blog.1.image
Blog
January 5th

Artificial Intelligence and Litigation Strategies: The Compressed Course

George Socha
George Socha

Artificial Intelligence and Litigation Strategies: The Compressed Course

Professor Bill Hamilton and I will be teaching a new course “Artificial Intelligence and Litigation Strategies” next week at the University of Florida Levin College of Law. This will be, we believe, the first offering of its kind. The course will focus on teaching upper-level students how attorneys can use AI to meet litigation objectives more effectively.

Why a course on AI at a law school?

This course is part of a much larger undertaking by the University of Florida and the law school. In 2020, University of Florida leaders unveiled a sweeping initiative to infuse AI across all academic disciplines. “AI is entering all sectors of society and having a rapid and profound impact,” said UF Provost and Senior Vice President of Academic Affairs Glover. “For us at UF, an AI university is one in which every student -- no matter their chosen occupation -- has an opportunity to learn about AI and data science at whatever capacity they would like.”

To this end, University of Florida Levin College of Law faculty has been offering courses such as AI, Machine Learning and Ethics in Law and Regulation, delivered jointly with the Herbert Wertheim College of Engineering; Artificial Intelligence, Technology, and the Law; Big Data and the Law; Biotechnology and Medical AI, Medical Technology and the Law; and Artificial Intelligence and Tax Law.

Why a course or AI and litigation strategies?

In keeping with this initiative, next week’s course – one of several compressed upper-level courses delivered over five days – will focus on the use of artificial intelligence to respond to requests for production, conduct early and prelitigation investigations, prepare to take and defend depositions, cull data sets for privileged and work product documents, and prepare for case conferences and disclosures.

The course will cover both theory and practice. In addition to sessions on topics such as data analytics, sentiment analysis, and deposition preparation, students will get hands-on experience using Reveal’s AI-powered eDiscovery platform throughout the course.

Why us?

Bill and I joined forces to develop this course, each of us bring to bear decades of eDiscovery experience and expertise. Bill is a Senior Legal Skills Professor UF Law, where he also serves as a Director of the UF Law E-Discovery Project and the International Center for Information Retrieval (ICAIR), a multidisciplinary endeavor to support the civil litigation process through electronic discovery law courses, research, the development of information retrieval method and tools, and electronic discovery skills training offered to practicing attorneys and litigation support professionals.

Bill previously was a litigation partner at Quarles & Brady and before that at Holland & Knight in a career spanning more than 30 years. In addition to teaching eDiscovery at UF Law for nearly 15 years, Bill also was a vice chancellor at Bryan University for more than five years, where he created and ran online eDiscovery programs.

My career also has spanned more than thirty years. I was a litigation partner at Halleland Lewis Nilan and before that an attorney at Popham Haik, had my own eDiscovery consulting firm for more than a decade, and worked at the assurance, tax, and financial advisory services firm BDO. In 2005, my colleague Tom Gelbmann and I founded EDRM, whose frameworks and content have empowered a generation of legal professionals. These days, as part of the leadership team at Reveal I am responsible for increasing market awareness and adoption of Reveal’s platform globally, help guide the product roadmap, and consult with company clients on effective deployment of legal technology.

Between us, Bill and I have worked on nearly every aspect of lawsuits and investigations, from preliminary efforts to gather information in anticipation of a matter through appeals and final disposition of matters. As litigation and trial lawyers, we have handled everything from personal injury matters to some of the nation’s largest financial investigations, multidistrict litigations, and academic fraud scandals. For these matters, we have used a wide array to litigation support and eDiscovery tools up to and including some of the most advanced AI tools available to lawyers, investigators, and their staff. We also have served as arbitrators, neutrals, special masters, and 30(b)(6) and expert witnesses – experiences that have provided yet another set of perspectives on the use of technology to support and enhance the practice of law.

In preparing this course, Bill and I have relied on the able assistance of my colleague Charles Duff, a Strategic Sales Engineer at Reveal. Starting with the concepts we provided, Charles has worked hard to design and create the hands-on exercises the students will use.

What can the students expect?

The students, all second and third years, will get a 14-hour course compressed into a single week. They will not need to have any advanced or specialized computer knowledge, be experts in technology, or have mastered (or, for that matter, ever used) eDiscovery software.

We will meet with the students in class for three hours a day. Students will be expected to spend up to six hours additional hours daily on assignments, readings, and exercises.

Each day of the course will have a particular focus.

Day one: Overview

On the first day, we will provide a general introduction to eDiscovery in litigation which will include overviews of Federal and Florida rules governing the discovery of electronically stored information, conceptual frameworks that shape how we handle ESI in discovery including The Sedona Principles and the EDRM model, and issues relating to scope, costs, and search. We also will introduce the students to data analytics as used for litigation, how they have evolved, and the emergence of AI as a legal solution. Finally, we will introduce students to Reveal’s eDiscovery platform, which they will be using throughout the course.

Day two: AI and investigations

On the second day we will examine the use of AI to assist with investigations, both standalone investigations and the investigative components of lawsuits. After an overview of the conceptual frameworks involved, we will work with three particular sets of AI capabilities that can enhance attorneys’ ability to learn more about the who, what, when, where, why, and how of matters.

We will start with communications analysis, learning how to use AI to better look at the content and context of the ideas, thoughts, and feelings we express, with whom we express those things, and what they might mean. From there we will turn to sentiment analysis, using AI to explore the emotional significance of the language we use as we communicate with others. We will close the day with image analysis, learning how AI can help us make effective use of the pictures, photographs, and drawings that so often get ignored in lawsuits and investigations.

Day three: AI and litigation events

Midweek we will shift our attention to ways AI can help with tasks every litigator needs to able to perform. We will begin the day with the FRCP Rule 26(f) meet and confer conference, move to deposition preparation, and finish with privilege review. With each topic, we will cover theory, examine strategy, and perform exercises meant to help illustrate how AI can help.

Day four: AI and technology assisted document review

Thursday will be all about technology assisted review (TAR), the most widely publicized and more extensively used AI capability in the eDiscovery world. We will look at the early days of TAR, see how the industry adapted to early challenges, then explore TAR as it is used today. After that, the students, working as a team, will get the chance to go through a mock review project.

Day five: AI and privacy

Friday we will turn our sights to data privacy, initially discussing the rise of data privacy and the growth of frameworks to address privacy concerns. We will explore different approaches to locating personally identifiable information (PII) and examine options for redacting PII and similar content, a capability whose uses range from litigation to compliance and beyond.

We will wrap up casting our gaze to the future of AI in litigation, both in the short term and down the road.

Learn More

If you and your organization would like to learn more about artificial intelligence and litigation strategies, about the eDiscovery programs at UF Law including UF Law’s upcoming 9th Annual E-Discovery Conference, or about how Reveal uses AI as an integral part of its AI-powered end-to-end legal document review platform, contact us.

*/