In conversation with Bolch Judicial Institute Director David F. Levi, Dan Ariely offers a behavioral scientist’s take on motivation, incentives, and sanctions in legal settings.
As a teenager, Dan Ariely suffered extreme injuries as a result of a terrible accident — a flare exploded next to him, burning more than 70 percent of his body. He spent years in the hospital recovering — and found himself with a bird’s-eye view of the human interactions happening all around him. He observed people with fascination, especially the nurses who cared for him. They insisted, for instance, on pulling off his bandages quickly, refusing his requests to allow him to remove them himself, to take breaks, or to even slow down. He has called the experience his “immersive introduction to irrationality.”
Ariely began to wonder whether he might be able to study, empirically, the least painful approach to this procedure and the thought processes motivating the nurses’ decisions. As he discovered, the age-old practice of “ripping off the Band-Aid” was not supported by science: His studies found that most people, like him, would rather face lower levels of pain for longer periods of time rather than higher levels of pain for shorter periods of time. His research prompted more questions, more studies, and more answers.
Now a professor of psychology and behavioral economics at Duke, Ariely investigates the incentives that drive people to behave the way they do and how to create incentives to drive people to improve their lives. He is a founding member of the Center for Advanced Hindsight and the author of several books, including Predictably Irrational and The (Honest) Truth About Dishonesty: How We Lie to Everyone — Especially Ourselves. Professor David F. Levi, director of the Bolch Judicial Institute and former Chief United States District Judge for the Eastern District of California, spoke to Ariely about his research and its overlap with the goals of the legal system.
Levi: Your work strikes me as of great interest to judges and legislators because you study how best to induce or encourage certain kinds of conduct or decision making in response to certain kinds of incentives or sanctions. What kinds of decision-making issues are you focused on right now?
Ariely: At Duke, my research lab focuses on financial decision making and health. And we basically go to different institutions and try to incentivize people to behave better. We are of the opinion that information doesn’t change behavior, and instead what you need to focus on is changing the flow of decision making. So we try to change systems, not to change people. That, by the way, I think is the huge question and challenge for the law, where we in general give less credit to people and more credit to systems. We think that if you have bad behavior it’s not because people are bad, it’s because the systems are not designed in line to support good behavior.
For example, with money: If we can get people to deposit some money into a savings account, directly from a pay-check, that’s a really good idea. If you give the option of whether to deposit or not, so that it is not automatic each pay period, the same kind of savings won’t really happen.
Then, on top of that, I have a group in Israel. There, we work only with the government on changing behavior. For instance, we have changed food labels to help people pick food. What we did there was to move away from the American label that gives lots and lots of information that people don’t read. Instead, we created a fairly simple system that has a green circle if something is healthy and a red circle if something is unhealthy. We do other things, too. We try to get people to use less cash, and pay taxes, and rideshare, and we try to change people’s attitude towards the government, and we try to get kids to study more computer science, and so on.
And finally, I have a few startups, which happens when I have an idea that I like but nobody else likes.
Levi: I think your work on rule-following and cheating would be of particular interest to judges. What can you tell us about that?
Ariely: My colleagues in my lab and I did a lot of research on cheating, and we found that if you put good people in situations that contain inherent conflicts of interest, then bad results happen. And it’s not about people, it’s again about bad systems.
So one of my startups is a company called Lemonade. And Lemonade is working on being an insurance company without any conflicts of interest. How could you do that? If you think about the regular insurance company, they take money from consumers. They take, they take, they take, they take. At some point, something bad happens to the consumer, and then the insurance company has to pay. But of course the insurance company doesn’t want to pay; they would be better off not paying than paying. And consumers, of course, know that the insurance company prefers not to pay, so they cheat. The insurance company of course knows that consumers cheat, so they make it difficult and complex and require paperwork and all kinds of things.
But if you think about this system, it’s inherently based on conflict of interest and distrust. So we said, “Let’s fix it.” How? We decided to build a system with three parts: We have consumers, an insurance company, and a charity. And when people sign up, we ask them to name a charity that they really care about. And let’s say they picked World Wildlife Fund. And then they paid, they paid, they paid. And when it’s time for the insurance company to pay claims, we pay claims. We take a fixed income, so our amount of profit doesn’t change depending on whether we accept or deny claims. And at the end of the year, all the money that is left over in the pool of those consumers that picked the World Wildlife Fund goes to the World Wildlife Fund.
So there’s a couple of things here. One is we make the same amount no matter what. It doesn’t matter if you had bad luck or something bad happened to you; our profits are not going to change. The other is that if consumers cheat, they’re cheating their favorite charity.
Anyway, we started this insurance company, and it took a really long time to get approval from regulators. Because, I think, the regulators really do not understand the benefit of having no conflict of interest. And from the beginning lots of very good things happened. So for example, less than two weeks after we started, we got an email from somebody that says, “You insured my apartment. I submitted a claim because my laptop was stolen. But it turns out it wasn’t stolen — I just misplaced it, and now I’ve found it. How do I return the money?”
And on that day I wrote all my friends in big insurance companies and asked them, “What is your policy for this?” And, as you can imagine, they don’t have one. And, you know, it can’t possibly be that the big insurance companies don’t have consumers who claim things and later discover their mistake. But I think what happens is that nobody is honest about it and comes back to return the money.
So that makes me incredibly proud, because I think it shows that if you design a system that assumes trust, you get trust back. If you create a system that assumes distrust, you get distrust back.
Levi: Our system sometimes gives insurance companies some incentives to deny a claim or at least delay payment. How do you address this?
Ariely: At Lemonade, we don’t have that. We take a fixed amount of profit, let’s say ten percent. We guarantee that that is our profit, and that’s it. Yes, it is the case that if we hold onto the money for longer, we can probably make a bit more money out of this, but that’s not our approach. But ten percent is what we get. And we take it on day one. We don’t have to wait until claims are settled and then we see how much money we made. We just say, “No, we’re selling you insurance, this is what we’re making, that’s the deal.”
Levi: What kinds of work have you done on the topic of motivation?
Ariely: I’ve been doing lots of research on motivation. And the really sad thing about my research on motivation is that every time I go into a company, I find that it’s incredibly easy to improve motivation. And the reason it is sad is because it means that people don’t spend enough time thinking about how to increase motivation, even though it’s so easy to do.
So, a few years ago, I got an initial set of data of how companies treat their employees, and I used this data to play a simulation game in the market. I said, imagine I got my first data about how companies treat their employees in 2006. And imagine that I used that data to invest in the stock market in 2006. And then I got new data in 2007, and so on and so forth. And it turns out that basing your investments on how companies treat their employees can beat the S&P 500.
For example, it turns out that level of salary doesn’t matter very much. But fairness in salary matters a lot. So, in terms of stock return, the companies that pay in a fair way do better than those companies that don’t pay in a fair way. And it turns out that companies where men and women are treated more equally in all kinds of ways, not just in salary, do about 7.4 percent a year better than companies that mistreat women, relatively speaking.
There are two important things there. One is to make it clear to companies that treating their employees well is important. Lots of CEOs stand on stages and say, “The quality of my people is the best thing I have.” They all say, but do they act on that? And the answer is no. The second thing is that what matters to employees isn’t always what people think matters. For example, while salary doesn’t matter so much, relative salary matters a lot. Bureaucracy, too, seems to crush motivation. All of these kinds of things are a big deal.
On the legal side, one of the things I’m hoping is that right now we ask companies to report their finances to investors. And not just the usual measures. I think we should ask companies to record how much they are investing in their employees. Right now, when companies buy a warehouse, that’s considered an investment. When companies invest in employees, it’s called a cost. I think we need to change that. We need companies to also have an interest, and be rewarded in the stock market, for treating their employees well.
Levi: What are your thoughts on the two salary models that large law firms tend to follow — internal transparency about salary, or absolute darkness on the matter (and perhaps even a partnership agreement that prohibits asking others what they make)?
Ariely: I would say this: Fairness is very important for performance and satisfaction at work, but fairness is not about revealing or not revealing salaries. You can imagine revealing when it’s not fair, and you can imagine reveal-ing when it’s fair. So whether to reveal salary is a separate issue from fairness. But the other thing to consider is that being transparent about salary can be a recipe for creating competition. So then the important question is: Do we want to create competition? In most businesses, competition is a very mixed blessing. You might want some competition, but what you want more is lots of collaboration and cooperation. I don’t know how it is in law firms, but in most areas of life you want people to help each other. And if people are focusing only on individual achievements, you’re going to basically destroy collaboration. Oftentimes the focus is on salary, but that’s not the right approach. The right approach is to focus on human motivation.
Let’s pretend we had no salary. Would these people still be interested in working here? How hard would they work? And you might say, well, without a salary, they might not be able to show up, etc., and that’s true. But what types of salaries would help them be motivated? And what do we want? Do we want collaboration? Do we want fairness? Do we want them to worry about losing their job? Do we want them to worry about not being able to pay their kid’s school tuition by the end of the year? Or don’t we want those things?
Now, if you have a job that requires peoples’ brains, and thoughtfulness, and concentration, it’s very unlikely that you would want them to worry about anything. You want them to be fully focused. For example, I can’t imagine that you would want to go to a surgeon who has been told that their ability to pay for their kid’s college tuition is going to depend on the quality of the surgery. So, in that context at least, it is not a good idea to start by focusing on the outcome. What you need to do is to start by saying what you want from people.
Levi: There’s been a lot of attention in the legal community lately on “fees and fines,” which are financial penalties for petty offenses, like traffic violations. In addition to penalizing certain conduct, they are also intended to help local governments raise money. These fees and fines fall heavily on poor people, and a minor violation with a minor financial penalty can turn into something very costly — like a traffic violation, which might cost $25 initially but then is enhanced by another fine for failure to appear because the person cannot get to court to pay the fine. Or the system penalizes people in a way that is contrary to its intended purpose — like suspending someone’s driver’s license when they fail to pay child support, which means they can no longer drive to work, and so they lose their job and, thus, can’t pay their child support. What would you recommend when it comes to these kinds of sanctions?
Ariely: So first of all, let’s talk about deterrence. Deterrence is not so much influenced by the size of the penalty. It’s influenced by the probability of the penalty. Right now, for example, the penalty for texting and driving is dying and killing other people. It’s a very, very high penalty, but it doesn’t deter anybody. Because people view the likelihood of that outcome as small. Imagine, in contrast, that every time you took out your phone and texted while driving, I would charge you $10 immediately, directly out of your bank account. Forget how I do this, but we could do something with a penalty of $10 if it was certain to be enforced 100 percent of the time.
We live in this world in which we think that probabilistic penalties are going to work out, but they don’t. They don’t deter. And actually, when it comes to probabilistic penalties, you learn the wrong lesson. Imagine if you think the probability of killing someone while texting and driving is 1 percent. One day you text and drive, and nothing happens. At the end of the day, you say, “Oh, the probability is really only three-quarters of a per-cent,” and so on as you continue to text and drive without a problem. So bad behavior is not influenced by delayed probabilistic penalty. And we need to get our mind around that because so much of our penalties are both delayed and probabilistic.
So, when it comes to fees and fines, adding more fines when people don’t show up is not helping. It’s not a good incentive system. In particular, taking away things that are crucial for people to make an income are just a bad idea.
I take my lab with me to the Durham jail once a year to study the cases there. We find that frequently prisoners there have been convicted for one thing on top of another on top of another, and then they have to get a job and they have to drive and then it gets worse and worse.
If it was me, I would try to figure out a system that encourages people to behave in a better way. So let’s say somebody doesn’t pay child support. I would say, “Here is your punishment: We will contact your employer directly and you will have to pay directly from your paycheck.” Or, for someone who is not making a car payment, “We are going to put an app in your phone that does X, Y, or Z.” Or, “We’re going to give you the kind of insurance that increases every time you do something unsafe.” I would do all this rather than saying, “Let people have a lot of freedom in life to make any decision they want, including bad ones, and then we will just fine them on the back end.” Instead, I would basically force people into systems that would make it more likely that they will behave well.
Levi: What about offering a carrot, rather than a stick? Suppose you said, “If you pay your child support on time, then the city will add to what you paid for your child.”
Ariely: We would certainly try to do that. There’s a very nice non-profit organization [The Good Plus Foundation, goodplusfoundation.org] that responds to this image of a child-support-paying father as only there to provide money. They offer GED classes and tell the fathers, “If you come to a GED class, as a reward, we will give you diapers, or we will give you toys to take to your child.” And in this way, they basically give the fathers reasons to play a different role in their kids’ lives — rather than just the financial role. They owe money. But how motivating is it to just owe money, to just be a wallet? So how do you take the basket of things that you want to encourage and how do you build the whole package around it?
Levi: What kinds of judicial decision-making issues have you studied?
Ariely: I’m very interested in how judges determine bail. We just started looking at this issue, and so far it seems many judges have some kind of rule of thumb about it, which is interesting. As you know, if people get bail from a bail bond, they lose 10 percent up front, and they never get it back. That’s a tremendous loss for people with low income, and we need to find better ways to get judges to depart from their default of bail and get them to think more generally about the welfare of the person in question.
Levi: Let’s say that our audience of judges were to say, “I volunteer to be part of any experiment that Dan Ariely wants to run on judging.” Do you have any immediate thoughts as to what sort of an experiment you might like to design?
Ariely: I would, and I think that the first step would be something about their views on what biases exist and what role those biases play in the legal system and, in particular, how they influence judges. And then once I had their opinions about what biases matter and to what degree, I would try to test what biases really affect them and in what ways.
Levi: Dan, thank you very much for taking time to talk with me. Your research offers useful insight for anyone who works with people and the consequences of their decisions.