Reed Smith and its lawyers have used machine-assisted case preparation tools for many years (and it launched the Gravity Stack subsidiary) to apply legal technology that cuts costs, saves labor and extracts serious questions faster for senior lawyers to review. Partners David Cohen (https://www.reedsmith.com/en/professi...) , Anthony Diana (https://www.reedsmith.com/en/professi...) and Therese Craparo (https://www.reedsmith.com/en/professi...) discuss how generative AI is creating powerful new options for legal teams using machine-assisted legal processes in case preparation and e-discovery. They discuss how the field of e-discovery, with the help of emerging AI systems, is becoming more widely accepted as a cost and quality improvement.
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Transcript:
Intro: Hello, and welcome to Tech Law Talks, a podcast brought to you by Reed Smith's Emerging Technologies Group. In each episode of this podcast, we will discuss cutting-edge issues on technology, data, and the law. We will provide practical observations on a wide variety of technology and data topics to give you quick and actionable tips to address the issues you are dealing with every day.
David: Hello, everyone, and welcome to Tech Law Talks and our new series on AI. Over the the coming months, we'll explore the key challenges and opportunities within the rapidly evolving AI landscape. Today, we're going to focus on AI in eDiscovery. My name is David Cohen, and I'm pleased to be joined today by my colleagues, Anthony, Diana, and Therese Craparo. I head up Reed Smith's Records & eDiscovery practice group, big practice group, 70 plus lawyers strong, and we're very excited to be moving into AI territory. And we've been using some AI tools and we're testing new ones. Therese, I'm going to turn it over to you to introduce yourself.
Therese: Sure. Thanks, Dave. Hi, my name is Therese Craparo. I am a partner in our Emerging Technologies Group here at Reed Smith. My practice focuses on eDiscovery, digital innovation, and data risk management. And And like all of us, seeing a significant uptick in the interest in using AI across industries and particularly in the legal industry. Anthony?
Anthony: Hello, this is Anthony Diana. I am a partner in the New York office, also part of the Emerging Technologies Group. And similarly, my practice focuses on digital transformation projects for large clients, particularly financial institutions. and also been dealing with e-discovery issues for more than 20 years, basically, as long as e-discovery has existed. I think all of us have on this call. So looking forward to talking about AI.
David: Thanks, Anthony. And my first question is, the field of e-discovery was one of the first to make practical use of AI in the form of predictive coding and document analytics. Predictive coding has now been around for more than two decades. So, Teresa and Anthony, how's that been working out?
Therese: You know, I think it's a dual answer, right? It's been working out incredibly well, and yet it's not used as much as it should be. I think that at this stage, the use of predictive coding and analytics in e-discovery is pretty standard, right? Right. As Dave, as you said, two decades ago, it was very controversial and there was a lot of debate and dispute about the appropriate use and the right controls and the like going on in the industry and a lot of discovery fights around that. But I think at this stage, we've really gotten to a point where this technology is, you know, well understood, used incredibly effectively to appropriately manage and streamline e-discovery and to improve on discovery processes and the like. I think it's far less controversial in terms of its use. And frankly, the e-discovery industry has done a really great job at promoting it and finding ways to use this advanced technology in litigation. I think that one of the challenges is that still is that while the lawyers who are using it are using it incredibly effectively, it's still not enough people that have adopted it. And I think there are still lawyers out there that haven't been using predictive coding or document analytics in ways that they could be using it to improve their own processes. I don't know, Anthony, what are your thoughts on that?
Anthony: Yeah, I mean, I think to reiterate this, I mean, the predictive coding that everyone's used to is it's machine learning, right? So it's AI, but it's machine learning. And I think it was particularly helpful just in terms of workflow and what we're trying to accomplish in eDiscovery when we're trying to produce relevant information. Information, machine learning made a lot of sense. And I think I was a big proponent of it. I think a lot of people are because it gave a lot of control. The big issue was it allowed, I would call, senior attorneys to have more control over what is relevant. So the whole idea is you...
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