The Thomson Reuters Legal SYNERGY user conference is under way today through June 3, with legal professionals from the U.S., Canada, the UK and Europe gathering virtually for product sessions and continuing legal education as well as opportunities to network with peers and hear from fascinating guests.

Among today’s highlights are host and Emmy Award-winning writer and comedian Seth Meyers’ opening monologue. Another must-see is the session AI in action: A review of future legal use cases, moderated by Frank Schilder, senior director Research for Thomson Reuters Labs, and Rachel Beithon, Thomson Reuters product developer.  

Legal Current had a chance to catch up with Beithon before her session for her perspective on the advantages of using AI in legal research and how customer feedback shapes the development of AI solutions at Thomson Reuters. Below is a recap of the conversation.

Legal Current: What AI trends are shaping the legal industry?

Beithon: One trend that I’m seeing is an overall increase in comfort with AI as a base for legal research, and also increasing expectations from our customers and their clients that AI is involved in legal research process. It’s been an expectation in certain practice areas, like IP, for a number of years, but more and more legal professionals really expect that legal advice isn’t just based on anecdotes, but on quantifiable data. And the legal community also wants to use technology and AI to their advantage – so document automation and analytics are becoming more important, and there is an increased expectation that providers will have sophisticated capabilities for the legal community to use in both of those. They are both relatively new, in terms of the broader legal technology experience, and as I talk to customers, they are excited for products like Quick Check and Litigation Analytics and want more from both.

LC: Share some key examples of AI research happening at Thomson Reuters.

Beithon: Just about everywhere now. And it’s becoming more key, as we look at new enhancements, to expand into other areas we haven’t investigated for use with AI. I know we’re using it extensively in Westlaw Edge – it touches more areas than ever, like Checkpoint in our Tax & Accounting business, and it has certainly expanded into places like Westlaw Edge UK and other products in the Thomson Reuters portfolio.

You can learn more about our research in AI and its application on our site dedicated to showcasing our work in AI applied research.

LC: How do the Thomson Reuters AI principles guide your work?

Beithon: I’ve learned a lot about our AI principles from working with Thomson Reuters Labs, and that’s helped inform how I approach the use of AI within Litigation Analytics. I try to keep all of them top of mind, but the ones I feel coming up the most often on the business side are bias and accountability. We want to make sure, always, that we are creating fair representations. We have been careful to communicate that we are providing a way for users to create their own legal determinations with the use of data. We know that the more data you have, the more informed a decision can be, and I think users appreciate the ability to use metrics to inform their decision-making as it makes for more holistic client conversations.

LC: With damages analytics, how did customers inform its development, and what has their response been using it?

Beithon: Customer input and feedback was always top of mind in developing damages analytics. When I was a reference attorney, one of the primary requests from customers was a tool like the damages project in Litigation Analytics, so we knew it was important to do and important to do well, and Thomson Reuters Labs was the only partner we could envision bringing that project to life. In that first month of partnering, we sat down and talked through the problem we were trying to solve – discussing how customers could find damages information in Westlaw, prior to releasing damages in Litigation Analytics – and why that was not a great customer experience. And, of course, how we hoped to improve that and make it a great experience. We took every opportunity to talk to customers about damages and made it a focus in our everyday conversations and during customer research. Those conversations helped us create the product we have today.

The response has been so great. People are so excited about it when we speak to them, and even more excited when they didn’t know we’d released it. It seems to be a perfect way for users, who weren’t necessarily convinced about using Litigation Analytics before, to see the advantages of quantifiable legal research. And we get a lot of requests for “more,” which is my favorite type of feedback because it often indicates that they trust us to be the ones to go further in our development, which is important for a great customer experience.

LC:  Looking ahead, what’s an application of AI in the legal domain that you’re most excited about and why?

Beithon: One place I’m most excited to see AI is the social justice impact of it in the legal domain; it’s already been tried in that space, with varying degrees of success. There is a powerful case for being able to point to quantitative analysis in the law when it comes to bias, and if it is done well, with an eye to it matching the goals and values of the legal profession, and with a very careful eye toward ethical implications of its use, it will be powerful to use AI to provide better access to justice.

To learn more about Legal SYNERGY2021, visit the U.S. conference site, Canada conference site, or Europe/U.K. conference site.

Watch Legal Current for more details about SYNERGY sessions, and follow @LegalCurrent for updates throughout SYNERGY.