Skip to content

The Irrationality of Illegal Fishing (Part 4): The Hidden Costs of Poor Enforcement

June 23, 2014

Why does a fisher, or anyone for that matter, break the law? The dominant explanation in crime research is that people break the law after having conducted an analysis of the costs, benefits, and likelihood of getting caught. This is what is called the rational economic theory of crime.

But what if many people break the law for non-rational reasons?  That is, what if people do not usually conduct an analysis of the expected costs and benefits before breaking the law, but instead cheat according to non-economic factors? This is the subject of the very clever book “The Honest Truth About Dishonesty” by behavioral economist Dan Ariely.

I’ve recently had the pleasure of revisiting Ariely’s book to consider how his findings might explain illegal fisher decision-making and point to ways to reduce overall non-compliance in fisheries. It is some of these findings, and my speculations, that I’d like to share with you here as a radically different way to look at the problem of illegal fishing. And since the findings are numerous, I’ll be sharing them in a series format. 

Part 4: The Hidden Costs of Poor Enforcement


In the last post in this series, we explored two factors that Dan Ariely’s theory of irrational cheating suggests can be managed for reduced cheating. These factors are 1) the discontentedness and 2) the mental tiredness of potential cheaters. Importantly, it is likely that these two factors play a role in fisheries management – quite often low-quality management can lead to dissatisfaction among fishermen, and the status of the fishery’s resources and competition can lead to considerable mental tiredness among fishers as they struggle to make a living. Thus, with Ariely’s theory of irrational cheating, we find the first areas where we might act to reduce irrational illegal fishing.

Today I’ll consider four additional factors that can be managed to reduce irrational cheating, and all of these factors relate to how authorities police the system. They are 1) the targeting of worst offenders, 2) the targeting of in-group and out-group offenders, 3) the highlighting of positive deviance, and 4) the stopping of minor cheating problems before they grow. I’m sure you’ll see quite quickly the implications each of these manageable factors have for fisheries management, and I’ll take some time to provide some speculation for each. 

Collectively, the factors discussed here show that there are presently hidden and irrational costs to poor enforcement in fisheries management. That is, poor enforcement does not just simply allow illegal fishers to “get away with it”, but also also permits illegal fishers (or the lack thereof) to send important signals to other fishers about how they should behave.

The first enforcement factor to consider is that of how authorities do, or do not, target the worst offenders when cheating is present in a system. In the course of Ariely’s work, he conducted many clever studies, but perhaps none so stand out as the time he and a colleague employed an actor to act either as a villain or moral agent. The study revealed that cheating is contagious, and particularly so when potential cheaters witness someone rampantly breaking the rules. 

The study again involved Ariely’s math test with a fake shredder, which allowed him and his colleagues to see how much people really cheated (see past posts for more details). Here is the set up to the study, which Ariely affectionally refers to as the “Madoff condition” in honor of Bernie Madoff:

What would happen if our participants could observe someone else— a Madoff in the making— cheating egregiously? Would it alter their level of cheating? 

Imagine that you are a participant in our so-called Madoff condition. You’re seated at a desk, and the experimenter gives you and your fellow participants the instructions. “You may begin!” she announces. You dive into the problem set, trying to solve as many matrices as possible to maximize your earnings. About sixty seconds pass, and you’re still on the first question. The clock is ticking. 

“I’ve finished!” a tall, skinny, blond-haired guy says as he stands up and looks at the experimenter. “What should I do now?” 

“Impossible,” you think. “I haven’t even solved the first matrix!” You and everyone else stare at him in disbelief. Obviously, he’s cheated. Nobody could have completed all twenty matrices in less than sixty seconds. 

“Go shred your worksheet,” the instructor tells him. The guy walks to the back of the room, shreds his worksheet, and then says, “I solved everything, so my envelope for the extra money is empty. What should I do with it?” 

“If you don’t have money to return,” the experimenter replies, unfazed, “put the empty envelope in the box, and you are free to go.” The student thanks her, waves good-bye to everyone, and leaves the room smiling, having pocketed the entire amount. Having observed this episode, how do you react? Do you become outraged that the guy cheated and got away with it? Do you change your own moral behavior? Do you cheat less? More?

So what happened when an actor did just what Ariely describes above? In the Madoff condition, the experiment participants claimed to have solved an average of fifteen out of twenty problems, an additional eight problems beyond the control condition (which had no opportunity for cheating), and an additional three matrices beyond the shredder condition in which there was no actor. In short, the observance of an egregious cheater raised cheating by roughly double, all while the economic gains remained the same.

While the insight here may not offer new recommendations for fisheries enforcement – that we should target the worst offenders, who likely act in a rational manner – it does suggest that the consequences of inaction are much greater than just letting a “bad apple” continue his or her cheating ways. This research tells us that illegal fishing that appears to be rational, isolated, and large-scale can have significant knock-on effects by promoting irrationally-motivated illegal operations among other fishers. 

The second enforcement factor to consider in the cheating game is that of which “worst violators” are targeted by the authorities. In particular, Ariely’s research reveals that it is very important that enforcement officers target fishers that fall both within the main fishing community, or those which we might call members of the “in-group”, and those fisheries that fall outside of it, which me might call members of the “out-group”. 

Why? Well, apparently when we observe egregious cheating by insiders, or members of the “in-group, we observe it as a signal to cheat quite a bit more. This is what we saw described above in the “Madoff” condition. This is a concerning effect, yet we also see that the opposite is true when we observe cheating by members of the “out-group”. In fact, when we observe cheating by outsiders, we apparently see it as an opportunity to affirm our superiority over others, and act quite a bit better than we would have otherwise.

Let’s return to Ariely’s “Madoff” condition, which is described above, to see how we can arrive at this more sophisticated insight into cheating behavior. 

Ariely and his colleagues followed up their Madoff condition with a modification that had the deviant participant (again, secretly an actor) wear clothing indicating he was a student at a rival school. The result was that the other participants did not look upon a significant cheat as a signal to behave the same, but instead saw “Madoff-level behavior” as a signal to abstain from significant wrong-doing. 

Here’s the description:

The structure of our next experiment was the same as in the Madoff condition: our actor stood up a few seconds into the experiment and announced that he had solved everything and so forth. But this time there was one fashion-related difference: the actor wore a University of Pittsburgh sweatshirt. 

Let me explain. Pittsburgh has two world-class universities, the University of Pittsburgh (UPitt) and Carnegie Mellon University (CMU). Like many institutions of higher learning that are in close proximity, these two have a long-standing rivalry…

We conducted all of these experiments at Carnegie Mellon University , and all our participants were Carnegie Mellon students. In the basic Madoff condition, David had worn just a plain T-shirt and jeans and had therefore been assumed to be a Carnegie Mellon student, just like all the other participants. But in our new condition, which we named the “outsider-Madoff condition,” David wore a blue-and-gold UPitt sweatshirt. This signaled to the other students that he was an outsider— a UPitt student— and not part of their social group; in fact, he belonged to a rival group…

[I]f the increase in cheating in the Madoff condition was due to an emerging social norm that revealed to our participants that cheating was acceptable in their social group, this influence would operate only when our actor was part of their in-group (a Carnegie Mellon student) and not when he was a member of another, rival group (a UPitt student). The crucial element in this design, therefore, was the social link connecting David to the other participants: when he was dressed in a UPitt sweatshirt, would the CMU students continue to play copycat , or would they resist his influence? [Emphasis added]

The results of the study did indeed confirm a significant role for the perception of in-group and out-group behavior. The participants that observed the actor cheat when identified as a UPItt student claimed to have solved only nine problems. While this was still more than the control condition (by about two matrices), they cheated far less than if they had thought the cheater was a Carnegie Mellon student!  In all, the introduction of an “outsider” element to the cheating reduced the cheating from about 15 problems to 9 problems!

And even more incredibly, the level of cheating under the outsider condition was even less than under the standard shredder condition, where participants typically cheated by about 12 problems. 

This means that when the violator is perceived to be part of the out-group, irrational cheating can reduce significantly from baseline amounts, while when it is perceived as part of the in-group, irrational cheating can take off. 

The implications for fisheries enforcement are then clear. Fisheries enforcement activities should be sure to target significant cheaters among both in-group and out-group fishers. This recommendation makes me think of the illegal fishing situation in West Africa, where foreign trawlers are responsible for significant amounts of illegal fishing, and are increasingly the targets of enforcement efforts. Yet rarely do we hear about enforcement actions taken against illegal fishers among the domestic fishing fleets in West Africa. It suggests that enforcement agencies may be missing an important opportunity to reduce irrational illegal fishing by not targeting illegal local fishers as well. 

The third enforcement factor that might be better managed to reduce irrational cheating is that of how positive deviants are highlighted among potential cheaters. “Positive deviance” is occurs when a potential cheater acts in an uncharacteristically moral way. (For an example, recall the story of George Washington and the apple tree, when he declared, “I cannot tell a lie.”) Ariely’s research suggests that the observation of positive deviance it is yet another factor affecting cheating. 

Ariely and his colleagues came upon the role of such moral reminders when they modified the Madoff condition in yet another way. In particular, they had their actor dressed as an “in-group” student of Carnegie Mellon, but rather than cheat, the actor pointed out that he could cheat egregiously and then appeared to take the math test as any other. Thus, the actor demonstrated his capacity to cheat, and appeared to restrain himself. 

Here again is a description:

[W]e set up another experiment, with a different type of social-moral information. In the new setup, we wanted to see whether erasing any concern about being caught but without giving an enacted example of cheating would also cause participants to cheat more. We got David [the actor] to work for us again, but this time he interjected a question as the experimenter was wrapping up the instructions. “Excuse me,” he said to the experimenter in a loud voice, “Given these instructions, can’t I just say I solved everything and walk away with all the cash? Is this okay?” After pausing for a few seconds, the experimenter answered, “You can do whatever you want.” For obvious reasons, we called this the question condition. Upon hearing this exchange, participants quickly understood that in this experiment they could cheat and get away with it. If you were a participant, would this understanding encourage you to cheat more? Would you conduct a quick cost-benefit analysis and figure that you could walk away with some unearned dough ? After all, you heard the experimenter say, “Do whatever you want,” didn’t you? 

When this question was posed, and the actor did not proceed to get up immediately and take all the money possible, a very interesting thing happened. The participants still cheated, but by far less than in the standard “Madoff” condition…and even less than the standard “shredder” condition. In this “question” condition, the participants claimed to have solved an average of ten problems— about three more problems than in the control condition (which means they did cheat) but by about two fewer problems than in the shredder condition and by five fewer than in the Madoff condition.

Did you get that? They cheated by less when it was pointed out that they could cheat and get away with it! Now, Ariely saw that only the question-making was of important in this condition, but its just as clear that the condition involved a clever participant (secretly an actor) that chose not to act as he had suggested he might. To me, it leaves a very clear suggestion, that the highlighting of positive deviance, or good behavior, could result in a significant reduction in baseline irrational cheating. 

As for fisheries management, this means there could be a significant benefit if enforcement activities did not just highlight the bad behavior of illegal fishers, but also the good behavior of highly-compliant fishermen. 

The fourth and final enforcement factor that we will consider in this post is how authorities work to end minor, perhaps even innocuous cheating problems. This is relevant as the work of Ariely and his colleagues shows that such minor cheating can lead to cheating elsewhere, and in much more serious ways. 

In other words, cheating can snowball. This was revealed by another study that involved Ariely’s math test and fake shredder, only this time, participants were asked to wear either fake or real designer sunglasses (in fact, all were real).

Here’s the set up:

AT THE START of the experiment, we assigned each woman to one of three conditions: authentic, fake, or no information. In the authentic condition, we told participants that they would be donning real Chloé designer sunglasses. In the fake condition, we told them that they would be wearing counterfeit sunglasses that looked identical to those made by Chloé (in actuality all the products we used were the real McCoy). Finally, in the no-information condition, we didn’t say anything about the authenticity of the sunglasses. 

Once the women donned their sunglasses, we directed them to the hallway, where we asked them to look at different posters and out the windows so that they could later evaluate the quality and experience of looking through their sunglasses. Soon after, we called them into another room for another task. What was the task? You guessed it: while the women were still wearing their sunglasses we gave them our old friend, the matrix task. 

Now imagine yourself as a participant in this study. You show up to the lab, and you’re randomly assigned to the fake condition . The experimenter informs you that your glasses are counterfeit and instructs you to test them out to see what you think. You’re handed a rather real-looking case (the logo is spot-on!), and you pull out the sunglasses, examine them, and slip them on. Once you’ve put on the specs, you start walking around the hallway, examining different posters and looking out the windows. But while you are doing so, what is going through your head? Do you compare the sunglasses to the pair in your car or the ones you broke the other day? Do you think, “Yeah, these are very convincing. No one would be able to tell they’re fake.” Maybe you think that the weight doesn’t feel right or that the plastic seems cheap. And if you do think about the fakeness of what you are wearing, would it cause you to cheat more on the matrix test? Less? The same amount? 

The result of the study was that many more people cheated when they were wearing the “fake” sunglasses than when they were wearing the “real” sunglasses. While 30 percent of the participants in the authentic condition reported solving more problems than they actually had, a whopping 74 percent of those in the fake condition reported solving more problems than they actually had. (Meanwhile, in the control condition, in which the authenticity of the glasses was not revealed, only 42 percent of the women cheated, which was not – in fact – statistically different from the “authentic” condition.)

Ariely and his colleagues found this snowballing effect rather intriguing, so continued to play with their “real” and “fake” sunglasses in other ways. In a rather different study, Ariely & Co. had their participants play a few hundred rounds of a game where they counted dots for money, and – per usual – there was ample room provided for people to cheat.  

What happened when this was combined with “real” and “fake” sunglasses? Interestingly, those with “fake” sunglasses cheated much much more. And while all participants cheated more over time, it was particularly bad for those people who somehow got it in their head that they were the sort of people that do such things (i.e. by wearing fake sunglasses).

I think we all might agree that these results are rather surprising. Can just believing you’re wearing fake designer sunglasses lead you to be someone more likely to steal money in a game? Apparently, the answer is yes. 

The study’s conclusion makes me rather fearful for fisheries where fishers are regularly permitted to cheat in minor ways. I’ve seen such situations arise when enforcement officers are sympathetic to fishers’ needs to fish “every now and then” during closed seasons, and when regulations are so tricky that fishermen might be permitted to fish for significant time periods without the proper documentation. 

This all goes to suggest that it can be rather important that fisheries managers work to ensure that most of their fishers are not just “compliant where it matters” but instead endeavor to have most fishers in 100% compliance with existing rules and regulations. I would suspect that some cases might require that there simply be more enforcement actions taken to engender compliance, but I could also see how this might require some reform of the rules and regulations to reclassify regular fisher behavior as acceptable.  

In sum, Ariely’s theory of irrational cheating offers us a variety of factors related to enforcement activities that might be better managed to reduce irrational illegal fishing. These factors are 1) the targeting of worst offenders, whose actions can have significant knock-on effects; 2) the targeting of both in-group and out-group offenders, which provide positive and negative signaling to other fishers; 3) the highlighting of positive deviance, which can permit fishers to reflect on their behavior and act in a more moral manner; and 4) the stopping of minor cheating problems, which can snowball into serious problems over time.

1. Act in a timely manner to catch the worst offenders. Delaying the apprehension of worst offenders can irrationally signal to other fishers that it is ok to cheat.

2. Ensure that both in-group and illegal fishers are targeted. Observing illegal fishing by members of a fisher’s “in-group” can be a meaningful signal that it is ok to cheat as well, while observing illegal cheating by outsiders – ideally through their apprehension – can allow fishers to reflect upon their behavior and act more morally.

3. Highlight the good behavior of compliant fishers. Fishers’ awareness of other fishers that chose not to act in a non-compliant manner offers an opportunity for they themselves to reflection and improve upon their own behavior.

4. Aim for 100% compliance, even when minor cheating appears to be innocuous. Cheating begets cheating, and an insignificant cheat can lead to more serious problems elsewhere. This might mean increased enforcement, but could also include regulatory reform.

Of course, a bigger question among enforcement agencies is “Which fisheries face significant illegal fishing?”  This is because enforcement agencies typically face steep budget constraints and must be quite careful about how they deploy their resources.  Again, Ariely’s research offers some suggestions as to how we might measure irrational illegal fishing, which as we’ve previously discussed, could well be more damaging to a fishery than rational, economically motivated illegal fishing.  I’ll be tackling this in the next post.

No comments yet

Leave a Reply

Please log in using one of these methods to post your comment: Logo

You are commenting using your account. Log Out /  Change )

Twitter picture

You are commenting using your Twitter account. Log Out /  Change )

Facebook photo

You are commenting using your Facebook account. Log Out /  Change )

Connecting to %s

%d bloggers like this: