alt.legal: I Still Haven’t Found What I’m Looking For!
Technology columnist Ed Sohn launches a new multi-part series on artificial intelligence and machine learning in the law.
Laura Webster
I have spoke with the tongue of angels
I have held the hand of a devil
It was warm in the night, I was cold as a stone
But I still haven’t found what I’m looking for
After graduating with a computer science degree from Illinois, a career in IP law seemed to be the most natural (and perhaps the only obvious) intersection between my technical background and legal practice. But I found myself drawn to business litigation, so that’s what I did instead. As a business litigator, my technology background did not serve me much. I guess other associates on my floor would occasionally ask how I got my dual screens to work, and I tended to be faster at reformatting my motions and briefs because I knew some hotkeys.
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In recent years, however, legal technology has finally started to advance and receive investment in classical areas of legal practice. Technology is helping attorneys with evidence, workflows, contract management, even risk assessments in patent review or litigation. (And don’t worry, the robots aren’t really coming for our jobs.)
Today, I am launching a new multi-part series on artificial intelligence and machine learning in the law. I’m starting with an interview with Laura Webster, Director, Partner Solutions at Content Analyst Company. She specializes in consulting with clients to apply Content Analyst technology into innovative software applications.
In a world increasingly at the mercy of Big Data, Content Analyst makes it possible to find… (wait for it) what you’re looking for.
Ed Sohn: Laura, thanks for making time today. Tell me about Content Analyst and your primary legal product.
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Laura Webster: Content Analyst’s primary product is CAAT (Content Analyst Analytical Technology), it’s the analytics engine. The core of CAAT’s offering is conceptual search—searching by topic or concept as opposed to keywords. It supports investigative workflows, like technology-assisted review in the legal market and advanced analytics in other markets. It is the engine underneath a lot of innovative products. We help clients innovate in their products and how CAAT can support that.
ES: What’s been the most exciting thing about working with CAAT?
LW: Well, we didn’t start in e-discovery—we started in the intelligence community. We got into e-discovery several years ago. But it has been such a great fit, so for me, watching explosive growth in this industry has been so exciting. It’s been really fun to see the various providers integrating CAAT and to see how well it works with providers and law firms.
Outside of e-discovery, we are getting into new markets where potential partners are starting to realize that there are advanced capabilities out there and see how they can benefit from it. More and more people are seeing how they can get some new technology into their existing applications. It’s exciting to be walking side by side with them on it.
ES: It sounds like CAAT is a really flexible tool. What are the best use cases for CAAT, and conversely, what is it not best suited for?
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LW: Looking at e-discovery, one thing is that a lot of the information you’re looking for is not easily findable, or even not intended to be found. You don’t really know how to search for that information that’s intentionally made not searchable. So, concept searching has a very strong role in investigative-type work, organizing documents and content in order to get through all of it more quickly. It just made sense on why it’s such a fit.
Likewise, in other markets, it’s also a lot about findability: trying to find information that you have and figure out how you (and by “you” I mean an enterprise) can use that information. There is lots of opportunity for general concept searching, making it easier to locate and use to your benefit.
Where it’s not a good fit: CAAT is not intended to completely replace keyword searching exact phrases. If I need to know every place and every document that says the words “Laura Webster,” I need to use keyword searching to do that.
ES: So what about things like highly quantitative data? Numerical values in structured data?
LW: Right, so the obvious thing is where you’re looking at massive spreadsheets filled with financial data or numbers, CAAT probably is not your best bet. Use the existing computational tools that are out there for that. CAAT is good for concepts.
As for structured data, the classic power of CAAT is definitely in unstructured data filled with latent concepts. But, I will say that with respect to structured data, there are definitely applications for CAAT when you can combine conceptual searching with existing search technology. Using CAAT in conjunction with metadata provided with the structured content, you can get much greater insight into your data.
ES: Is CAAT evolving? Is there R&D happening on the core engine technology, or is it just about finding ways to implement it better?
LW: Oh, there’s absolutely still R&D happening to improve the quality of the indexing, the capabilities of your search and further enhancing the classification capabilities. We are always working on improving the APIs (application programming interfaces, the connection point for partners to integrate our tech with theirs) to make it easier for developers, and we’re always seeking to improve the way we work with services. At the product level, there’s so much R&D and creative thought, we’re always looking to innovate more.
ES: So this sounds great for technology-assisted review in e-discovery, and I think everyone knows about your work there. What are some other obvious use cases for CAAT, especially in the legal arena?
LW: What immediately comes to mind is information governance. There are absolutely huge opportunities in helping companies know what they have before getting into litigation. But there are also challenges here at the enterprise level. IT departments have different interests in business data than legal folks, and it gets challenging to get agreement on an approach to data. A lot of times it comes down to who has control over the budget. We do have partners that are tapping into that space, equipped with our engine.
There is so much interesting activity going on with CAAT in other industries, but another area related to legal where we are seeing growth is in contract management. Many enterprises have thousands of contracts with expirations, services tied to them, renewal dates, and we’re back to findability—a lot of enterprises are just trying to figure out what contracts they have. This is another opportunity ripe for CAAT.
ES: Jump into a time machine five years into the future. What, in your mind, are the qualities of a beautiful world where Content Analyst has been wildly successful?
LW: That’s a tough one. Primarily, it’s behavioral changes. We’re seeing that start to take place already—people are searching for information differently. Instead of using keywords and getting results around data that contains those words and searching over and over again, technology starts learning what it is they are looking for and feeding relevant information to the end user. Users can quickly get access to information rather than going through the hunt for it. We’re going to keep seeing that trend and hopefully keep fostering and fulfilling those expectations.
In terms of enterprise, there’s really so much information that businesses don’t know about themselves, in litigation, in contract, anywhere. I see a world where that uncertainty is greatly reduced by successful CAAT integrations, resulting in higher preparedness for businesses.
ES: How can lawyers get in on this party?
LW: Primarily, lawyers just need to start using products that incorporate CAAT! The people who are super excited about analytics in e-discovery, they are easy to reach and persuade. It’s the skeptics that are more challenging, but I would encourage everyone to learn, to read the blogs out there on analytics, and explore the tools that are out there driven by CAAT.
ES: How has this been for you personally? What’s your background?
LW: I’ve been with Content Analyst for just over four years. I was first exposed to Content Analyst in e-discovery, when I was previously with Fios, because before that I was purely in software. I instantly became an analytics junkie, just getting our users to cluster and batch, and I was really intrigued. The fact that technology could solve some of these unique problems was really fascinating. So I jumped over to the software side of Content Analyst.
What’s fun for me now is to spend time with partners in the e-discovery space, as well as partners in really different types of work. Learning what they do, some of it is like “I’ve never ever touched your line of work and I need to learn everything you do,” and when doing that, understanding what their challenges are, learning how big of an impact CAAT can have on issues that I didn’t even know existed.
ES: Thanks so much, Laura. This has been really insightful.
Ed Sohn is a Senior Director at Thomson Reuters Legal Managed Services (formerly Pangea3). After more than five years as a Biglaw litigation associate and more than two years in New Delhi overseeing the delivery of managed document review, Ed now focuses on managing the new e-discovery solutions with technology managed services. You can contact Ed about e-discovery, legal managed services, theology, chess, Star Trek: The Next Generation, or the Chicago Bulls at edward.sohn@thomsonreuters.com.
