Reading 2220: Individual and Group Decision Making

Watch this video (approx. 17 minutes long).

From "Conflict Between Intuitive and Rational Processing,"
Veronika Denes-Raj and Seymour Epstein
Journal of Personality and Social Psychology, 1994, 66, 819-829

Subjects. Seventy-nine undergraduates (30 men and 49 women) enrolled in psychology classes at a large northeastern state university participated in the study in exchange for experimental credit and an opportunity to win up to $7.
Materials. A number of transparent, plastic bowls contained various mixtures of red and white jelly beans. The bowls were arranged in pairs consisting of a large bowl and a small bowl. The small bowl always contained 10 beans, one of which was red. The large bowl always contained 100 beans, and anywhere between 5 to 9 of them, depending on the trial, were red. The bowls (more accurately, the rectangular platters) were of a size such that the jelly beans were spread out in a single layer, with no bean hidden from view. To eliminate concern about arithmetic ability, each bowl was clearly labeled with an index card indicating the percentage of red jelly beans it contained.

On seven of the trials, designated as win trials, they [subjects] would win $ 1 if they drew a red bean and would win nothing if they drew a white bean; on the other five trials, designated as lose trials, they would lose $1 if they drew a red bean and not lose anything if they drew a white bean.

The small bowl offered a 10% chance of drawing a red bean on all standard trials. The probabilities (5%-9%) in the large bowl on standard trials were varied according to a Latin Square design...

Subjects were given $ 10 in play money to begin with and told that at the end of the experiment, any earnings they had beyond the $ 10 would be exchanged for real money. They were informed that they could keep their winnings above the amount loaned but would not be held accountable for any net losses...

On each trial, the experimenter presented subjects with the two bowls, announced whether the trial was a win or a lose trial, and called attention to the respective probabilities in the bowls. The experimenter then shielded the bowls from view with a cardboard screen, scrambled the jelly beans, and told the subject to draw a single bean from the bowl of his or her choice. If subjects selected a red bean on a $ 1 win trial, they were immediately given $ 1 in play money. If they picked a red bean on a lose trial, they immediately paid $ 1 in play money to the experimenter.

Nonoptimal choices [subjects choosing from the bowl with a lower percent of winning jelly beans]. An examination of nonoptimal responses on the ... win trials revealed that... a considerable majority (82%) of subjects made one or more nonoptimal choices. The mean number of nonoptimal choices on win trials was 2.18, and the mode was 2, made by 24% of the subjects. Eight percent of the subjects made nonoptimal responses on all five win trials. On lose trials, similar, but not as extreme results were obtained, with 61% of subjects making one or more nonoptimal responses. The mean number of nonoptimal responses for lose trials was 1.34, and the mode was zero, made by 39% of subjects. Four percent of subjects made nonoptimal responses on all five lose trials.

[on win trials] A majority (61%) preferred the large bowl that offered a 9% probability of winning over the small bowl, with its constant offering of a 10% chance of winning. A substantial number of subjects (23%) selected the large over the small bowl when it offered only half the chance (5% vs. 10%) of winning.

How to exploit irrational decision-making
By Tom Albrighton
http://www.abccopywriting.com/blog/2010/03/08/exploit-irrational-decision-making/
[a website for people in advertising]

One of the cornerstones of economics is the theory of rational choice - the idea that people decide how to act by carefully weighing costs against benefits.

In the aftermath of the financial crisis, largely unforeseen by economists, rational choice theory is looking a bit tattered. The rationality of the big players in finance, as well as the supposedly corrective hand of 'the market', has been shown to be an utter fallacy. Investors systematically ignored huge long-term risks, with catastrophic consequences.

Maybe the economists should hang out more with their colleagues over at psychology and organisational behaviour, where researchers have been investigating and documenting flawed decision-making for decades.

For the psychologist or sociologist, a human decision-maker still acts to minimise costs and maximise benefits (or to avoid pain and seek pleasure). But their assessment of those costs and benefits is likely to be hopelessly inaccurate, biased or incomplete.

All this is good news for the copywriter, because these decision-making biases can be exploited in order to nudge a reader towards a buying decision - even though the purchase may not benefit them in any rational or quantifiable way. This post outlines a few of the most common biases that affect our decisions, and how they can be exploited.

Bigness bias

Bigness bias is the tendency to discount relatively small amounts that are measured against much larger amounts. For example, you might regard $1000 as a lot of money to pay for a suit. But to secure a house you really wanted, you wouldn't hesitate to increase your offer by $1000, or even $10,000. Context is everything. For example:

For just 1% of what you take home each month, you can protect every penny you earn from the threat of serious illness or redundancy.

Distinction bias

Viewing options in conjunction makes them seem more different than when they are viewed in isolation. Exploit this by juxtaposing the promoted offering with an alternative option and emphasising some distinction between them. For example:

The EconoHeat offers four different ways to programme your heating - most controllers have just three.

The money illusion

We tend to focus on the face value of money rather than its actual purchasing power. That's why a $10 cashback offer is so appealing - it's free money! - whereas a voucher worth $10 is less powerful, and a free saucepan worth $10 even less so (even if we need one). Exploit this bias by quoting as many cash amounts as you possibly can when savings or reductions are concerned (i.e. talk in pounds or dollars, not percentages or fractions).

Reactance

Reactance is the urge to do the opposite of what you're told. (As the parent of a three-year-old, I can confirm this from extensive field research.)

Right-wingers in the US often harness reactance by suggesting that a 'liberal mafia' is destroying America; by doing so, they position voting for the profoundly conservative Republicans as some sort of rebellion.

Apple did something similar with its 1984 and Think Different campaigns, encouraging computer buyers to resist the domination of IBM. Reactance favours new market entrants, minority choices and fringe players, who can turn their underdog status into a virtue in their marketing by inciting customers to rebel against the established order.

Neglect of probability

Human beings are awful at estimating and comparing probabilities. That's why millions play the Lottery, even though the chance of winning (the 'positive expected value', in risk terminology) is infinitesimal. (Premium Bonds are a much better bet.)

This is great news if you're selling the chance to be, do or acquire something - simply emphasise a desirable upside and people will wildly overestimate their chances of success.

Apply for our copywriting course today and you could be earning big money from home in under two months.

Every new applicant gets the chance to win a fabulous city break for two in Prague.

Déformation professionnelle

Déformation professionnelle is the tendency to view things through the lens of one's own professional skills or culture. You can exploit it when writing for trade magazines or niche websites - since no-one else is reading, go ahead and trot out the jargon, prejudices and petty concerns that your audience love, and generate instant rapport. (Obviously, you need to be able to do this convincingly, and sound like an 'insider', or it will backfire badly.)

Bandwagon theory

This is the tendency to jump on the bandwagon and do what others are doing. I've already covered it in my piece on social proof.

Illusion of control

We believe that we can control, or at least influence, outcomes that we clearly cannot. Most superstitions are rooted in this belief, but more 'sophisticated' systems of thought such as technical analysis (using charts to predict share price movements) are arguably manifestations of the same thing.

Many distress purchases appeal to the illusion of control. Insurance, for example, is often predicated on the idea that the dark, chaotic world out there can be kept at bay for an affordable monthly payment. Some cosmetic treatments also encourage us to change things that, deep down, we know we can't.

http://bigfatgenius.com/3200/Myers%20Diener%20-%20Who%20is%20Happy.pdf


PSYCHOLOGICAL SCIENCE AGENDA
Volume 18: No. 4, April 2004

Affective Forecasting:
The Perils of Predicting Future Feelings
by Brett Pelham, Senior Scientist

We can all remember times when we've found ourselves in trouble by misspeaking, misremembering, or miscalculating. Psychologists Dan Gilbert and Tim Wilson, who study affective forecasting, believe that there are also times when we can get into trouble by miswanting. If you are wondering how anyone could ever miswant something, consider how wanting is intrinsically tied to predicting. To want something is to predict that when we get it, we will feel good. Moreover, the better we think something will make us feel, the more we want it.

Here lies the problem of miswanting. However, the problem is not that people do not know the difference between apple pie and a knuckle sandwich. Instead, miswanting refers to the fact that people sometimes make mistakes about how much they will like something in the future. That is, people often mispredict the duration of their good and bad feelings.

There are several reasons why people mispredict how they will feel about future events. One reason is focalism: we focus too heavily on a single good or bad event when considering how that event will make us feel about our lives. In the case of negative future events, a second reason is that we are typically unaware of the operation of our own psychological immune systems. When a terrible event befalls us, the psychological immune system jumps into action, in much the same way that our physical immune system jumps into action when we encounter a life-threatening virus. However, because the psychological immune system is largely unconscious, most people don't realize its power.

In one early study of affective forecasting, Gilbert and colleagues documented a common belief among assistant professors: they believed that their tenure decisions would strongly influence their long-term happiness. They then checked this prediction by assessing the actual happiness of two groups of former assistant professors: those who had received tenure and those who had not. The result? Those who had failed to receive tenure in the past few years were just as happy as those who had achieved it. Similar results have been observed in labs across the country. For example, a classic study by Philip Brickman and colleagues showed that, even in great quantities, money doesn't buy happiness. A year or two after hitting the big numbers, lottery winners were about as happy as they were before striking it rich.

Researchers who study affective forecasting have shown that our failure to appreciate how quickly we adapt to good and bad events applies to our reactions to such diverse events as having one's beloved team lose a college football game and having someone else win the hand of someone we love. Those who study affective forecasting have also turned their attention to less dramatic events by showing that mildly bad events occasionally bother us longer than seriously bad events. In one study, Gilbert and colleagues asked some people (forecasters) to predict how much they would dislike someone who had recently insulted them. They asked others to predict how much they would dislike the same insulting stranger when they merely observed the stranger insult someone else in the very same manner. Not surprisingly, people expected to dislike a stranger more after they had personally been the victims of his criticisms. But if people's psychological immune systems only kick into gear when they have personally been insulted, then people might actually dislike insulters less when they become the object of attack. When people were put in this actual situation, this is precisely what happened. Victims disliked insulters less than those who were mere observers. Presumably, more intense interpersonal threats often trigger quick, self-protective responses that mute our initial feelings of dislike.

Do these studies have implications for important life decisions? Gilbert and Wilson think so. For example, they noted that in some living wills, people specify that if they ever reach a point at which the quality of their life is very low, they do not wish to receive any special medical attention that would prolong their life. However, when medical researchers interviewed people who were slowly dying and experiencing a very low quality of life, such people almost unanimously reported that they would go to great lengths to add even a few days to their lives.

In another example, Gilbert and Wilson recently noted that drivers may practice safe driving habits more rigorously when taking long trips than when driving around the block. “If a trip to another state triggers the decision to wear a seat belt and a trip around the block does not, the paradoxical consequence is that people may be more likely to sustain injuries in automobile accidents when they are taking short rather than long trips” (Gilbert et al., 2004).


Excerpt from The Wisdom of Crowds by James Surowiecki

One day in the fall of 1906, the British scientist Francis Galton left his home in the town of Plymouth and headed for a country fair.... As he walked through the exhibition that day, Galton came across a weight-judging competition. A fat ox had been selected and placed on display, and members of the gathering crowd were lining up to place wagers on the weight of the ox... Eight hundred people tried their luck. They were a diverse lot. Many of them were butchers and farmers, who were presumably expert at judging the eight of livestock, but there were also quite a few people who had, as it were, no insider knowledge of cattle... When the contest was over and the prizes had been awarded, Galton borrowed the tickets from the organizers... added all the contestants' estimates, and calculated the mean of the group's guesses... Galton undoubtedly thought that the average guess of the group would be way off the mark. After all, mix a few very smart people with some mediocre people and a lot of dumb people, and it seems likely you'd end up with a dumb answer. But Galton was wrong. The crowd had guessed that the ox... would weigh 1,197 pounds... The ox weighed 1,198 pounds...

In May 1968, the U.S. submarine Scorpion disappeared on its way back to Newport News after a tour of duty in the North Atlantic. Although the navy knew the sub's last reported location, it had no idea what had happened to the Scorpion, and only the vaguest sense of how far it might have traveled after it had last made radio contact... The only possible solution, one might have thought, was to track down three or four top experts on submarines and ocean currents, ask them where they thought the Scorpion was, and search there. But... a naval officer named John Craven had a different plan.

[Craven] assembled a team of men with a wide range of knowledge, including mathematicians, submarine specialists, and salvage men. Instead of asking them to consult with each other to come up with an answer... Craven's men bet on why the submarine ran into trouble, on its speed as it headed to the ocean bottom, on the steepness of its decent, and so forth...

[Craven] took all the guesses and used a formula called Bayes's theorem to estimate the Scorpion's final location...

The location that Craven came up with was not a spot that any individual member of the group had picked... The final estimate was a genuinely collective judgment that the group as a whole had made, as opposed to representing the individual judgment of the smartest people in it... Five months after the Scorpion disappeared, a navy ship found it. It was 220 yards from where Craven's group had said it would be...

"Who Wants to Be a Millionaire?" was a simple show in terms of structure: a contestant was asked multiple-choice questions, which got successively more difficult, and if she answered fifteen questions in a row correctly, she walked away with $1 million. The show's gimmick was that if a contestant got stumped by a question, she could pursue three avenues of assistance. First, she could have two of the four multiple-choice answers removed (so she'd have at least a fifty-fifty shot at the right response). Second, she could place a call to a friend or relative, a person whom, before the show, she had singled out as one of the smartest people she knew, and ask him or her for the answer. And third, she could poll the studio audience, which would immediately cast its votes by computer. Everything we think we know about intelligence suggests that the smart individual would offer the most help. And, in fact, the "experts" did okay, offering the right answer-under pressure-almost 65 percent of the time. But they paled in comparison to the audiences. Those random crowds of people with nothing better to do on a weekday afternoon than sit in a TV studio picked the right answer 91 percent of the time...

As it happens, the possibilities of group intelligence, at least when it came to judging questions of fact, were demonstrated by a host of experiments conducted by American sociologists and psychologists between 1920 and the mid-1950s, the heyday of research into group dynamics. Although in general, as we'll see, the bigger the crowd the better, the groups in most of these early experiments-which for some reason remained relatively unknown outside of academia-were relatively small. Yet they nonetheless performed very well. The Columbia sociologist Hazel Knight kicked things off with a series of studies in the early 1920s, the first of which had the virtue of simplicity. In that study Knight asked the students in her class to estimate the room's temperature, and then took a simple average of the estimates. The group guessed 72.4 degrees, while the actual temperature was 72 degrees. This was not, to be sure, the most auspicious beginning, since classroom temperatures are so stable that it's hard to imagine a class's estimate being too far off base. But in the years that followed, far more convincing evidence emerged, as students and soldiers across America were subjected to a barrage of puzzles, intelligence tests, and word games. The sociologist Kate H. Gordon asked two hundred students to rank items by weight, and found that the group's "estimate" was 94 percent accurate, which was better than all but five of the individual guesses. In another experiment students were asked to look at ten piles of buckshot-each a slightly different size than the rest-that had been glued to a piece of white cardboard, and rank them by size. This time, the group's guess was 94.5 percent accurate. A classic demonstration of group intelligence is the jelly-beans-in-the-jar experiment, in which invariably the group's estimate is superior to the vast majority of the individual guesses. When finance professor Jack Treynor ran the experiment in his class with a jar that held 850 beans, the group estimate was 871. Only one of the fifty-six people in the class made a better guess...

There are two lessons to draw from these experiments. First, in most of them the members of the group were not talking to each other or working on a problem together. They were making individual guesses, which were aggregated and then averaged. This is exactly what Galton did, and it is likely to produce excellent results. Second, the group's guess will not be better than that of every single person in the group each time. In many (perhaps most) cases, there will be a few people who do better than the group. This is, in some sense, a good thing, since especially in situations where there is an incentive for doing well (like, say, the stock market) it gives people reason to keep participating. But there is no evidence in these studies that certain people consistently outperform the group. In other words, if you run ten different jelly-bean-counting experiments, it's likely that each time one or two students will outperform the group. But they will not be the same students each time. Over the ten experiments, the group's performance will almost certainly be the best possible. The simplest way to get reliably good answers is just to ask the group each time...

At 11:38 AM on January 28, 1986, the space shuttle Challenger lifted off from it's launch pad at Cape Canaveral. Seventy-four seconds later, it was ten miles high and rising. Then it blew up... The stock market did not pause to mourn. Within minutes, investors started dumping the stocks of the four major contractors who had participated in the Challenger launch... Marton Thiokol's stock was hit hardest of all... at market close [that day], Thiokol's stock was down nearly 12 percent. By contrast, the stocks of the three other firms started to creep back up, and by the end of the day their value had fallen only around 3 percent. What this means is that the stock market had, almost immediately, labeled Morton Thiokol as the company that was responsible for the Challenger disaster... The stop decline in Thiokol's stock price... was an unmistakable sign that investors believed that Thiokol was responsible...

[O]n the day of the disaster there were no public comments singling out Thiokol as the guilty party... the Times declared, “There are no clues as to the cause of the accident.” Regardless, the market was right. Six months after the explosion... Thiokol was held liable for the accident...

Founded in 1988 and run by the College of Business at the University of Iowa, the Iowa Electronic Market features a host of markets designed to predict the outcomes of elections... Open to anyone who wants to participate, the IEM allows people to buy and sell futures "contracts" based on how they think a given candidate will do in an upcoming election... One is designed to predict the winner of an election... the other major kind of IEM contract is set up to predict what percentage of the final popular vote a candidate will get...

If the IEM's predictions are accurate, the prices of these different contracts will be close to their true values [the results of the elections]...

So how has the IEM done? Well, a study of the IEM's performance in fourty-nine different elections between 1988 and 2000 found that the election-eve prices in the IEM were, on average, off by just 1.37 percent in presidential elections, 3.43 percent in other U.S. elections, and 2.12 percent in foreign elections... The IEM has generally outperformed the major national polls, and had been more accurate in those polls even months in advance of the actual election.

Excerpted from The Wisdom of Crowds by James Surowiecki Copyright © 2004 by James Surowiecki.