By Kristen M. Hallows, Bricker & Eckler LLP
Fastcase CEO Ed Walters has had enough with the magic and the unicorns and the hype surrounding artificial intelligence, or AI. He urged attendees at the American Association of Law Libraries (AALL) session, “Powered by AI, Built in the Law Library,” to think of AI like pivot tables in Excel: they’re just tools. They’re not magic, but they can be to those who don’t understand them.
He began by sharing a few hilarious examples of the limitations of AI. Is it a Shar-Pei, or is it soft serve? AI doesn’t know! It can’t differentiate between the two. And, whatever you do, don’t expect appealing names for paint colors from AI. Stoner Blue might seem appropriate for your teenager’s room, but can you imagine taking home a color sample by the name of Bank Butt? How about a light brown named Turdly?
So, AI is good at some things and not good at others. When it works, we stop calling it AI. You may not identify it as such, but AI is “baked into” some very common tools law firms and libraries probably use every day, such as spellcheck and Google Translate.
Ed refers to the first wave of AI, where we are currently, as “read only” AI. What’s coming is the second wave, which he calls “read/write” AI. It’s a much cooler phase in which we get to go from consumer AI to maker AI. Maker AI presents a new suite of tools that information professionals can use to provide more customized and actionable information to attorneys and firm administrators. Whereas traditional legal research services offer the same data to all users, maker AI lets information professionals create their own datasets and extract results unique to them. These results can provide insights to help structure alternative fee arrangements or to help inform litigation strategy or settlement decisions.
Take the Fastcase AI Sandbox. The AI Sandbox was designed to empower people. It’s a set of secure servers with datasets and metadata from Fastcase, coupled with an extensive suite of AI tools. Law firms or law schools can combine the Fastcase data with in-house data. Once you have your desired dataset, you can query it and get results out. For example, you can load a set of judicial opinions and get personality insights out–a judge’s preferences or tendencies. Using Docket Alarm’s new tool, you can create your own analytics on a subset of documents, such as mandamus petitions in Texas. Upload your own data and crunch it! And you can build your own apps with Neota Logic, rules-driven software with built-in decision tree logic.
Legal information professionals can drive this new read/write AI. Law librarians can build things with AI now, not just create reports, and some librarians are already doing it. Continue reading