We knew before starting this blog that few others are interested in making persuasive psychology practical. It’s frustrating, but it forces us to research carefully and it ensures our ideas are new and potentially useful, not exhaustively re-hashed impractical nonsense or indecipherable jargon-laced dissertations. The dearth of information about every-day, real-world, common-man influence strategies is a blessing and curse; we’re doing what few have done before, but few are there to help us do it.
Last week, though, we got help.
In our post Exploring Unpredictable Social Strategies, we made a bold claim: we said that the best way to control your subordinates is to reward them randomly when they do something you like, and that no other method would produce the same results. We based our claim on solid evidence that random ratio reward schedules induce compliance by trapping reward-seekers in a common probabilistic error called the gambler’s fallacy. After that, we introduced you to the hot hands fallacy, and advised you to be open with your subordinates about the process, lest they commit this error – the wrong error. The advice was an even bigger leap than our previous claim because we didn’t have – and didn’t expect to find – a study comparing the relative effects of each kind of fallacy. The concept was just too new. So we were surprised last week when we found one with this subtitle: “The hot hand versus the gambler’s fallacy.” Rarely does a search turn up results like that; we eagerly read it.
The study turned out to be better than we could have hoped. Not only did it address the same question we were asking ourselves, it did so by experimenting with the same random process (coin-tossing) we’d been using as an example, and its findings suggest we were right: random ratio reward schedules work best if everyone knows that the process, not you, determines who wins and who loses.
The Study
Canadian researchers Christopher J. R. Roney and Lana M. Trick wanted to identify the cognitive mechanics behind the gambler’s and hot hands fallacies. Because the fallacies predict different outcomes and assume different processes, each one should only occur in mutually exclusive situations. When outcomes are genuinely random, everyone should be committing the gambler’s fallacy. When outcomes are plausibly skills-based or are possibly rigged, everyone should be committing the hot hands fallacy. But have you ever heard someone claim they’re “on a roll” after they win twice or three times in a row? Of course you have. Have you ever seen a gambler who’s unable to quit while he or she is ahead? Hopefully not, but perhaps. Do you know someone who picks their own “lucky” lottery numbers every week? More than likely. In all these examples, the person is committing the hot hands fallacy even though the game is random. Why?
Roney and Trick hypothesized that the cognitive mechanics involved in each of these fallacies activate or deactivate whenever someone’s beliefs about a process’s outcomes change. If a person believes he or she or some other human being is somehow skillfully controlling outcomes previously believed to be merely random, then the person should switch from using the gambler’s fallacy to using the hot hands fallacy. For coin-tossing, it would look like this: changing a person’s focus from the random nature of the coin to the real or imagined skills of the coin-tosser should induce a switch in fallacies.
Testing this theory was incredibly simple. The experiments involved 124 undergrads (the subjects) watching one of two women flip a coin. In the experimental conditions, one woman would flip seven times, and lie about what came up such that the results were always either HTHTTTT or THTHHHH (alternation followed by repetition). The subjects would bet on the next outcome each time and record their confidence in the bet. Before the eighth flip, though, the woman would say one of two lines: “Wow, I’m really throwing a lot of [heads or tails],” or, “Wow, this coin is really coming up with lot of [heads or tails].” (In the control condition, these lines were not said.) Then, the woman either kept flipping or handed the coin off to the second woman (who, ostensibly, was there to record the “results.”) You can see that depending on which of the two phrases was said in between the seventh and eight flips that the researchers intended to re-focus the subject’s attention, changing it ever so slightly toward the woman’s “skill” (the first phrase), or even more intently on the coin (the second phrase). The researchers also predicted that when the coin changed hands, the gambler’s fallacy would remain in effect regardless of which phrase preceded the eighth flip.
They were mostly right. As expected, nearly all of the control subjects committed the gambler’s fallacy and predicted the streaks to end on the eighth flip. And, as expected, when the coin changed hands, the gambler’s fallacy was predominant in all cases. But just a small majority of the subjects who’d heard the first phrase committed the hot hands fallacy and guessed that the repetition would continue. Something similar happened to the subjects who’d heard the second phrase: about half of them committed the hot hands fallacy, probably because the wording of the second phrase led them to believe the coin itself was biased or “charmed.”
The most revealing data, however, are the confidence scores of the bets placed by the subjects. Overall, those who committed the hot hands fallacy in the first experimental condition were much more confident in their bets on the outcome of the eighth flip than those who stuck with the gambler’s fallacy. The highest confidence in bets on reversals, of course, occurred in the control condition.
So, what does this mean for our reward system? Well, if you keep your method secret from those you want to control, you might lose about half of your rewardees to the hot hands fallacy; once you hit a streak, half of them will expect it to continue, and those who don’t won’t hesitate to change their minds if it does continue. In other words, they’ll stop trying. Keep it transparent, though, and they will stay busy doing what you want them to.
Damage Control
Let’s say you’re the supervisor of a group of employees (assembly-line workers, for instance.) You want your workers to be more efficient because your superiors are worried about their bottom-line. You remember from business school that incentives are a good way to achieve this goal, but your workers are already well-paid and enjoy several generous benefit packages, so you’re at a loss for how to incentivize them more. That night, after work, you read on Practical Persuasion that a random-ratio reward system based on a coin-toss is the best way to induce compliance. The next morning, you call your team together and tell them that each day of the month, whoever is 95 percent productive or better could get $100 cash. You don’t tell them that the result is determined randomly because you’re afraid they won’t play along.
For two weeks, your employees operate at break-neck speed. Efficiency is consistently in the 80s and 90s, even on Fridays. A third of your employees are 90 percent productive or higher. As you expected, about half of those get bonuses. The money you saved the company on labor and utilities more than makes up for the extra cash. The bosses sing your praises.
The next two weeks, though, are different. Productivity flat-lines, and then drops back to previous levels. You remind your workers that the productivity game is still on, but they don’t seem to care. Only half of the original productivity all-stars from before make the cut this time. The bosses suddenly can’t remember your name.
After two more weeks of low productivity, HR organizes a company-wide teamwork seminar that wastes even more time and money. You also have to meet for two hours with the 21-year-old economics major who the bosses hired on as a “business strategies consultant” (he gets paid twice as much as you do, by the way). You’re pissed. You go home, get drunk, and resolve to expose those two bastards at Practical Persuasion for the frauds they really are.
We hope this doesn’t really happen to anyone. If it does, don’t hit “send” on that angry email just yet. We now know that when people aren’t aware that a game is random, they assume it’s rigged after seeing several successively repeating outcomes. Also, a bit more than half of them will be almost certain that it is so. To get them back, try this: explain how your system works…and then secretly scrap it. Purposefully alternate your responses for a while. Many people often mistake these alternations for randomness, so intentionally switching back-and-forth like this should get most of the skeptics back on board. Be sure to submit to the coin (or whatever random process you’re using) once you’re secure.
Sources
Roney, C. J. R., & Trick, L. M. (2009). Sympathetic magic and perceptions of randomness: The hot hand versus the gambler’s fallacy. Thinking and Reasoning, 15(2), 197 – 210.
