We misinterpret reality

Recently a newspaper headline caught my eye:
A man mistook the sounds of DVD porn for a woman's pleas for help. Now he is accused of breaking into someone else's apartment with a sword in his hands.

The article was about a man named James Van Iveren, and the events took place in the suburbs of Milwaukee. One morning Van Iveren, then thirty-nine years old, heard sounds from the apartment on the floor above. According to him, very clear and ambiguous sounds. A woman screamed. “She was begging for help,” Van Iveren said.

At first he tried not to pay attention to the screams, but soon realized that this was simply impossible. There was no telephone in the house, so the man could not call the police. And then he grabbed the only weapon he had - a family heirloom, an ancient sword - rushed up the stairs and knocked down the door to his neighbor's apartment...

And he saw the neighbor himself, Bret Steighorst, a thirty-three-year-old student at a local technical college, who at that time was watching a porn film called Casa de Culo (Culo delicately translates as “ass”). “The film was in Spanish, and I didn’t understand a word,” Steighorst later admitted to reporters. “I bought it for my girlfriends.”

Van Iveren decisively asked the owner of the apartment where the woman who had just screamed was. Steighorst said that there were no women in his apartment. He even showed the uninvited guest the house, opening closet doors to prove that no one was hiding there. Finding no victims, the failed savior left with his sword. And after some time the police came to him. He was charged with criminal trespass causing damage. Soon all the media wrote about this case.

“Now I feel terribly stupid,” Van Iveren admits. “The whole thing was just a big, stupid mistake.”

How we interpret reality

Indeed, it turned out stupid. Meanwhile, Van Iveren's misplaced chivalry serves as a clear illustration of one very common source of error - interpretation. Many everyday misunderstandings occur precisely because of incorrect interpretation. You have probably encountered such problems without even realizing it. Let's say, have you ever tried to open the lock of someone else's car with your key in the parking lot of a shopping center?

Perception works in different ways - sometimes through the eyes, sometimes through the ears. For example, a few years ago, researchers in the UK decided to determine whether music influences the choice of wines people buy in grocery stores. To do this, they installed a tape recorder on the top shelf in the wine department of one store. Below, on the rack itself, four varieties of French and German wines of comparable price and quality were displayed. And then alternately, every other day, they played French and German music to the customers. It turned out that on days when French melodies were played, French wine sold better than German, and when German melodies were played, people bought German wines more actively. (Moreover, the majority of the store’s customers initially mainly preferred French wines.)

By the way, the difference in sales cannot be called insignificant. For example, when French music was playing in the store, forty bottles of French wine were sold per day, and when German music was playing, sales dropped to twelve bottles. The same trend was observed in relation to German wines: when German compositions were played, people bought about twenty bottles a day, and when French chansonniers were played, its sales dropped to eight bottles.

Interestingly, most people did not seem to realize how the music played in the store affected them. When leaving the shopping area, the researchers asked customers to fill out a questionnaire. And of the forty-four people they surveyed, only six (about 14 percent) admitted that they made a choice influenced by music. This result clearly illustrates the reason for the power of framing - the thing is that we, as a rule, have no idea about the influence of this effect on our decisions.

The lion's share of what we still know about the framing effect, or framing effect, we know thanks to the works of Princeton University professor and Nobel Prize winner Daniel Kahneman, as well as the now deceased member of the National Academy of Sciences, Amos Tversky. These scientists studied how people make decisions, especially under conditions of uncertainty. As a result of a series of experiments, they clearly demonstrated that the answer to it often greatly depends on how we formulate a particular question.

So, during one of the experiments, Kahneman and Tversky divided the subjects into two groups. Both were given the same start to a hypothetical problem: the United States was preparing for an epidemic of an unknown Asian disease that was expected to kill six hundred people. Both groups were then given two options for further conditions and asked which one they would prefer. The first group was given the following options: if program A was adopted, the lives of two hundred people would be saved. If we accept program B, then it is one-third likely that all six hundred sick people will be saved and two-thirds likely that they will all die.

The options in the second group stated: if program B is adopted, four hundred patients will die. If Program D is adopted, it is one-third likely that no one will die, and two-thirds likely that everyone who gets sick will die.

Now take a short break and re-read both scenarios. (By the way, the participants in the experiment were not given such a chance.) The two solutions to the problem completely coincide. Programs A and B describe the same result: two hundred people will be saved, four hundred will die. The same applies to programs B and D: it is one third likely that everyone will be saved, two thirds - that no one will survive.

In theory, if a person prefers option A, he should also choose option B, since the consequences in both cases are exactly the same. However, it didn't turn out that way. In the options given to the first group, the solution was formulated in terms of the number of lives saved, so 72 percent of respondents preferred option A. But in the problem of the second group, the answer was formulated in terms of the number of deaths, and 78 percent chose option D. Other experiments yielded similar results in this area. During one of them, people were asked to choose one of two methods of treating cancer: radiation and surgery. Some were presented with information on survival rates, and respondents mostly chose surgery. Others received information in terms of mortality rates. A much higher percentage of respondents preferred irradiation. The results of the chosen option had very little effect on the medical education and experience of the experiment participants: they were almost the same in surveys of non-medical students, medical students and doctors. .

We prefer to choose for sure

Kahneman and Tversky's findings indicate that people appear to use a clear and consistent pattern of reasoning when making decisions. In situations where losses are expected, people tend to take more risks. For example, if, as in the above example, the emphasis is on mortality, a riskier alternative is preferable, offering at least some prospect of saving all the sick. But when assessing benefits, a person acts much more conservatively, so he chooses only what he is sure of. Most likely, this behavior is partly explained by how a person perceives risk.

“There are two different approaches to risk analysis: automatic, or intuitive, analysis, and more thoughtful, meaningful analysis,” says University of Oregon psychology professor Paul Slovic. “Our perception of risk comes mainly from feelings and emotions, so most of the time we function in system number one.”

As we have yet to see, this number one systematic approach determines many financial decisions. They can also explain the uncertainty in decision-making in other, less significant areas, say, in American football. This was clearly demonstrated by the results of an interesting study recently conducted by David Romer, a professor of political economy at the University of California at Berkeley. Romer explored the dilemma faced by a coach facing a fourth down (i.e., fourth down) situation: should he “take the risk” and get another four-down streak, or should he take the “safe” route and punt the ball?

The researcher conducted an analysis using a database of more than seven hundred National Football League games. Along the way, he made some adjustments to take into account the realities of American football. For example, to avoid particularly sensitive moments that often arise when one team is heavily ahead of the other or half a game is over, Romer focused exclusively on the first quarter of the matches he analyzed. The analysis showed that professional football coaches, despite their reputation as tough and decisive guys, generally tend to make very cautious decisions. In particular, according to Romer's calculations, situations in which teams really should take risks occur 40 percent of the time; but coaches choose risk much less often—only 13 percent of the time.

Agree, these numbers are interesting in themselves. But Professor Romer’s research is interesting not so much for the data obtained, but because we are talking about coaches of football teams. Unlike participants in most scientific experiments, trainers are not amateurs who make bets only with friends, without particularly risking anything. These highly paid professionals (the average annual salary of a professional football coach is three million dollars) are paid to make risky decisions. Even their workplace directly depends on this: the annual turnover rate among specialists in this profile reaches 20 percent. In addition, coaches have the invaluable opportunity to learn from their own mistakes. Fourth down situations occur multiple times during every game, and if a coach makes a poor strategic decision once and doesn't take advantage of that chance, he can do better the next time. In addition, each of them has full access to information about the decisions of other fellow trainers, which can also be used with considerable benefit for themselves.

However, Romer concluded that football coaches' decisions are characterized by systematic biases that ultimately harm their teams. Of course, to fully assess the damage, a comprehensive study is needed, since the professor's analysis was limited solely to the situation with fourth downs in the first quarter of the game, and not throughout the game. Romer estimates that if coaches picked fourth downs more often, it would result in one extra win (or more) every three seasons. This may not sound very impressive, but in the hyper-competitive world of professional football this is a very, very significant result.

And most importantly, Professor Romer’s findings pose the following question: since generously paid professionals, when making independent decisions on which their work and well-being largely depend, tend to make serious systematic errors, what then can we say about you and me, mere mortals? ? Do we really make decisions the same way?

Interpretation and money

To answer this question, let's try to analyze what happens when we have to make investment decisions. Like football coaches assessing the risks and rewards of a fourth down, most of us don't pull out calculators to calculate the risks of different alternatives using complex math. We, as Paul Slovic put it, rely on system one, which is trying to understand how risky certain investments seem to us. And the assessment usually depends on how we perceive them.

Consider a real-life example: On November 27, 1997, the journal Nature published a paper reporting positive results with endostatin, a new cancer drug developed by a small Rockville biotech company, EntreMed. On the same day, an article about this drug appeared in the New York Times; it was posted on page A28. Then that was the end of the matter. But almost six months later, on Sunday, May 3, 1998, the New York Times ran a front-page story with the catchy headline “Hope in the Lab: Special Report. We welcome with cautious reverence the drugs that destroyed cancerous tumors in mice.” The article described in superlatives the same EntreMed and its endostatin.

It is important to note that information about the drug has not changed at all over these six months. The second article about endostatin in Sunday's New York Times said nothing new. Only the “frame” has changed: the information has moved from page A28 to the front page of a respectable publication.

And the investors reacted to it, in essence, the same way as our friend the failed savior: they rushed up the stairs with a sword drawn, in order to then find themselves in a stupid situation, which they discovered a little later. The day after the Sunday Times story appeared, investors poured hundreds of millions of dollars into EntreMed stock. In the first two minutes of trading that morning, the price of the company's securities jumped as much as sixfold. By the end of the day, their value had increased even more, by a truly astonishing 330 percent. At the time, it was one of the biggest one-day gains recorded on the stock exchange since 1963. However, the euphoria did not last long. Other scientific laboratories were unable to obtain the same optimistic results when testing the drug that scientists reported in November 1997, and EntreMed's stock price plummeted. By October 2008, they were trading at just 34 cents a share, a significant drop from their peak of $85 a share the day after the Sunday Times front-page story.

How time affects our decisions

There are a number of factors that influence how we frame our decisions, and one of the least obvious but important ones is time. When the consequences of our decisions are distant in time, we tend to take big gambles. If consequences are expected soon, we tend to become more cautious and conservative. A good example is the beginning of human life, the process of giving birth to a child. Research has shown that women's wishes regarding anesthesia during childbirth vary significantly as the time horizon changes. While labor pains have not yet begun, many women in labor prefer not to have anesthesia. But during childbirth, most of them ask for anesthesia, which, frankly, is not at all surprising. And a month after the birth of a child, recent women in labor are again sharply opposed to anesthesia.

Scientists have determined that time constraints influence decision making in different ways. For example, after the terrorist attacks of September 11, 2001, the perception of life and time changed for many people in the United States. Americans, especially in large cities such as New York, began to live, as they say, one day at a time. Activities that provide long-term positive results, such as dieting or going to the gym, have fallen out of favor; people suddenly wanted to live cheerfully and carefree now, and not work for the future. What did this lead to? The well-known dietary nutrition center Jenny Craig reported that it had lost many of its clients.

The time factor even influences the choice of foods we eat, clothes we buy, movies we watch. In one experiment, two groups of people had to choose three movies in theaters, like those you can rent from Blockbuster or Netflix. The first group was asked to choose films to watch in the future, and the second - to watch right now. So what happened? The first group mostly chose intellectual films like the Oscar-winning “The Piano,” which explored the complex emotions of a mute woman living in the wildness of newly colonized Victorian-era New Zealand. The second group preferred simple and unpretentious films, such as the action thriller A Clear and Present Danger with Harrison Ford in the title role.

Researchers observed a similar effect by asking office workers to choose and order one of two snack options for the next week: fruit or unhealthy food like chips. The question was asked to two groups at two different points in time: at the end of the workday, when people were already hungry, and immediately after lunch, when everyone was full. And the state of hunger played a very significant role in their decision. About 78 percent of the "hungry" group chose unhealthy snacks; in the “well-fed” group, only 42 percent of the subjects preferred them. In other words, when office workers were hungry, that is, they wanted food immediately, they preferred tasty but unhealthy food. Just like the audience, who chose for immediate viewing not the masterpieces of world cinema. But when people felt full, they chose healthy foods. Likewise, video rental customers preferred highly intelligent films for viewing in the future.

Something similar happens when buying clothes. When it gets colder outside, the number of orders for warm clothes from the catalog soars, which is, in fact, quite expected. But the number of subsequent returns of goods is also increasing, which, you see, can no longer be called natural. What explains this? Because when there is a sharp cold snap, people often exaggerate the value of warm clothes and their need for them and then often return them. University of Michigan professor Mike Conlin advises thinking about buying clothes the same way you would buying groceries when you're particularly hungry.

Conlin and his colleagues analyzed sales statistics for nearly twelve million different products ordered over a five-year period from a large outdoor clothing company. The products analyzed included the customer's zip code, order date and return information. The scientists then compared sales information with weather forecast data for more than forty thousand zip codes across the United States. It turned out that a decrease in temperature on the day of order by ten degrees on average led to an increase in the subsequent number of returns of warm clothes by almost 4 percent. It must be said that different goods were returned in different ways. Expensive clothing such as jackets and coats tended to be returned to the retailer about twice as often as, say, relatively cheap hats and mittens. But overall, the number of returns increased by an average of about 4 percent. It seems like quite a bit. However, catalog sales in the United States are a huge business with annual sales of more than $125 billion, so even very small fluctuations in product return rates can have very negative financial consequences for companies.

The price of beauty

Many corporations are just now realizing how almost invisible, subtle factors like those described above influence the decisions of their clients. Not long ago, for example, one large bank from South Africa attracted Sendhil Mullainathan, a professor of economics at Harvard University, to cooperate. Like any credit institution in the world, the bank sought to increase its lending volume. But how to do this? Traditionally, interest rates on loans are reduced to stimulate demand for the service. But this bank acted differently.

Its leadership decided to experiment. The bank sent out a letter to more than fifty thousand of its borrowers that began with the words “Congratulations!” It went on to say that borrowers “become eligible” for a new cash loan. These were small, short-term cash loans like those offered in the US under mini-lending (or consumer lending). By American standards, the interest rates on the loans offered by the aforementioned bank were quite high - from 7.75 to 11.75 percent per month - but such rates are not uncommon in the South African market. And the amount of loans in dollar terms was small, about $150.

Each of the letters, sent out to groups of recipients according to a random selection, contained some tempting offers that could influence the choice of the subjects. Professor Mullainathan and his colleagues were able to evaluate the psychological impact of the proposals mentioned in the messages, regardless of strictly economic factors such as interest rates. For example, some clients were offered a low rate, while others were offered a high rate. The third were offered to play the lottery, they got a chance to win a mobile phone. But the most interesting element (at least for you and me) was located in the lower right corner of each letter - photographs of bank employees of different genders and races.

“The result simply stunned me,” admits Professor Mullainathan. “If there was a woman in the photo, the demand for credit among male customers increased to the same extent as if the interest rate was reduced by as much as five points!”

To the least cynical person, this fact is unlikely to surprise, especially after what we learned in previous chapters about the perception of attractive faces. But for banks, making such a discovery is like finding a goldmine. Even if we are talking about very small loans issued at a high interest rate, the chance to earn an additional five percent without the slightest risk is certainly a very rare and attractive opportunity.

Do the academic findings regarding the South African bank apply to financial institutions in other countries? According to one of the co-authors of the study described above, Marianne Bertrand, a professor at the Graduate School of Business at the University of Chicago, this question is difficult to answer, since the study was conducted exclusively on South African subjects. However, given the effectiveness of similar psychological methods of influence, observed in the United States, the professor considers it logical to conclude that the factors operating in one country are likely to work in another.

What you can learn from the grocery store

One of the methods of psychological influence, or manipulation, is called “anchoring.” A number of studies have revealed an interesting feature: when a person needs to make this or that decision, he ties it to a number - almost any number, often not having the slightest relation to the matter, especially if he sees or hears this number immediately before making a decision. Want to check it out? Ask your friends to write down the first three digits of their phone numbers, and then ask them to name the estimated date of Genghis Khan's death. Researchers conducted this experiment in truly countless variations - for example, after writing three digits of a telephone, subjects were asked to estimate the length of the Nile, the height of the arch in St. Louis, and other objects. And they invariably found a clear correlation between the two numbers. Thus, people almost always assumed that Genghis Khan lived in the first millennium AD (a three-digit number). However, it is not. Genghis Khan lived and died in the second millennium, therefore the date of his death is of four digits . The Encyclopedia Britannica gives three dates of birth of this Mongol warrior: 1155, 1162 or 1167. But the date of Genghis Khan’s death is known absolutely precisely - 1227. .

Of course, knowing this in advance, people could perhaps correct themselves. But just as we are not always aware of the influence of framing, or the framing effect, on our decisions (remember music and French wine?), we also rarely notice the anchoring effect. We often don't realize that information—say, grocery prices in stores—is presented to us in a way that influences our purchasing decisions. Meanwhile, we become victims of this effect every time we go to the store.

What Vicki McCracken remembers best from her childhood in Southern Indiana was going to the grocery store with her mom. “We were always short of money,” she says, “and my mother was constantly looking at the price tags.”

Years later, as a graduate student at Purdue University, McCracken remained interested in the issue of store prices. For example, if ordinary shoppers like her mother had the opportunity to look at a list of prices at different grocery stores in town before going shopping, would they go to another store? Would you change your shopping list? To find out the answer to these interesting questions, the US Department of Agriculture provided research funds to Wiki.

With the help of colleagues at Purdue University, McCracken conducted a simple but comprehensive test of grocery store prices in four different cities in four states across the country. In each city, the researchers hired a group of inspectors whose task was to walk around local stores with notepads in hand and write down the prices of a number of the most popular products among the population.

And McCracken and his colleagues published weekly prices for the consumer basket in local newspapers. And not only their total cost, but also the prices of individual products, for example, a can of Folgers coffee. The reaction to this information was not long in coming, but it was not at all what the researchers expected.

“The reaction came very quickly,” says Vicki McCracken. Several stores banned inspectors from crossing their thresholds. And one store owner even threatened to kill himself if McCracken did not stop publishing lists and comparing his prices with those of other outlets. “His prices, of course, were much higher than those of his competitors,” she notes.

McCracken didn't give up. It’s just that now its controllers did not walk around with notepads, which immediately gave them away, but simply came and purchased those products whose prices were of interest to the experimenters. (By the way, compassionate researchers stopped publishing information about prices in the store of a person who threatened to commit suicide.) This work continued for a whole year. Ultimately, the researchers found, as expected, that when price lists appeared in newspapers, many grocery stores lowered their prices, bringing them into relative line with competitors' prices.

However, this was not the most interesting thing. Controllers monitored prices not only for those goods about which information was later published, but also for those about which information was not published in the newspapers. For example, they fixed the prices of both a can of Folgers coffee (which was published) and Maxwell House coffee (which was not published in the newspapers). As a result, scientists have identified one of the shadowy aspects of food retailing. “While stores were lowering prices that were publicly known, they were also raising them on products that were not reported in the newspapers,” McCracken said. So, while the price of Folgers went down, Maxwell House coffee went up—presumably, according to the researcher, enough to offset the discount offered on a competing brand.

And of course, most buyers had no idea about this. That's the point! Grocery stores had every reason to expect that shoppers would flock in droves to advertised discounted prices, unaware that they would have to pay more for other items in the shopping basket.

Examples of the anchoring effect can be found in most grocery stores. For example, stores wanting to increase sales (and who doesn't?) often use a pricing approach known as multi-unit pricing. Remember how often we are offered four cans of canned peaches for two dollars, rather than 50 cents a can. From a logical point of view, the price of the product is exactly the same (as in the hypothetical problem of saving the lives of patients, invented by researchers Kahneman and Tversky), in contrast to the formulation. Accordingly, different offers have different effects on the consumer’s decision.

In the first example, the number four acts as an anchor. Without realizing it, customers choose four cans. Such manipulations are surprisingly effective. In one real-world study, researchers compared consumers' actual purchases at eighty-six different grocery stores and found that the multiunit pricing approach produced a 32 percent increase in sales compared to the per-unit pricing approach. one unit of goods (“one can for 50 cents”).

Another way stores use the anchor effect is to force us to buy more goods than we need: they impose quantity limits, say, “twelve units per person.” The number 12 acts as an anchor. Having analyzed the effectiveness of this technique for increasing sales volumes, scientists came to the conclusion that it is also very effective. The larger the anchor, the higher the sales rate. The trick only fails when the anchor is absurdly large, say 50 units.

The main clue when “anchoring” is the first number. According to scientists, people process information in the order in which it is presented to them. And the most important place in this sequence is, of course, the first. For example, if a party's candidate comes first on the ballot in a primary, he can safely add almost three percentage points to his results. By the way, the opportunity to be the first to put forward a proposal during negotiations provides the same significant advantage. This is explained by the fact that the first sentence becomes an anchor in the subsequent discussion. This effect was experimentally discovered in 2001 by researchers from Utah, as well as from Germany. According to their observations, whichever party to the negotiations, buyer or seller, who puts forward an offer first, achieves better results in them.

How does the price of real estate in the catalog influence the purchasing decision?

The same applies to the most important and responsible negotiations that most ordinary people will have to conduct in their entire lives - negotiations about buying a house. Real estate, as a rule, is not sold in packages (“four houses for two million dollars”), and its sellers rarely, or rather never, set restrictions on purchases (“twelve houses per client”). However, the price we ultimately pay is often tied to the number we see first, which is the listing price of the property.

The power of listing prices was clearly demonstrated by a real-life experiment in which the decisions of ordinary students were compared with those of experienced real estate agents. Members of both groups were asked to rate specific homes for sale in Tucson. To help, each study participant was given a ten-page packet containing information that any buyer would likely consider. It included recent home prices in the area, listing prices of homes for inspection, and information from the standard MLS Multiple Listing Service, a real estate listing tool used in the United States, Canada, and the United Kingdom. Note lane . And so on for each property put up for sale.

And the shopping began. Participants had the opportunity to examine the house from all sides and walk around the neighborhood, just as you and I would do when looking for a new home. The experts and amateurs were then given calculators and asked to roughly estimate the houses. They were also asked to create a checklist and describe how they arrived at their conclusions.

The study revealed a number of very interesting facts, which, however, are unlikely to reassure you, especially if you are going to buy or sell real estate. Firstly, the estimates of amateurs and experts were not so different. For example, when asked about the declared value of real estate, the spread in both groups was only a few thousand, and sometimes several hundred dollars. Secondly, the assessments of both groups of participants were significantly influenced by the price of the house indicated in the catalogue. Despite all the other information available to them, both groups stubbornly tied their estimates to the same figure—the list price. The higher it was, the higher their own assumptions about how much the house should be put on the market for. This may partly explain why catalog prices (at least for buyers) are so often unrealistically high. Thus, this price, in fact, represents the starting offer in the negotiations; the entire upcoming bargaining will be “anchored” from this point. And as we have already said, the one who puts forward the first proposal, as a rule, achieves the best result.

And finally, the third and, in a sense, the most important conclusion: even the most experienced specialists in the field of real estate trade fall for this bait. Like the doctors who charge drug companies to write prescriptions for their drugs, real estate agents were completely unaware that list prices influenced their subsequent decisions. They believed that their professional judgment regarding the value of a house was not at all dependent on an arbitrarily chosen price in the catalog, although in reality everything was different. In a survey conducted at the very end of the experiment, real estate agents “categorically denied that they had taken catalog prices into account.” However, after analyzing the checklists of these professionals, the researchers found the opposite . According to the researchers, the question of whether the real estate agents really did not know that they were using the list price as a guide, or were simply unwilling to “publicly acknowledge the dependence of their judgments on, admittedly , absolutely unreliable information” remains open. A similar finding regarding the reluctance of other professionals—political scientists—to admit their mistakes is described in Tetlock (1998). .

As the above examples show, resisting psychological methods of influence is not at all easy. These very powerful tools work in a variety of settings and locations, from grocery stores to voting booths. I'll give you some tips to help you avoid falling into their trap.

First, try using such an effective tool as reframing. For example, if you are buying a house, try to negotiate not on the price ($250,000) but on the price per square meter (say, “I agree to pay $500 per square meter”).

Secondly, try to act first. Of course, this is not always possible. But if, for example, you're behind on your mortgage (or about to be), you'll get a lot out of it by contacting the lender first and making an offer. This will put you in a winning position and your proposal will become the anchor around which the negotiations will revolve.

Third, be wary of sales. They are often used as an “anchoring” mechanism to draw your attention to the price the seller wants you to focus on. But according to a recent study, the inflated prices of many other non-discounted items are likely to completely wipe out your savings from purchasing the discounted product. Want to check it out? Just save your receipts from several trips to the store and compare them. Better yet, visit specialized sites that track prices for thousands of food products, both advertised and not advertised by sellers.

Joseph Hallinan. "Why We Get Wrong: Thinking Traps in Action"