Generative artificial intelligence tools are transforming the ability of federal agencies to accomplish routine but time-consuming tasks. Now employees working in government legal functions are turning to AI tools to enhance research, synthesize vast amounts of information and draft documents quickly.
Jake Nelson, general manager of emerging products at LexisNexis, said generative AI tools are adept at handling repetitive tasks — such as summarizing large volumes of text and identifying key legal precedents — while allowing legal professionals to focus on higher-value work.
“Drafting boilerplate language that’s largely the same from one draft to another is probably not the best use of time,” Nelson said during Federal News Network’s AI and Data Exchange.
Instead, generative AI tools can serve as a “personalized assistant” that boosts the productivity of federal employees, he said.
But these tools can’t replace federal employees’ legal expertise, Nelson added.
“You’re still in the driver’s seat, and that’s absolutely critical. While maybe you’re using AI in the future to draft that initial draft, you’re still ultimately responsible for what you’re filing,” he said. “It’s not about replacement. It’s about being able to do more in less time, more effectively, and serve more people.
“Being able to add that efficiency, especially within the government, is incredibly important. Being able to synthesize, to summarize, to draft based on precedents that are really important and being able to home in on those precedents that you find particularly useful is huge. Being able to do that is probably where the lowest hanging fruit is.”
Getting started with AI
Agencies are experimenting with generative AI’s potential but in some cases struggle with where to begin.
“Every generative AI provider is offering some sort of trial or other type of offering where you can start to test and use these,” Nelson said. “Spending a day or two with platforms like Lexis+ AI to see what it can do — from a research, a drafting, a summarization standpoint — goes an extremely long way in actually making this useful to you.”
One of the primary concerns surrounding AI in the legal field is data security. Nelson said while general or free AI models often feed user prompts and outputs back into their models for training purposes, legal AI platforms like LexisNexis’ solutions are built on a private and secure foundation to ensure that documents and prompts used are not made available to other users of the same products or AI models.
The future of AI in legal services
Generative AI capabilities are accelerating and as these tools continue to evolve, Nelson said they will play an even greater role in legal functions.
“AI is not perfect. We’re on that exponential curve of improvement, of growth. There will always be a space for legal professionals to fill that gap,” he said. “When you’re looking at legal technology, legal AI and generative AI in the legal space, you can see the tremendous difference a year makes.”
A major challenge in generative AI is the issue of hallucinations, AI-generated content that includes inaccurate or misleading information. To mitigate this, Nelson said users should consider products that leverage a multimodel approach to validate outputs.
“Maybe we’ve got one model that’s being used to search and retrieve that content that you need to enrich or improve that output. Maybe you’ve got a model that’s being used to generate that first draft,” he said. “But that follow-up, in terms of validating citations to reduce hallucination, that is the trick. We have to pull in different models to validate one another in order to address those bigger concerns, with generative AI hallucination being at the very top of that list.”
Legal offices across the government have lots to gain from integrating generative AI into their workflows, Nelson said. From streamlining research and drafting to enhancing accuracy and efficiency, AI can be a valuable tool for legal professionals.
“This is a huge opportunity for us in the legal profession to be able to use these tools — to do more, to do more efficiently, to do good with AI,” Nelson said.
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