted AI in some capacity, and 25% have adopted AI widely or universally.

As law firms continue to embrace AI, we can also look forward to how legal LLMs are influencing some of the emerging trends and innovations in AI for the legal sector, such as increasingly-effective legal LLM-powered tools for legal research, chatbots, and legal drafting.

Moving forward, these types of advancements in AI for lawyers and legal LLM tools have the potential to make legal workflows more productive and accessible, which can unlock opportunities to deliver more effective and cost-efficient legal services to clients. By adapting to the evolving legal technology landscape, legal professionals can maintain a competitive edge while also staying current with important factors related to AI and data privacy and ethics.

Conclusion

The previously-unattainable ability to use large language models to process and analyze large amounts of legal text quickly is changing how legal professionals approach their workflows. And, while they’ve already made an impact on the workflows—and ethical responsibilities—of many legal professionals, it seems likely that the full potential for large language models in the legal domain is still unfolding.

When lawyers can leverage the power of legal LLMs to automate routine tasks and simplify repetitive work, they unlock time and energy to focus on high-value legal work and better serve clients.

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