Sean Claggett · John Campbell
TLU Huntington Beach 2023 Replay - JuryBall: What Is Big Data & Jury Psychology
February 20, 2024 6:30 PM||TLU n Demand
Registering for this webinar will give you access to the following programs. Use the same zoom link to watch both programs.
Monday, Feb 19th - JuryBall: What Is Big Data
John and Sean will spend the first hour discussing “What is Big Data and How Can Lawyers Use It”. While the law has traditionally been considered an art, with intuition and instinct playing a major role in decision-making, there should be a larger emphasis on data and science in the field. Many questions in the law have fixed and correct answers, and lawyers should not be guessing at these answers but instead using data to inform their decisions. The first hour of this presentation provides examples of questions that have concrete answers, such as whether to begin an opening statement by discussing the plaintiff's injury or the defendant's conduct. John and Sean will show that bringing more science to cases does not eliminate the art of lawyering but elevates it. To illustrate this point, we will discusses the development of a computer program, AlphaGo, which learned to play the board game Go through deep learning and eventually beat the world champion. Just as AlphaGo taught the champion new tricks, bringing more science to law can empower great lawyers to try even better cases.
Tuesday, Feb 20th - Jury Psychology
People are predictable, even when their behavior is irrational. Human cognitive fallacies, which are predictable, repeatable, and chronicled in books like; Thinking, Fast and Slow and Predictably Irrational, can be used to lawyers advantage if they ask the right empirical questions and study them correctly. During this hour we will stress the importance of testing empirical questions to avoid self-inflicted, expensive wounds, and emphasizes that trying a case without obtaining the answers to empirical questions is equivalent to guessing. Finally, we will explain that the true value of a case, within a range, is knowable and should be determined through data, not instincts, to avoid data.
