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62 – John Campbell – The Empirical Jury: Big Data with Big Results

In this Trial Lawyer Nation podcast, Michael is joined by attorney, law professor, and founder of Empirical Jury, John Campbell. They sit down for a conversation about big data for trial lawyers, what John’s company “Empirical Jury” does, legal “urban legends” and their validity (or lack thereof), the most interesting findings he has discovered working on specific cases, and an in-depth look at the effects of COVID-19 on jury attitudes.

The episode starts off with Michael asking John how he got into the field of jury research. John describes his path of starting out as a teacher and deciding to go back to school to become a lawyer. He then joined Denver Law School as a professor studying tort reform in an academic setting, founded the Denver Empirical Justice Institute, and discovered his passion for big data. There, he studied civil justice issues and how jurors behave, but wondered if he could apply scientific methods and big data to law based on an individual case. Basically, he wanted to know what would happen if he had 400 people look at a case instead of the traditional 10-15 people you get with a focus group.

Thus, Empirical Jury was born. John describes the process as working like a “gig economy.” He will share an ad along the lines of, “be a mock juror and get paid to do it,” and is able to recruit hundreds of workers in one day. The work is all done online in their own time, and costs much less per juror than a traditional focus group. With numbers like that, Michael asks what everyone must be thinking – how representative can your jury pool be? Are the respondents all underemployed young people? John says it’s more representative than you’d think. He explains how many people take online surveys for fun, like playing Sudoku. His participants range between 18-80 years old, very conservative to very liberal, and typically earn up to $150,000 a year.

Michael then inquires about the many “urban legends” of law applied to jurors, specifically are any of them true? The short answer is no, but John dives into some surprising details. The moral of the story is to avoid stereotyping based on factors like race or gender, but to instead focus heavily on their responses to bias questions. A juror who believes the burden of proof is too low for the plaintiff’s lawyer being placed on the jury can have detrimental effects on the outcome of the case.

John goes on to share some of his most interesting findings. The first addresses the idea that if you ask for more, you get more. He has found this to be true based on the anchoring principle, with an interesting caveat – the amount you ask for directly affects liability. Typically, the liability climbs the more you ask for until you hit “the cliff.” He shares a shocking example of this in practice and concludes with, “You’re your own damage cap.”

The conversation shifts to the highly debated topic of COVID-19 and its effects on jury attitudes. John has conducted extensive research on this topic, including a survey of 1,500 jurors asking questions about COVID-19 and trial options. He lists a number of shocking statistics and concludes that to seat a jury today you would have to account for a loss of 50% of jurors before asking a single voir dire question not related to COVID-19. Knowing this information, another vital question remains – do the remaining 50% of jurors skew towards the defense or the plaintiff? John explains how the answer is more complicated than most people think, but goes on to share some in-depth findings which have huge implications for the future of jury trials.

John continues by describing another study he conducted where he asked 1,200 jurors how they would prefer to participate in a jury, including a variety of in-person and virtual options. The respondents had a surprising favorite – the option to watch the case via video recording from home, on their own time. While this may sound far-fetched, John describes a series of strategies which could be used to make this a success.

With virtual trials becoming a new possibility, many plaintiff’s lawyers are wondering if a jury can award a big damage verdict without attending the trial in person. With an absence of body language or eye contact, will damages decrease? John doesn’t think so. He cites multiple studies he has conducted in the past where he’s been able to predict huge verdicts within 10% of the actual verdict. He believes if you show jurors real evidence such as day in the life videos, jurors take that seriously and award damages accordingly. He compares this to watching a movie and crying, to which Michael adds, “You just have to change the presentation.” Michael and John both agree that lawyers may have to go to trial this year whether they want to or not, and they reflect on the best strategies lawyers who face this should take.

Another concern commonly noted by plaintiff’s lawyers faced with the possibility of a trial in the era of COVID-19 is if jurors are forced to attend court in person, do they blame the plaintiff because they filed the lawsuit? While some early research indicated they may, John has not found this to be true. His research showed jurors blame the plaintiff and the defense in equal numbers, but the most common answer was, “I don’t blame anyone. I understand this has to happen.” John summarizes the COVID-19 effect on jurors by stating, “While there are some effects on who will show up for jury duty, what we don’t see is a blame for the plaintiff’s attorney.”

This podcast also covers the role of traditional focus groups, using instincts in trial, jury consultant costs, the Fusion Effect, jury attitudes towards medical malpractice cases, how to test if online jurors are paying attention and if their responses should be accepted, what the defense already does with big data, and so much more.

If you’d like to work with John Campbell on a case or would like to learn more about Empirical Jury, you can visit their website at www.empiricaljury.com or email John directly at john@empiricaljury.com.

Click here to view the COVID-19 research PDF John mentions on the show.

 

Bio:

John Campbell, JD is a trial and appellate lawyer turned law professor turned jury researcher.

John trained as a trial lawyer under John Simon, a member of the Inner Circle of Advocates, and then went on to become a successful consumer attorney.  John’s verdicts and settlements exceed $350 million.  John has also handled appeals in the Eighth, Second, Tenth, and Fourth Circuit, as well as the United States Supreme Court and a variety of state courts.  Most recently, John served as lead counsel in a series of class actions against municipalities, including Ferguson, Missouri, who engaged in policing for profit.  The cases led to the eradication of many predatory fees targeted at minorities and the working poor.   John remains a member of Campbell Law LLC.

For eight years John served as a professor at the University of Denver Sturm College of Law.  While there, he founded the Civil Justice Research Initiative, dedicated to better understanding jury behavior through rigorous empirical research.  He continues to run CJRI at the University of Denver and teaches as an adjunct professor.

John’s academic work led to demand for him to study individual cases for plaintiff attorneys.  He ultimately founded Empirical Jury.  In only a few years, Empirical Jury has emerged as a cutting-edge firm that uses big data and scientific approaches to equip attorneys to obtain the best result possible for clients.  Empirical Jury has been involved in verdicts in excess of $550 million and is routinely called on to analyze some of the most complex consequential cases in the country.

During the Covid-19 era, Empirical Jury is also leading the way on understanding the Covid Effect through careful data gathering and analysis.  To date, Empirical Jury has surveyed over 1,200 jurors on topics relating to Covid-19, virtual trials, and jury duty.

 

33 – Julian C. Gomez – Autonomous Vehicles: People v. Machines

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In this Trial Lawyer Nation podcast, Michael Cowen sits down with automotive products liability attorney, Julian C. Gomez, to discuss his expertise on product cases, specifically dealing with autonomous vehicles (AKA: Robot Cars). Most attorneys can relate, but the gist of every other talk Michael has ever heard on this topic, before Julian’s, was that we’re going to get robot cars, they’re never going to crash, and they’re going to put everyone out of business in 5 years. This is certainly what the automotive industry is trying to promise, but the data we have to date suggests otherwise.

Julian’s beginnings, getting into the field of automotive product cases, started back when he clerked for a judge who was the first in the country to try a Ford Explorer/Firestone case. He was able to sit through the trial and learn from some of the best lawyers in the country, which sparked his interest and set him on this path. When Julian started doing automotive product cases, he noticed the engineers were starting to address the legal issues as opposed to the engineering issues behind them. He points out that the engineering is really not all that difficult – the vehicle uses data gathering devices, puts the information into a data processor, which processes the data based on an algorithm, then an answer or result is spitting out, and makes the vehicle do something. Getting too far into the details can sometimes overcomplicate things, which Julian compares to the area of autonomous vehicles and states “I don’t have to be a computer engineer, to know that my computer is broken or to know that it’s working.”

Julian then describes the different levels of crash avoidance technologies (1-6) to include all sides of the vehicle along with the various types (signaling warnings to taking full-blown actions with the vehicle). He goes on to talk about how the levels start to gray out based on human data input as well as how there really are no “driverless” vehicles on the road today, despite what you hear on the news. He also discusses a recent AAA report addressing the confusion regarding the different types of autonomous systems due to the industry, and manufacturers, because there is not a standardized naming structure for these systems.

Interestingly, Julian explains the current way they are measuring the level 3-5 type autonomous vehicles is through disengagements, where the human driver has had to take over the car’s actions instead of it driving itself. In comparison, Apple had roughly 1 disengagement every 1.2 miles whereas, on the opposite end of the spectrum, Waymo had roughly 1 disengagement every 10,000 miles. And while there is a huge disparity between the top performers and the bottom, and numerous tragedies throughout the industry, Julian points out the real problem is there haven’t been enough vehicle miles driven to know how safe they are going to be. He also talks about the millions of vehicle miles driven each year compared to the thousands of deaths that occur on the road, and then extrapolates the data from when Uber had its recent fatality, based on the number of vehicle miles driven by autonomous cars at that point, to determine we would be experiencing around 1.6 million deaths each year. He brings this point home by stating even if you cut that number in half multiple times, it’s still much more than what is happening today on our roads.

Another problem Julian points out is the conflicts that occur between an objective algorithm system in the computer within the car working with a human subjective system. He gives a great example of how we’ve all seen cars, even before we started driving, interact in different ways when the driver is planning to turn right (IE: roll slowly through the light, even if it’s technically not the correct way). As humans, we are able to gauge how much space/time we have between our vehicle and the vehicle turning in front of us, whereas autonomous cars look at it from the standpoint of what the rule is and how it will obey that rule.

Michael points out how the computers can only do what they are programmed to do, making the job of the engineers to think of every possibility and then the safest possible outcome for each of the scenarios unfathomably enormous. Julian notes that as humans, the second most common function our bodies perform (breathing being the first) is seeing. We have been “seeing” and processing things through our eyesight for our entire lives, since day one. Some even suggest for a computer to process the amount of data we have seen in our lives, the computer would be the size of a warehouse, much less the size of a car, or the size of a computer in a car. Julian also discusses the responsibility to predict the unknown, which is nearly impossible, as if to say “tell me everything you don’t know.”

Michael and Julian recount the unfortunate incident in Arizona with the self-driving Uber car, the details of which are likely not what you might have heard previously, nor are they what you might expect (hint, hint – the frontal collision system was turned off, but by whom? Listen to find out). Also, perhaps somewhat shockingly, was the fact that the case was settled in 10 days, which Julian notes, might give you a sense of how Uber felt about their culpability in the case. Michael and Julian also discuss the perceptions of the “auto-piloted” cars as set forth by the marketing departments of the vehicles and how they are not exactly in line with what the cars are actually equipped to do.

The podcast concludes with Julian revealing his process for evaluating which product liability cases to take on as well as the “why” behind them versus simply going after damages, the results of which could do more harm to the legal industry than good when the wrong type of cases are pursued. They also make some predictions as to the future of mass-produced autonomous vehicles and where they’ll likely be used. As this technology continues to evolve, this episode drives home (no pun intended) the vast areas of the unknown in the auto industry in regards to where blame should be placed in such an environment where humans are sharing responsibility with computers, along with the engineers and companies who design them, to keep our roadways safe for everyone.

“Please note the TLN19 discount code mentioned in this show has now expired.”

 

BACKGROUND ON JULIAN C. GOMEZ

Julian C. Gomez is an attorney in McAllen, Texas. Julian was raised in South Texas. Julian is a ninth-generation Texan and his family still ranches on their original Spanish land grant. Julian graduated from Texas A&M University with a degree in Agricultural Economics and was a member of the Corps of Cadets while at Texas A&M.

After graduation, Julian spent time on the floor of the Chicago Mercantile Exchange as an analyst in the cattle futures and options pits. Julian graduated from the University of Houston Law School in 2000. Julian was a law clerk for Filemon Vela, United States District Judge, Southern District of Texas, Brownsville Division and a law clerk for Reynaldo Garza, United States Circuit Court Judge, Fifth Circuit Court of Appeals. After his clerkships, Julian founded The Julian C. Gomez Law Firm and has practiced there since.

Julian has a national and international practice focusing primarily on catastrophic product liability and negligence cases, mass torts, and contingent commercial litigation. Julian is a past Chairman of the American Association for Justice’s Products Liability Section (the largest organization of plaintiffs product liability attorneys in the U.S.); on the executive board of and the vice president of continuing legal education for the Texas Trial Lawyers Association, on the board of directors of and co-chair of continuing legal education committee for the Attorneys Information Exchange Group (the largest organization of plaintiffs automotive product liability attorneys in the U.S.); has served on plaintiffs’ committees in national mass tort litigation; is a graduate of Gerry Spence’s Trial Lawyer’s College; is a graduate of the American Association for Justice’s Leadership Academy; is the special liaison to the National Highway Traffic Safety Administration on behalf of both American Association for Justice’s Products Liability Section and the Attorneys Information Exchange Group; regularly speaks at international, national, statewide, and local continuing legal education courses on topics ranging from federal jurisdiction to products liability; is the 2017 Men’s 40-44, –69k Texas Weightlifting Champion; and has a 3:45 marathon time.

Julian is a U.S. Coast Guard licensed captain, is on the board of directors of the USA Weightlifting Foundation (the foundation for United States’ Olympic weightlifting athletes) the board of directors of McAllen Educational Foundation (the foundation for the McAllen Independent School District), and the board of directors of the Texas International Fishing Tournament (the largest fishing tournament in the State of Texas). In his free time, Julian loves spending time with his number one legal assistant, his daughter, Averri; and is an avid outdoorsman, rancher, photographer, snow skier, and tarpon fly-fishing angler.

For more information on Julian C. Gomez visit his website at https://www.jcglf.com/

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