Serial Bottlenecks in Human Information Processing PDF

serial bottlenecks: Psychologists have proposed that there are serial bottlenecks in human information processing, points at which it is no longer possible to continue processing everything in parallel. Example: Although most of us can perform separate actions simultaneously when the actions involve different motor systems (such as walking and chewing gum), we have difficulty in getting one motor system to do two things at once. where the bottlenecks in information processing lie? Various theories about when they happen are referred to as early- selection theories or late-selection theories, depending on where they propose that bottlenecks take place. Wherever there is a bottleneck, our cognitive processes must select which pieces of information to attend to and which to ignore. Attention: attention is concerned with where these bottlenecks occur and how information is selected at these bottlenecks. Example: imagine ourselves at a Museum, looking at a painting. First, our eyes will catch the large, salient objects. This is an instance of stimulus-driven attention. Second step is that we have a goal and will direct our attention over the picture to find the object being described. Now imagine that we hear an alarm system starting to ring. A stimulus-driven factor has intervened, and our attention will be drawn away from the picture and switch to the adjacent room. Goal-directed attention versus stimulus-driven attention Neural imaging evidence suggests that the goal-directed attentional system is more left lateralized, whereas the stimulus-driven system is more right lateralized. The prefrontal regions of the brain (dorsolateral prefrontal cortex, anterior cingulate) are particularly important in executive control. MEMORY FOR MEANINGFUL INTERPRETATIONS OF EVENTS: If you show the Participants different pictures and ask them about their differences, they are more sensitive to meaning-significant changes in a picture and not for details in the picture. This is not because they are incapable of remembering such detail, but rather because this detail does not seem important and so is not attended. When people see a picture, they attend to and remember best those aspects that they consider meaningful. Multimodal Hypothesis vs. Amodal Hypothesis: Multimodal hypothesis: we have various representations tied to different perceptual and motor systems and that we have means of directly converting one representation to another. Example: the double-headed arrow going from the visual to the motor would be a system for converting a visual representation into a motor representation and a system for converting the representations in the opposite direction. Amodal Hypothesis: According to this hypothesis, we have systems for converting any type of perceptual or motor representation into an abstract representation and for converting any abstract representation into any type of perceptual or motor representation. So, to convert a representation of a picture into a representation of an action, one first converts the visual representation into an abstract representation of its significance and then converts that representation into a motor representation. About the previous example (differences of the photos), we can say that the amodal hypothesis holds that this information is retained in the central meaning system. The multimodal hypothesis holds that the person has converted the information from the modality of the presentation to some other modality. Categorization: Categorization simplifies perception and cognition related to the social world by detecting inherent similarity relationships or by imposing structure on it (or both). Research on categorization has focused both on how we form the categories in the first place and on how we use them to interpret experiences. It has also been concerned with notations for representing this categorical knowledge. For instance, if you tell someone, "I was licked by a dog;' your listener can predict the number of legs on the creature, its approximate size, and so on. The effects of such categorical perceptions are not always positive-for instance, they can lead to stereotyping. Semantic Networks: people store information about various categories such as canaries, robins, fish, and so on-in a network structure. we represent a hierarchy of categorical facts, such as that a canary is a bird and a bird is an animal, by linking nodes for the two categories with isa links. If our categorical knowledge were structured like Figure 5.10, we would expect sentences in level 1 to be verified more quickly than sentence in level 2, which would be verified more quickly than sentence 3. (Because we need to check the lower level of the information) The following statements about the organization of facts in semantic memory and their retrieval times seem to be valid conclusions from the research: I. If a fact about a concept is encountered frequently, it will be stored with that concept even if it could be inferred from a higher order concept. 2. The more frequently a fact about a concept is encountered, the more strongly that fact will be associated with the concept. The more strongly facts are associated with concepts, the more rapidly they are verified. 3. Inferring facts that are not directly stored with a concept takes a relatively long time. Schemas: Semantic networks, which just store properties with concepts, cannot capture the nature of our general knowledge about a house, such as its typical size or shape. Schemas represent categorical knowledge according to a slot structure, in which slots are attributes that members of a category possess, and each slot is filled with one or more values, or specific instances, of that attribute. Example: House Isa: building Parts: rooms Materials: wood, brick, stone In this representation, such terms as materials and shape are the attributes or slots, and such terms as wood, brick, and rectilinear are the values. Each pair of a slot and a value specifies a typical feature. Values like those listed above are called default values because they do not exclude other possibilities. For instance, the fact that houses are usually built of materials such as wood, brick, and stone does not mean that something built of cardboard could not be a house. If we know something is a house, we can use the schema to infer that it is probably made of wood, brick, or stone and that it has walls, windows, and ceilings. Schemas have another type of structure, called a part hierarchy. (Like the photo in the previous page) Psychological Reality of Schemas: Here we had an example that was about an experiment room, and 30 participants that were asked to recall the items in the room, after being 35 seconds in the room. 29 of the 30 participants recalled that the office had a chair, a desk, and walls. Their recall was strongly influenced by their schema of what an office contains. Only 8 participants, however, recalled that it had a bulletin board or a skull. On the other hand, 9 participants recalled that it had books, which it did not. (They falsely recalled items that are default values of the schema but were not in this office.) we see that a person's memory for the properties of a location is strongly influenced by that person's default assumptions about what is typically found in the location. A schema is a way of encoding those default assumptions. Degree of Category Membership: One of the important features of schemas is that they allow variation in the objects associated with a schema. Example: apples are seen as fruits more rapidly than are watermelons, and robins are seen as birds more rapidly than are chickens. Failing to have a default or typical value does not disqualify an object from being a member of the category, but people's judgments about nontypical objects tend to vary a great deal. although participants did agree on some items, they disagreed on many. For instance, whereas all 30 participants agreed that cancer was a disease and happiness was not, 16 thought stroke was a disease and 14 did not. In the following photo, it was asked from the participant of an experiment to give a rate(response to a fex photos of dishes and asked which one is a cup? Their answers depend on the depth of the cups. Results from this experiment demonstrating that the cup category does not appear to have clearcut boundaries. The percentage of participants who used the term cup versus the term bowl to describe the objects shown in the above figure is plotted as a function of the ratio of width to depth. The solid lines reflect the neutral context condition, the dashed lines the food-context condition. The Psychophysical Law Recently invented procedures have shown that whenever the stimulus increases, the intensity of the sensation grows in accordance with a common basic principle. Two conflicting laws The issue concerns the form of the psychophysical law, the equation that tells how the strength of the external stimulus determines your impression of subjective intensity. The two contending laws are known as the logarithmic law and the power law. The two conflicting laws made their first appearance in connection with a friendly game of chance. More than two centuries ago a paradox in a gambling game led to one of the first conjectures about the law that governs the subjective value of stimuli. If we regard money as a stimulus· and the subjective value attached to its ownership as a response, then the problem becomes a stimulus response relation. Two laws of utility Gabriel Cramer puzzled said, that the subjective value of money, what economists now call utility, grows less rapidly than the numerical amount of money, the number of pennies or dollars. We know about Cramer's conjecture only because Daniel Bernoulli, mentioned the idea in a footnote attached to his famous paper of 1738 in which he proposed his own solution to the paradox. Bernoulli's hypothesis, which he reached quite independently, resembled Cramer's in one important respect. Both men concluded that the subjective value of each penny becomes less as the number of pennies increases. In the jargon of the economist, money exhibits a decreasing marginal utility. But Bernoulli chose a logarithmic function to represent the decreasing marginal utility, whereas Cramer had chosen a power function with an ex- ponent of one-half, which is the square root. In Fig. 1 we see a graph of the power function that Cramer used to explain the growth of utility (ordinate) as a function of gains in wealth (abscissa). Both curves are similar in one important respect. They are both concave downward in a manner consistent with the principle that has appeared so obvious to nearly everyone, namely, that the value of one added dollar seems less when you have a thousand than when you have only two or three. Nevertheless, there are important differences between the two functions, even though both are concave downward. The exponent is 0.5, which means that the function expresses a simple square-root function. In other words, the subjective value grows as the square root of the number of dollars, so that it takes a fourfold inCrease in dollars to double the subjective value. It was supposed to express the relation between subjective value in utiles and number of dollars. Bernoulli derived his logarithmic function by first making a simple assumption. The added utility, he said, grows smaller as the number of dollars grows larger-a simple inverse relation. Cramer's power function derives from an assumption that is just as simple and perhaps even more plausible. This alternative assumption states that the added utility grows smaller as the total utility grows larger. Again a simple inverse relation, but this time it is between the added utility and the total utility, not between the added utility and the total number of dollars. Fechner's jnd scale Fechner proposed to measure sensation by way of indirect experiments a kind of assault from the rear. Instead of asking a person to make a direct estimation of the relative magnitudes of his sensations, Fechner conducted scores of discrimination tests in which he measured the JND. (just noticeable difference ) Fechner's law is a logarithmic function. When the stimulus increases geometrically (for example, by doubling at each step), the sensation, according to Fechner, increases arithmetically (in steps of constant size). Metathetic versus prothetic The prototypes of the two kinds of perceptual continua are exemplified by loudness and pitch. Loudness is an aspect of sound that has what can best be described as degrees of magnitude or quantity. Pitch does not. Pitch varies from high to low;· it has a kind of position, 3nd in a sense it is a qualitative continuum. Loudness may be called a prothetic continuum, and pitch a metathetic one. The criteria that define those two classes of continua reside wholly in how they behave in psychophysical experiments, but the names themselves were suggested to me by the nature of the physiological processes that appear to underlie some of the sensory continua. The psychophysical power law Equal stimulus ratios produce equal subjective ratios. The general rule is this: on all continua governed by the power law, a constant percentage change in the stimulus produces a constant percentage change in the sensed effect. Why a power function? Chapter 33 – p.360 - Joint evaluation o Here one considers two scenarios at the same time and make a comparison o Also possible to apply a rule or a norm o No surprise and little ambiguity when comparing o Influenced by System 2 § à Comparison that occurs in joint evaluation involves more careful and effortful assessment - Separate evaluation o Here one only considers one scenario o More focused on emotions o Surprise and high ambiguity because no comparison o Influenced by System 1 § à emotional reactions are likely to determine single evaluation o à Judgments made in single and in joint evaluation are not consistent - Example: o You offered a choice between two bets, which are to be played on a roulette wheel with 36 sectors § Bet A: 11/36 to win $160 and 25/36 to lose $15 § Bet B: 35/36 to win $40 and 1/36 to lose $10 o You are asked to choose between safe bet and riskier one à high chance to win and small chance to win à B is the popular choice (in joint evaluation) o Now you are exposed to each bet separately (separate evaluation) à what is the lowest price at which you would sell it? à selling price for A is higher than for B à preference reversal (mainly seen in within subject experiment) - Judgment within categories: o Judgment and preferences are coherent within categories o And incoherent when objects which are evaluated belong to different categories - Summary à o Joint evaluation favors System 2 § à comparative judgement involves System 2 and is more stable than separate evaluation o Separate evaluation favors System 1 § à Separate evaluation reflects intensity of emotional response Chapter 7 Kahnemann - How does System 1 work? o Basically, jumping to conclusions § à but only efficient if: conclusions are likely to be correct and the costs of a mistake are acceptable jump saves much time and effort § à risky if: Situation is unfamiliar The stakes are high There is no much time to collect more information o Errors of System 1 can be prevented by System 2 o System 1 is influence by experience à influences how we interpret things § Recent experiences leads to memories which influence way of interpreting things à easer in general § Experience which are more far away create distant memories which makes it harder to interpret things o System 1 has not acceptance for doubt or questioning, things are just accepted à less mental effort o System 1 makes it easier to believe things (automatic operation which involves the construction of the best possible interpretation of a situation) o Biased to believe everything o Affected by confirmation bias § à uncritical accepting of suggestions and exaggeration of the likelihood of extreme and improbable events § à how often you have seen tsunamis in the past will influence your perception about future tsunamis o Halo Effect is also part of System 1 § The tendency to like or dislike everything about a person including things you have not observed o If there is no memory about a certain situation System 1 excels at constructing the best possible story that incorporates ideas currently activated, but it does not or cannot allow for information it does not have § à The measure of success for system 1 is the coherence of the story it manages to create § à when information is scarce System 1 operates as machine to jump to conclusions o System 1 is insensitive to quality and quantity of the information that gives rise to impressions and intuitions - How does System 2 work? o Has the characteristic of uncertainty and doubt o More mental effort o Sometimes busy and lazy à harder to activate o Tests hypotheses by searching for confirming evidence which is known as positive test strategy o - à The combination of coherences seeking System 1 with a lazy System 2 implies that System 2 will endorse many intuitive beliefs which reflect that System 2 will endorse many beliefs which are reflect the impressions generated by System 1 - Bias of Judgement and Choice: o Overconfidence § Neither the quantity nor the quality of the evidence counts for much in subjective confidence § The confidence that individuals have in their belief depends on the story they can tell about what they see § People often fail to allow for the possibility that evidence should be critical to our judgement is missing à what we see is all there is § People’s associative system tend to settle on coherent pattern of activation and suppresses doubt and ambiguity o Framing effects § Different ways of presenting the same information often evoke different emotions Example: o 90% fat free is seen as better than 10% fat o Base-rate neglect § People who are meek and tidy are more believed to be a librarian § Description is salient and vivid even though everyone knows there are more male farmers than librarians § This is a statistical fact which doesn’t come to your mind as a first thought Hsee Less is better - Normative decision theories = o assume that people have consistent and well-defined preferences regardless of how the preferences are elicited. - Behavioral decision research = o preferences are constructed ad hoc and can be easily influenced by contextual manipulations as framing of problem in terms of gain or a loss - ànormatively less valuable option is judged more favorably than its more valuable alternative = less-is-better theorem o risky option (e.g. 5% chance to win $96 or $0) can be valued more highly than superior risky option (e.g. a 5% chance to win $96 or $24). à evaluation according to which, the weight assigned to a given outcome in risky prospect depends both on rank and size - Example: o Silver medalists thought that they had almost won gold medal and were therefore disappointed with being the second, while the bronze medalists thought that they had almost not won anything, so felt lucky with what they had achieved. - Study 1 o used questionnaire with two between-subject versions o both versions participants were asked to imagine that they were about to study abroad and had received good-bye gift from friend o Version 1: § wool coat, from nearby department store § store carries variety of wool coats § worst coat costs $50 and the best costs $500 § The one your friend bought you costs $55 o Version 2: § wool scarf, from nearby department store § store carries variety of wool scarves § worst costs $5 and the best costs $50 § The one your friend bought you costs $45 - à In both conditions participants were asked how generous they thought the friend was. Answers the $55 coat is certainly more expensive than the $45 scarf, those receiving the scarf considered their gift giver to be more generous than those receiving the coat o judgment of a gift giver's generosity should depend on the cost of the gift, not on its usefulness = the cost of a gift is the only relevant value of concern for generosity - à gift givers want their gift recipients to perceive them as generous, it is better for them to give a high-value item from a low-value product category (e.g. a $45 scarf) rather than low- value item from high-value product category (e.g. a $55 coat). - Hard vs. easy evaluation: o The person judges an option in isolation, the judgment is influenced more by attributes that are easy to evaluate than by attributes that are hard to evaluate, even if the hard-to-evaluate attributes are more important. An attribute is said to be hard to evaluate if the decision maker is not aware of its distribution information and consequently does not know whether a given value on the attribute is good or bad. An attribute is said to be easy to evaluate if the decision maker knows its distribution information and thereby knows whether a given value on the attribute is good or bad. o à when people evaluate an object in isolation, they often think about other objects in same category, and compare the stimulus object to the other objects. § the first “the real value of the gift” is hard to evaluate. Without something to compare it to, people would not have an idea whether a $55 (or a $45) gift is good or bad § the second “product category” is a reference, and is not directly evaluated. § the last “relative position of the given gift in its category” is easy to evaluate. Participants had some distribution information (i.e. price range in this case) of this attribute. Compared with other wool coats ranging in price from $50 to $500, a $55 coat is quite inexpensive. Compared with other wool scarves ranging from $5 to $50, $45 scarf is quite expensive. The evaluability hypothesis predicts that one's evaluation of the gift would be influenced by the “relative position” attribute and not by the actual value. The result is consistent with prediction. In evaluating a gift, people are neither sensitive to the actual price of the gift, nor to the category of that gift (e.g. whether a coat or a scarf), but they are very sensitive to the relative position of the gift within its category. - Separate and joint evaluation: o Separate: § people cannot compare one option against another, and can only compare the given option to whatever reference is available at the time of the evaluation. o Joint: § In joint evaluation, the two options are juxtaposed, and each option becomes the most salient and convenient reference for evaluating the other option. In this case, people will give less weight to or ignore the reference information they would otherwise use in separate evaluation, and use the alternative option as their primary reference o Results for Study 2 as experiments for separate and joint evaluation: § clear less-is-better effect in separate evaluation, and a clear preference reversal between joint and separate evaluations § In the separate evaluation versions, Vendor L's serving was valued more than for Vendor H's, even though Vendor L's serving contained less ice-cream § In joint evaluation, the effect was reversed: Vendor H's serving was valued more § - Dishes Set experiment (see lecture for explanation): § Willingness to pay prices: low-value option was valued more favorably than the high-value alternative in separate evaluation: values were higher for Set L than for Set H although Set L included fewer intact pieces than Set H In joint evaluation, the effect was reversed: WTP values were higher for Set H - General discussion: o This research compares valuations of options between separate evaluation and joint evaluation where one of the options is always more valuable or better than the other. o It demonstrates that preferences were reversed between these two evaluation modes, and, more interestingly, that the low-value option was valued more highly than the high-value alternative in separate evaluation. o There is a higher valuation of the low-value option in separate evaluation heavily on whatever comparison information is available at the time of the evaluation. o people use different information as their reference points in the joint evaluation mode than in the separate evaluation mode. o Even in separate evaluation, the reference point associated with one option often differs from that associated with the other option. o If the reference associated with the high-value option is better than the high-value option itself, and/or if the reference associated with the low-value option is worse than the low-value option itself, the less-is-better effect may emerge. o the less-is-better effect will be less likely to occur if the value of concern itself is easy to evaluate. § For example, for people in the ice cream business, the actual amount of ice cream in a serving may be easy to evaluate. They know how much a serving with a given amount of ice cream is worth, without having to compare it § Second, the less-is-better effect occurs not only because the “relation-to- reference” attribute is easy to evaluate, but also because the stimulus options have different relations with their respective references one is better than the reference and the other is worse than the reference, or one is better (or worse) than the reference and the other is equal to the reference. § If the stimulus options have similar relations with their respective references for example, both better than their references, then the less-is-better effect will be less likely to occur. For instance, in the ice cream case, if both servings were overfilled, there would probably not be a less-is-better effect in separate evaluation, and not be a preference reversal between joint and separate evaluations, either. o Which is the more valid method? § The first (separate evaluation) method is apparently imperfect, because, as we now know, the option favored in separate evaluation may well be different from the option that is objectively more valuable or better. § Then, is the second (joint evaluation) method more valid? Not necessarily, either. The answer depends on what it means by “more valid”. § If the criterion of validity is for the evaluations to be consistent with the objective quality of the stimulus options, then joint evaluation is indeed more valid than separate evaluation, because in joint evaluation people are more likely to discover subtle differences between the stimulus options which may be masked in separate evaluation, and more likely to know which option is objectively more valuable o In short, preferences elicited in joint evaluation may differ from preferences elicited in separate evaluation. Preferences elicited in joint evaluation are often more consistent with the objective quality of the evaluated options, but preferences elicited in separate evaluation are often more predictive of consumers' ultimate experience. Making decisions – Prospect theory: Value function Kahneman Ch. 26 The value function in prospect theory reflects three important properties that distinguish it from the traditional utility function. 1) value is measured in terms of changes in wealth from a reference point whereas a utility function measures value based on the level of wealth. 2) The value function is convex for losses reflecting risk-taking and concave for gains reflecting risk aversion whereas an individual's utility function evaluates risk aversion, risk neutrality, or risk loving. 3) The value function is steeper for losses than for gains due to loss aversion. The surprising outcome when comparing these two problems: Problem 1) Get $900 for sure OR a 90% chance to get $1’000 Problem 2) Lose $900 for sure OR 90% chance to lose $1’000 1) Most people chose in problem 1 the risk-averse option (Get $900 in this case) no surprise here. 2) Most people chose to gamble in this question -> risk seeking Explanation: The explanation of the risk-seeking choice is the mirror image of the explanation of the risk aversion in problem 1. The negative value of losing $900 is much more than 90% of the negative value of losing $1’000. This is clearer in problems 3 and 4: Problem 3) In addition to whatever you own, you get $1’000 Now you have these options to choose from: 50% chance to win $1’000 OR get $500 for sure Problem 4) In addition to whatever you own, you get $2000 Now you have these options to choose from: 50% chance to lose $1’000 OR lose $500 for sure The final states of wealth (which is all that matters for the Bernoulli theory) are identical for both. Either be richer by $1500 with 100% chance or gamble with equal chances (50%) to be richer by $1000 or by $2000. We expect to see similar preferences therefore according to Bernoulli’s theory Results: 3) A large majority preferred the sure thing 4) A large majority preferred the gamble This is a decisive counterexample of the key idea from Bernoulli’s theory It shows the importance of the reference point that is missing in the Utility function. The reference point is $1000 higher than the current wealth in problem 3 and $2000 higher in problem 4. Being richer by $1500 is a gain of $500 in problem 3 and a loss of $500 in problem 4. For financial outcomes, the usual reference point is the status quo, but it can also be the outcome that we expect. Outcomes that are better than the reference points are seen as gains. Below the reference points, they’re losses. Reference Dependence: Decisionmakers assess the psychological value of outcomes relative to a neutral reference point Loss aversion: When directly compared losses loom larger than gains. A loss of $100 is felt worse than a gain of $100. The absolute psychological value of a loss is greater than that of a gain of equal objective value Diminishing sensitivity: Subjective difference between $900 and $1000 is much smaller than the difference between $100 and $200. The psychological value increases with diminishing sensitivity with increasing deviations from the reference point Losses are subjectively felt worse than gains Asian disease problem: A2 = Program A in condition B B2= Program B in condition B Programs A and A2 are identical, as are programs B and B2. The change in the decision frame between the two groups of participants produced a preference reversal: when the programs were presented in terms of lives saved, the participants preferred the secure program, A. When the programs were presented in terms of expected deaths, participants chose gamble B2. People generally prefer the absolute certainty inherent in a positive framing effect, which offers an assurance of gains. When decision options appear framed as a likely gain, risk-averse choices predominate. A shift toward risk-seeking behavior occurs when a decision-maker frames decisions in negative terms or adopts a negative framing effect. In essence: In mixed gambles, where both a gain and a loss are possible, loss aversion causes extremely risk-averse choices. In bad choices, where a sure loss is compared to a larger loss that is merely probable, diminishing sensitivity causes risk-seeking. Blind spots of prospect theory: A. one chance in a million to win $1 million B. 90% chance to win $12 and 10% chance to win nothing C. 90% chance to win $1 million and 10% chance to win nothing Winning nothing is a possible outcome in all three gambles, and prospect theory assigns the same value to that outcome in the three cases. Winning nothing is the reference point and its value is zero. Winning nothing is a nonevent in the first two cases and assigning it a value of zero makes good sense. In contrast, failing to win in the third scenario is intensely disappointing. Like a salary increase that has been promised informally, the high probability of winning the large sum sets up a tentative new reference point. Relative to your expectations, winning nothing will be experienced as a large loss. Prospect theory cannot cope with this fact because it does not allow the value of an outcome (in this case, winning nothing) to change when it is highly unlikely, or when the alternative is very valuable. In simple words, prospect theory cannot deal with disappointment. Disappointment and the anticipation of disappointment are real, however, and the failure to acknowledge them is as obvious a flaw as the counterexamples that I invoked to criticize Bernoulli’s theory. Prospect theory and utility theory also fail to allow for regret. The two theories share the assumption that available options in a choice are evaluated separately and independently, and that the option with the highest value is selected. This assumption is certainly wrong, as the following example shows: Problem 6: Choose between 90% chance to win $1 million OR $50 with certainty. Problem 7: Choose between 90% chance to win $1 million OR $150,000 with certainty Compare the anticipated pain of choosing the gamble and not winning in the two cases. Failing to win is a disappointment in both, but the potential pain is compounded in problem 7 by knowing that if you choose the gamble and lose you will regret the “greedy” decision you made by spurning a sure gift of $150,000. In regret, the experience of an outcome depends on an option you could have adopted but did not S 12. Prospect Theory: Decision weights; Types of utility Kahneman Ch. 30 Rare Events Kahneman visited Israel several times during a period in which suicide bombings in buses were relatively common, though quite rare in absolute terms. For any traveller, the risks were tiny, but that was not how the public felt about it. People avoided buses as much as they could. Kahneman did not have much occasion to travel on buses, as he was driving a rented car, but he was chagrined to discover that his behavior was also affected. He found that he did not like to stop next to a bus at a red light, and he drove away more quickly than usual when the light changed. He knew that the risk was truly negligible, and that any effect at all on his actions would assign an inordinately high “decision weight” to a minuscule probability. In fact, he was more likely to be injured in a driving accident than by stopping near a bus. He was avoiding buses because he wanted to think of something else. This experience illustrates how terrorism works and why it is so effective: it induces an availability cascade. An extremely vivid image of death and damage, constantly reinforced by media attention and frequent conversations, becomes highly accessible, especially if it is associated with a specific situation such as the sight of a bus. ➔ System 2 may “know” that the probability is low, but this knowledge does not eliminate the self-generated discomfort and the wish to avoid it. ➔ System 1 cannot be turned off. Overweighting of unlikely outcomes is rooted in System 1. Overestimation and Overweighting 1. What is your judgment of the probability that the next president of the United States will be a third-party candidate? 2. How much will you pay for a bet in which you receive $1,000 if the next president of the United States is a third-party candidate, and no money otherwise? The two questions are different but obviously related. The first asks you to assess the probability of an unlikely event. The second invites you to put a decision weight on the same event, by placing a bet on it. How do people make the judgments and how do they assign decision weights? ➔ People overestimate the probabilities of unlikely events. ➔ People overweight unlikely events in their decisions. In overestimation and overweighting the same psychological mechanisms are involved: Focused attention, confirmation bias, and cognitive ease. Specific descriptions trigger the associative machinery of System 1. When you thought about the unlikely victory of a third-party candidate, your associative system worked in its usual confirmatory mode, selectively retrieving evidence, instances, and images that would make the statement true. You looked for a plausible scenario that conforms to the constraints of reality. Your judgment of probability was ultimately determined by the cognitive ease, or fluency, with which a plausible scenario came to mind. You do not always focus on the event you are asked to estimate. If the target event is very likely, you focus on its alternative. Example: What is the probability that a baby born in your local hospital will be released within three days? You were asked to estimate the probability of the baby going home, but you almost certainly focused on the events that might cause a baby not to be released within the normal period. You quickly realized that it is normal for babies in the United States to be released within two or three days of birth, so your attention turned to the abnormal alternative. The unlikely event became focal. The availability heuristic is likely to be evoked: your judgment was probably determined by the number of scenarios of medical problems you produced and by the ease with which they came to mind. Because you were in confirmatory mode, there is a good chance that your estimate of the frequency of problems was too high. The probability of a rare event is most likely to be overestimated when the alternative is not fully specified. Planning fallacy and other manifestations of optimism: The successful execution of a plan is specific and easy to imagine when one tries to forecast the outcome of a project. In contrast, the alternative of failure is diffuse, because there are innumerable ways for things to go wrong. Entrepreneurs and the investors who evaluate their prospects are prone both to overestimate their chances and to overweight their estimates. Vivid Outcomes In utility theory, decision weights and probabilities are the same. The decision weight of a sure thing is 100, and the weight that corresponds to a 90% chance is exactly 90, which is 9 times more than the decision weight for a 10% chance. In prospect theory, variations of probability have less effect on decision weights. An experiment found that the decision weight for a 90% chance was 71.2 and the decision weight for a 10% chance was 18.6. Psychologists at the University of Chicago published an article with the attractive title “Money, Kisses, and Electric Shocks: On the Affective Psychology of Risk.” Their finding was that the valuation of gambles was much less sensitive to probability when the fictitious outcomes were emotional (“meeting and kissing your favorite movie star” or “getting a painful, but not dangerous, electric shock”) than when the outcomes were gains or losses of cash. ➔ Rich and vivid representation of the outcome, whether or not it is emotional, reduces the role of probability in the evaluation of an uncertain prospect; adding irrelevant but vivid details to a monetary outcome also disrupts calculation. Example: 21% (or 84%) chance to receive $59 next Monday 21% (or 84%) chance to receive a large blue cardboard envelope containing $59 next Monday There will be less sensitivity to probability in the second case, because the blue envelope evokes a richer and more fluent representation than the abstract notion of a sum of money. You constructed the event in your mind, and the vivid image of the outcome exists there even if you know that its probability is low. Cognitive ease contributes to the certainty effect as well: when you hold a vivid image of an event, the possibility of its not occurring is also represented vividly, and overweighted. The combination of an enhanced possibility effect with an enhanced certainty effect leaves little room for decision weights to change between chances of 21% and 84%. Vivid Probabilities Urn A contains 10 marbles, of which 1 is red. Urn B contains 100 marbles, of which 8 are red. Which urn would you choose? The chances of winning are 10% in urn A and 8% in urn B, so making the right choice should be easy, but it is not: about 30%–40% of students choose the urn with the larger number of winning marbles, rather than the urn that provides a better chance of winning → Illustrates the superficial processing characteristic of System 1 The bias has been given several names; following Paul Slovic, Kahneman calls it denominator neglect. If your attention is drawn to the winning marbles, you do not assess the number of nonwinning marbles with the same care. Vivid imagery contributes to denominator neglect. The distinctive vividness of the winning marbles increases the decision weight of that event, enhancing the possibility effect. Of course, the same will be true of the certainty effect. If I have a 90% chance of winning a prize, the event of not winning will be more salient if 10 of 100 marbles are “losers” than if 1 of 10 marbles yields the same outcome. The idea of denominator neglect helps explain why different ways of communicating risks vary so much in their effects. You read that “a vaccine that protects children from a fatal disease carries a 0.001% risk of permanent disability.” The risk appears small. Now consider another description of the same risk: “One of 100,000 vaccinated children will be permanently disabled.” The second statement does something to your mind that the first does not: it calls up the image of an individual child who is permanently disabled by a vaccine; the 999,999 safely vaccinated children have faded into the background. ➔ As predicted by denominator neglect, low probability events are much more heavily weighted when described in terms of relative frequencies (how many) than when stated in more abstract terms of “chances,” “risk,” or “probability” (how likely). System 1 is much better at dealing with individuals than categories. The power of format (frequency or probability format) creates opportunities for manipulation. Decisions from Global Impressions The evidence suggests the hypothesis that focal attention and salience contribute to both the overestimation of unlikely events and the overweighting of unlikely outcomes (there are exceptions). Salience is enhanced by mere mention of an event, by its vividness, and by the format in which probability is described. Choice from description yields a possibility effect—rare outcomes are overweighted relative to their probability (Prospect Theory). In sharp contrast, overweighting is never observed in choice from experience, and underweighting is common. The interpretation of choice from experience is not yet settled. The probability of a rare event will (often, not always) be overestimated, because of the confirmatory bias of memory. Thinking about that event, you try to make it true in your mind. A rare event will be overweighted if it specifically attracts attention. Separate attention is effectively guaranteed when prospects are described explicitly (“99% chance to win $1,000, and 1% chance to win nothing”). When there is no overweighting, there will be neglect. When it comes to rare probabilities, our mind is not designed to get things quite right. Baron pp. 258 – 259: Experienced, predicted, and decision utility Experienced utility: Is what really matters. If you try two different kinds of beer, then the experience of drinking each beer is its true experienced utility. Predicted utility: The judgement you would make about each experience, how good it would be, possibly on the basis of memory of previous experience. Decision utility: Is inferred from your choice. Observe which one you choose. The three types of utility could conflict. Beer A might taste better (provide more experienced utility) than beer B, but you might predict the opposite. You might, for example, had a naive theory that a beer tastes better when you haven't had it for a while, and you might base your prediction on the fact that you haven't had B for a long time. Or, you might even predict that A would taste better, but you might choose B anyway because you follow a general heuristic of seeking variety, a rule that here could let you down, in terms of experienced utility. Part of the reason that we cannot predict our experiences well is that we cannot remember them well. Our memories of the quality of experiences are excessively influenced by their endings and by their best or worst points, and we tend to ignore their duration. Normative models are about experienced or, more generally, true utility. Ideally, your judgments and decisions should agree with your experienced utility. But they do not. Many of the demonstrations show that choices are inconsistent with other choices made by the same person. In such cases, both choices reflect "decision utility," but they cannot possibly both reflect true (or experienced) utility. The idea that utility is "revealed" in our choices — a common assumption in economics — is thus misleading because our choices reveal decision utility only. Our actual choices may not lead to the best outcomes. They may be subject to biases. Baron pp. 262 – 267: Prospect Theory It is important to remember that prospect theory is descriptive, not normative. It explains how and why our choices deviate from the normative model of expected-utility theory. Prospect theory applies directly to situations like the Allais paradox. Prospect theory, as a modification of expected-utility theory, has two main parts: one concerning probability and one concerning utility. The theory retains the basic idea that we make decisions as though we multiplied something like a subjective probability by something like a utility. The more probable a consequence is, the more heavily we weigh its utility in our decision. According to prospect theory however, we distort probabilities, and we think about utilities as changes from a reference point. The reference point is easily affected by irrelevant factors, and this fact leads us to make different decisions for the same problem, depending on how it is presented to us. Pi and the certainty effect: In essence, prospect theory begins with the premise that we do not treat the probabilities as they are stated. Instead, we distort them, according to a particular mathematical function that Kahneman and Tversky named the "pi function," using the Greek letter π instead of the usual p for probability. Instead of multiplying our utilities by p, the researchers proposed, people multiply by π. The function is graphed in Figure 11.1. More generally, we can describe the π function by saying that people are most sensitive to changes in probability near the natural boundaries of 0 (impossible) and 1 (certain). Sensitivity to changes diminishes as we move away from these boundaries. Thus, a 0.1 increase in the probability of winning a prize has a greater effect on decisions when it changes probability of winning from 0 to 0.1 (turning an impossibility into a possibility) or from 0.9 to 1 (turning a possibility into a certainty) than when it changes the probability from, say, 0.3 to 0.4, or 0.6 to 0.7 (turning a smaller possibility into a larger possibility). Certainty effect: An improvement from 95% to 100% is a qualitative change that has a large impact, the certainty effect. Outcomes that are almost certain are given less weight than their probability justifies. Principle of invariance: One’s choices ought to depend on the situation itself, not on the way it is described. In other words, when we can recognize two descriptions of a situation as equivalent, we ought to make the same choices for both descriptions. Subjects seem to violate this principle which is also called “framing effect” because the choice made is dependent on how the situation is presented or “framed”. Is the certainty effect rational? Why should we not weigh certain (sure) outcomes more than uncertain ones? 1.) It leads us to more inconsistent decisions, decisions that differ as a function of the way things are described to us (or the way we describe things to ourselves). 2.) Our feeling of "certainty" about an outcome is often, if not always, an illusion. For example, you may think of ($30) as a certain outcome: You get $30. Unless having money is your only goal in life, though, the $30 is really just a means to other ends. You might spend it on tickets to a football game, for example, and the game might be close, and so exciting that you tell your grandchildren about it or it might be a terrible game, with the rain pouring down, and you, without an umbrella, having to watch your team get slaughtered. In short, most, if not all S1. Introduction Snoddgrass, pp.18-30: Independent variable = the one that is manipulated Dependent variable = outcome. The question of interest is whether the behavior we measure is dependent on the variable we manipulated. You can think of the independent variable as the cause of the behavior, and the dependent variable as its eﬀect. The hypothesis is tested by an experiment. Two Types of Experiments: True experiments: 1) there be at least two conditions or groups (experimental group and control group); 2) the independent variable is manipulated by the experimenter. Correlational or observational studies: 1) both variables whose relationships are sought can take on a number of diﬀerent values; 2) one variable does not necessarily have to depend on or be caused by, the second variable (correlation is not causation) Artificial (the experimenter has complete control over which subject is given which treatment) and natural (the experimenter has no control, independent variables are properties of the subject) experiments There is a natural experiment for every artificial experiment. A confounded variable is one that is correlated with the independent variable and thus can be responsible for the eﬀect in the question. Experimental Versus Correlational Methods In a natural experiment, the variable in the question is divided into two or more categories. These categories may be truly dichotomous (male, female) or may lie along a continuum but be divided into groups by the experimenter (whether the person drank coﬀee for lunch or not). When we measure the degree of relationship between two continuous or quasi-continuous variables, we use a rule correlational method. Independent, Control, and Dependent Variables A Variable is anything that can take on a number of values. Independent variables are those that are either manipulated or selected by the experimenter; Control variables are those held constant by the experimenter across the conditions of an experiment (subject variables: sex, intelligence, age, socioeconomic status, family history, etc; environmental variables: room in which the experiment is conducted, the sex and attitude of the experimenter, the time of the day, time of the year, etc); Dependent variables are those measured by the experimenter as some selected behavior of the subjects (people participating) An independent variable can take on any number of values (called levels), but the minimum number is two. One of the levels is often the control condition in which nothing is manipulated. Types of Experimental Designs We can classify experimental designs along at least three dimensions: 1) the number of independent variables that are manipulated; 2) The number of levels of the independent variable or variables that are used. Levels are the values of the independent variable that are used in the experiment. Each value or level is also called a condition; 3) Whether the same subjects receive all conditions or diﬀerent subjects are randomly assigned to the diﬀerent conditions. Randomized design or randomized groups design: diﬀerent subjects are assigned at random to the diﬀerent conditions of an experiment. Repeated measures or matched groups design: same subjects participate in all conditions of an experiment or diﬀerent subjects are matched on some basis across conditions. Matched group design: if the number of conditions or levels is small (usually only two) subjects are paired on some set of criteria related to the dependent variable. Mixed design: when there are two independent variables, one may be randomized and one may be matched. Generally, matched designs are preferred to randomized designs (the same subject or pair of subjects functions as their own controls, automatically controlling for the potentially confounding eﬀects of variables such as IQ, genetic history, and environment). Dependent variables are normally measured on an interval scale: it’s possible to compute averages (arithmetic means) on the data. Examples: number of correct responses, reaction time, and response on a seven-point rating scale of the questionnaire. These three aspects of the experimental design determine the appropriate statistical test. A Single Independent Variable Random Groups Design with Two Levels: Two levels of a single independent variable, two independent groups of subjects. Examples: comparing reaction time performance of neurotic and normal subjects. The independent variable is subject status (neurotic versus normal). There are two levels, or conditions, of the independent variable, but a single subject participates in only one condition. The appropriate statistical test is an independent groups t test. Matched or Related Measures Design with Two levels: Two levels of a single independent variable, a single subject participates in both conditions or each of two subjects paired on some criterion participates in one condition (statistically, members of a matched pair are treated as though they were the same person - the scores are paired). In a matched or repeated measures design, we have the advantage of statistically controlling some of the variance resulting from individual diﬀerences. Example (same subject participates in both conditions): comparing the speed of learning a list of words for the same subject under alcohol and no-alcohol conditions. Independent variable: alcohol consumption. Example of experiment in which subjects are paired or matched: comparing the IQs of the first and second-born children from the same families. Independent variable: birth order. In both designs, the appropriate statistical test is a matched pairs t test. Random Groups Design with More than Two Levels: More than two conditions of an independent variable, a diﬀerent group of subjects is run in each condition. Example: comparing school performance of students in four diﬀerent educational programs (e.g., open classroom, individualized studies, etc.). The independent variable is the educational program. A single subject participates in only one condition. The appropriate statistical test is a one-way randomized analysis of variance (ANOVA). Repeated Measures Design with More than Two Levels: More than two conditions of a single independent variable, each subject participates in all conditions. Example: comparison of patients on a memory task before, during and after therapy. The independent variable is status of therapy. The appropriate statistical test is a one-way repeated measures analysis of variance. Two Independent Variables Example: we are interested in both type of drug and drug dosage: we might want to test four types of drugs at each of three dosage levels - low, medium and high - in all possible combinations. This results in a total of twelve (4x3 = 12) conditions. When there are two independent variables, both may be random, both may have repeated measures, or one may be random and one may have repeated measures. Regardless of whether one or both factors (independent variables) have repeated measures, each may vary on any number of levels. If we let a refer to the number of levels of factor A and b refer to the number of levels of factor B, then the total number of diﬀerent conditions in a two-factor experiment is equal to the product of a x b. Completely Randomized Design: Example: subjects are asked to learn a set of material and then are tested for recall at one of three retention intervals - immediately, one hour later, and 24 hours later. The investigator also manipulates the meaningfulness of the material, using both sentences and nonsense syllables. Each subject is tested with only one retention interval and one type of material, so this is a completely randomized 3 x 2 design. Completely Repeated Measures Design: Example: recall of words as a function of both their imagery and their frequency in print is measured, in which two levels of imagery (high and low) and three levels of frequency (high, medium, and low) are factorially combined in a 2 x 3 design. Each subject is tested on his or her ability to memorize words from all six categories. Mixed Design: Often used when one of the variables is nature’s own, such as sex, race, birth order, or some personality characteristics (they can be selected, but not manipulated). These become the random-group independent variable, subjects are assigned only to one group (male or female, etc). Interaction in Two-Factor Experiments: One of the major purposes of manipulating two independent variables is to determine whether they interact. By interaction, we mean that the eﬀect of moving from one level to another in the fist factor is not the same for each level of the second factor. For example, adding salt to unsalted pork roast usually increases taste preference, whereas adding salt to unsalted ice cream usually decreases taste preference. In this case, salt interacts with food type. Shadish, Cook, & Campbell (2002): pp: 3-12: Defining Cause, Eﬀect, and Causal Relationships That which produces any simple or complex idea, we denote by the general name cause, and that which is produced, eﬀect. A cause is that which makes any other thing, either simple idea, substance or mode, begin to be; and an eﬀect is that, which had its beginning from some other thing. Inus condition - an insuﬃcient but non-redundant part of unnecessary but suﬃcient condition. Most causes are more accurately called inus condition. Many factors are usually required for an eﬀect to occur, but we rarely know all of them and how they relate to each other. To diﬀerent degrees, all causal relationships are context dependent, so the generalization of experimental eﬀects is always at issue. In an experiment, we observe what did happen when people received a treatment. The counterfactual (contrary to fact) is knowledge of what would have happened to those same people if they simultaneously had not received treatment. An eﬀect is the diﬀerence between what did happen and what would have happened. How do we know if cause and eﬀect are related? A causal relationship exists if (1) the cause preceded the eﬀect, (2) the cause was related to the eﬀect, and (3) we can find no plausible alternative explanation for the eﬀect other than the cause. These three characteristics mirror what happens in experiments in which (1) we manipulate the presumed cause and observe an outcome afterward; (2) we see whether variation in the cause is related to variation in the eﬀect; and (3) we use various methods during the experiment to reduce the plausibility of other explanations for the eﬀect, along with ancillary methods to explore the plausibility of those we cannot rule out. Experiments are the best method to study causal relationships (better than correlational studies, cause sometimes it’s impossible to know which of two variables came first). Correlation does not prove causation. Experiments explore the eﬀects of things that can be manipulated (dose of a medicine, number of children in a classroom, etc). Nonmanipulable events (e.g., the explosion of a supernova) or attributes (e.g., people’s ages, their raw genetic material, biological sex) cannot be causes in experiments. Analogue experiments can sometimes be done on nonmanipulable cause, that is, experiments that manipulate an agent that is similar to the cause of interest (instead of changing a person’s race (impossible), it’s possible to chemically induce skin pigmentation changes in volunteer individuals). Causal description - describing the consequences attributable to deliberately varying a treatment (flicking a light switch - obtaining illumination) Causal explanation - clarifying the mechanisms through which and the conditions under which that causal relationship holds (closing an insulated circuit). Experiments are very good with causal descriptions but do less well with causal explanations. So causal explanation is an important route to the generalization of causal descriptions because it tells us which features of the causal relationship are essential to transfer to other situations. There is a close parallel between descriptive and explanatory causation and molar (meaning something takes as a whole rather than in parts. An analogy is to physics, in which molar might refer to the properties or motions of masses, as distinguished from those of molecules or atoms that make up those masses) and molecular causation. Optional: Introduction from Kahneman Introduction to the topic of the book: intuition mistakes, errors of judgment and choice. History of how Kahneman worked with his colleague Amos Tversky: The whole topic started when the professors tried to answer the question «Does a human have an intuitive understanding of statistics?» They found out that the answer is no, but with certain reservations. Our intuition is unreliable. But we make many decisions and assumptions based on our intuition. Kahneman and Tversky started studying heuristic errors (heuristics is understood as a set of techniques and methods that facilitate and simplify the solution of cognitive, constructive, practical tasks). They faced the following heuristic distortions (mistakes in predictions): - judging by similarity (instead of statistical facts); - heuristic accessibility: the desire to rely on the ease of sorting information in memory. We judge statistical probability and frequency by how easy for us it is to remember a similar case); Normal tasks where we make mistakes by using heuristics: calculating the probability of events, predicting the future, evaluating hypotheses, and predicting frequency. Before their study two positions were generally accepted. Firstly, people are mostly rational and, as a rule, think reasonably. Secondly, most deviations from rationality are explained by emotions: for example, fear, attachment or hatred. The new studies show that we cannot assume this: there are constant errors of thinking of normal people and they are caused more by the mechanism of thinking itself than by a violation of the thinking process under the influence of emotions. Then they studied decision-making in conditions of uncertainty. They spent days inventing choice problems and looking to see if their intuitive preferences coincided with the logic of choice. Here, as well as in the study of value judgments, there were systematic deviations in their own decisions and intuitive preferences, which constantly violated the rational rules of choice. The article «Prospect Theory: An Analysis of Decision under Risk» has become a base for behavioral economics. Actual Studies: Slow and Fast Thinking How does expert intuition work? "The situation gave a hint, the hint gave the expert access to the information stored in memory, and the information gave an answer. Intuition is nothing but recognition.» Correct intuitive guesses arise when experts, having learned to recognize familiar elements in a new situation, act accordingly. - Aﬀect heuristic: when decisions and judgments are made directly based on feelings of liking and dislike, with little or no thought or argument. When a person faces a new task and has the right knowledge, intuition recognizes the situation, and the intuitive solution that comes to mind is likely to be correct. When the question is diﬃcult and there is no qualified solution, intuition still has a chance: the answer will come to mind quickly, but it will be the answer to another question. The investment director was faced with a diﬃcult question: "Should I invest money in Ford shares?" But his choice determined the answer to another question, easier and more akin to the original one: "Do I like Ford cars?" This is the essence of intuitive heuristics: when faced with a diﬃcult question, we answer an easier one, usually without noticing the substitution. A spontaneous search for an intuitive solution is not always successful: from time to time neither a rationally justified answer nor a heuristic guess comes to mind. In such cases, we often switch to a slower and deeper form of thinking that requires a lot of eﬀort. This is the "slow thinking" (System 2) mentioned in the book title. Quick thinking (System 1) includes both variants S5. Judgement by Heuristics Chapter 12 The Science of Availability One of Kahneman and Tversky’s projects was the study of what that called the availability heuristic. They thought of that heuristic when they asked themselves what people actually do when they wish to estimate the frequency of a category, such as “people who divorce after the age of 60” or “dangerous plants.” The answer was straightforward: instances of the class will be retrieved from memory, and if retrieval is easy and fluent, the category will be judged to be large. The availability heuristic, like other heuristics of judgment, substitutes one question for another: you wish to estimate the size se ost c d of a category or the frequency of an event, but you report an impression of the ease with which instances come to mind. Substitution of questions inevitably produces systematic errors. You can discover how the heuristic leads to biases by following a simple procedure: list factors other than frequency that make it easy to come up with instances. Each factor in your list will be a potential source of bias. Examples: -A salient event that attracts your attention will be easily retrieved from memory like Divorces among Hollywood celebrities. You are therefore likely to exaggerate the frequency of both Hollywood divorces and political sex scandals. -A dramatic event temporarily increases the availability of its category. A plane crash that attracts media coverage will temporarily alter your feelings about the safety of flying. Accidents are on your mind, for a while, after you see a car burning at the side of the road, and the world is for a while a more dangerous place. -Personal experiences, pictures, and vivid examples are more available than incidents that happened to others, or mere words, or statistics. A judicial error that affects you will undermine your faith in the justice system more than a similar incident you read about in a newspaper. The Psychology of Availability The ease with which instances come to mind is a System 1 heuristic, which is replaced by a focus on content when System 2 is more engaged. Multiple lines of evidence converge on the conclusion that people who let themselves be guided by System 1 are more strongly susceptible to availability biases than others who are in a state of higher vigilance. The following are some conditions in which people “go with the flow” and are affected more strongly by ease of retrieval than by the content they retrieved: -when they are engaged in another effortful task at the same time -when they are in a good mood because they just thought of a happy episode in their life -if they score low on a depression scale -if they are knowledgeable novices on the topic of the task, in contrast to true experts -when they score high on a scale of faith in intuition -if they are (or are made to feel) powerful Chapter 14 Tom W’s Specialty It was an experiences about base rate. It requires to rank the following nine fields of graduate specialization in order of the likelihood that Tom W is now a student in each of these fields: business administration computer science engineering humanities and education law medicine library science physical and life sciences social science and social work The relative size of enrollment in the different fields is the key to a solution. So far as you know, Tom W was picked at random from the graduate students at the university, like a single marble drawn from an urn. To decide whether a marble is more likely to be red or green, you need to know how many marbles of each color there are in the urn. The proportion of marbles of a particular kind is called a base rate. Similarly, the base rate of humanities and education in this problem is the proportion of students of that field among all the graduate students. In the absence of specific information about Tom W, you will go by the base rates and guess that he is more likely to be enrolled in humanities and education than in computer science or library science, because there are more students overall in the humanities and education than in the other two fields. Using base-rate information is the obvious move when no other information is provided. The second task that has nothing to do with base rates. Need to define Tom’s speciality based on personality sketch of Tom W written during Tom’s senior year in high school by a psychologist, on the basis of psychological tests of uncertain validity: Tom W is of high intelligence, although lacking in true creativity. He has a need for order and clarity, and for neat and tidy systems in which every detail finds its appropriate place. His writing is rather dull and mechanical, occasionally enlivened by somewhat corny puns and flashes of imagination of the sci-fi type. He has a strong drive for competence. He seems to have little feel and little sympathy for other people, and does not enjoy interacting with others. Self-centered, he nonetheless has a deep moral sense. It is necessary to rank the nine fields of specialization listed below by how similar the description of Tom W is to the typical graduate student in each of the following fields. For example, hints of nerdiness (“corny puns”) -> computer science “neat and tidy systems” -> engineering If you examine Tom W again, you will see that he is a good fit to stereotypes of some small groups of students (computer scientists, librarians, engineers) and a much poorer fit to the largest groups (humanities and education, social science and social work). Predicting by Representativeness The third task in the sequence was administered to graduate students in psychology, and it is the critical one: rank the fields of specialization in order of the likelihood that Tom W is now a graduate student in each of these fields. The members of this prediction group knew the relevant statistical facts: they were familiar with the base rates of the different fields, and they knew that the source of Tom W’s description was not highly trustworthy. However, it is expected them to focus exclusively on the similarity of the description to the stereotypes—that they called it representativeness—ignoring both the base rates and the doubts about the veracity of the description. They would then rank the small specialty— computer science—as highly probable, because that outcome gets the highest representativeness score. Although it is common, prediction by representativeness is not statistically optimal. The Sins of Representativeness Judging probability byals representativeness has important virtues: the intuitive impressions that it produces are often—indeed, usually—more accurate than chance guesses would be. -On most occasions, people who act friendly are in fact friendly. -A professional athlete who is very tall and thin is much more likely to play basketball than football. -People with a PhD are more likely to subscribe to The New York Times than people who ended their education after high school. -Young men are more likely than elderly women to drive aggressively. One sin of representativeness is an excessive willingness to predict the occurrence of unlikely (low base-rate) events. Here is an example: you see a person reading The New York Times on the New York subway. Which of the following is a better bet about the reading stranger? -She has a PhD. -She does not have a college degree. Representativeness would tell you to bet on the PhD, but this is not necessarily wise. You should seriously consider the second alternative, because many more nongraduates than PhDs ride in New York subways. People without training in statistics are quite capable of using base rates in predictions under some conditions. As a result of experiment with student of Harvard university laziness seems to be the proper explanation of base-rate neglect. The second sin of representativeness is insensitivity to the quality of evidence. Recall the rule of System 1: WYSIATI. In the Tom W example, what activates your associative machinery is a description of Tom, which may or may not be an accurate portrayal. The statement that Tom W “has little feel and little sympathy for people” was probably enough to S3 p. 11 Not all intuitive judgements are produced only by heuristics, some expert decisions are explained by prolonged practice and skills. For example, a firefighter commander saved his team from death when he shouted to escape just before the floor collapsed without understanding why. Only later he realized that there were some unusual signals which prompted a sense of danger inside of him. Another examples of expert intuition are when the chess master who knows that the mate is coming or when physician makes a diagnosis after the first glance. Expert intuition strikes us as magical, but we all can do this in everyday life. In fact valid intuitions develop when experts have learned to recognize familiar elements in a new situation and to act in a manner that is appropriate to it. Chapter 1 The Characters of the Story To observe your mind in automatic mode, glance at the image below. You can easily predict her mood or anticipate what she might do without effort. This is an example of fast thinking. Now look at the following problem: Although you can quickly recognize that it’s a multiplication problem and even have some vague knowledge of range of possible results, the precise solution didn’t come to mind. In order to calculate it the mental work process (deliberate, effortful, and orderly) is needed. This is an example of slow thinking. Two Systems I adopt terms originally proposed by the psychologists Keith Stanovich and Richard West, and will refer to two systems in the mind as System 1 and System 2.  System 1 operates automatically and quickly, with little or no effort and no sense of voluntary control.  System 2 allocates attention to the effortful mental activities that demand it, including complex computations. The operations of System 2 are often associated with the subjective experience of agency, choice, and concentration. When we think of ourselves, we identify with System 2 which make makes choices. However, the automatic System 1 is the hero of the book. Because System 1 generates impressions and feelings that are the main sources of the explicit beliefs and deliberate choices of System 2. You will be invited to think of the two systems as agents with their individual abilities, limitations, and functions. In rough order of complexity, here are some examples of the automatic activities that are attributed to System 1:  Detect that one object is more distant than another.  Orient to the source of a sudden sound.  Complete the phrase “bread and...”  Make a “disgust face” when shown a horrible picture.  Detect hostility in a voice.  Answerto2+2=?  Read words on large billboards.  Drive a car on an empty road.  Find a strong move in chess (if you are a chess master).  Understand simple sentences.  Recognize that a “meek and tidy soul with a passion for detail” resembles an occupational stereotype. All these mental events belong with the angry woman—they occur automatically and require little or no effort. The capabilities of System 1 include innate skills that we share with other animals (recognize objects, orient attention,…). Other mental activities become fast and automatic through prolonged practice (reading and understanding nuances of social situations). Some skills, such as finding strong chess moves, are acquired only by specialized experts. Several of the mental actions in the list are completely involuntary (understanding simple sentences in your own language). Other activities, such as chewing, are susceptible to voluntary control but normally run on automatic pilot. The control of attention is shared by the two systems. Orienting to a loud sound is normally an involuntary operation of System 1, which immediately mobilizes the voluntary attention of System 2. The highly diverse operations of System 2 have one feature in common: they require attention. Here are some examples:  Brace for the starter gun in a race.  Focus attention on the clowns in the circus.  Focus on the voice of a particular person in a crowded and noisy room.  Look for a woman with white hair.  Search memory to identify a surprising sound.  Maintain a faster walking speed than is natural for you.  Monitor the appropriateness of your behavior in a social situation.  Count the occurrences of the letter a in a page of text.  Tell someone your phone number.  Park in a narrow space (for most people except garage attendants).  Compare two washing machines for overall value.  Fill out a tax form.  Check the validity of a complex logical argument. System 2 has some ability to change the way System 1 works, by programming the normally automatic functions of attention and memory. When waiting for a relative at a busy train station, for example, you can set yourself at will to look for a white-haired woman. You dispose of a limited budget of attention that you can allocate to activities. It is the mark of effortful activities that they interfere with each other, which is why it is difficult or impossible to conduct several at once. You could not compute the product of 17 × 24 while making a left turn into dense traffic, and you certainly should not try. You can do several things at once, but only if they are easy and undemanding. You are probably safe carrying on a conversation with a passenger while driving on an empty highway. Everyone understands the limited capacity of attention and adjust social behavioral accordingly. When the driver of a car is overtaking a truck on a narrow road, for example, adult passengers quite sensibly stop talking. Intense focusing on a task can make people effectively blind, even to stimuli that normally attract attention. The most dramatic demonstration was done with “The Invisible Gorilla” experiment. They constructed a short film of two teams passing basketballs, one team wearing white shirts, the other wearing black. The viewers of the film are instructed to count the number of passes made by the white team, ignoring the black players. This task is difficult and completely absorbing. Halfway through the video, a woman wearing a gorilla suit appears, crosses the court, thumps her chest, and moves on. The gorilla is in view for 9 seconds. Many thousands of people have seen the video, and about half of them do not notice anything unusual. It is the counting task—and especially the instruction to ignore one of the teams— that causes the blindness. No one who watches the video without that task would miss the gorilla. Seeing and orienting are automatic functions of System 1, but they depend on the allocation of some attention to the relevant stimulus. The authors note that the most remarkable observation of their study is that people find its results very surprising. Indeed, the viewers who fail to see the gorilla are initially sure that it was not there— they cannot imagine missing such a striking event. The gorilla study illustrates two important facts about our minds: we can be blind to the obvious, and we are also blind to our blindness. Plot Synopsis How the interaction of the two systems works? System 1 runs automatically and System 2 is normally in a comfortable low-effort mode, in which only a fraction of its capacity is engaged. System 1 continuously generates suggestions for System 2: impressions, intuitions, intentions, and feelings. If endorsed by System 2, impressions and intuitions turn into beliefs, and impulses turn into voluntary actions. When System 1 runs into difficulty, attention associated with System 2 is needed to solve it. For example, System 2 is mobilized when a question arises for which System 1 does not offer an answer. Also, System 2 is activated when an event is detected that violates the model of the world that System 1 maintains. System 2 is also credited with the continuous monitoring of your own behavior or safes you when an error about to be made. The division of labor between System 1 and System 2 is highly efficient: it minimizes effort and optimizes performance. The arrangement works well most of the time because System 1 is generally very good at what it does: its models of familiar situations are accurate, its short-term predictions are usually accurate as well, and its initial reactions to challenges are swift and generally appropriate. System 1 has biases, however, systematic errors that it is prone to make in specified circumstances. It sometimes answers easier questions than the one it was asked, and it has little understanding of logic and statistics. Conflict The book describes a classic experiment that produces a conflict between the two systems. The idea is that you will experience a conflict between a task that you intend to carry out (engages System 2) if there is an automatic response that interfered with it (engages System 1). This is what happens in the first task when you try to call out whether each word in the right column is printed in lowercase or in uppercase by saying “LOWER” or “UPPER” but trying to ignore the words itself. Or in the second task when when you try to say whether each word in the left column is printed to the left or to the right of the center by saying “LEFT” or “RIGHT” trying to ignore the words itself as well. As a result, you will do the task more slowly and less accurately than you could. This conflict also is common in our lives. We are all familiar with the experience of trying not to stare at the oddly dressed couple at the neighboring table in a restaurant. One of the tasks of System 2 is to overcome the impulses of System 1. In other words, System 2 is in charge of self-control. Illusions If you look at the picture above System 1 will tell you that the bottom line is obviously longer than the one above it. However, if you measure these lines with a ruler System 2 will come to the conclusion that the horizontal lines are in fact identical in length. And even if you choose to believe the measurement rather than visual expression you can’t prevent System 1 to see the lines as equal although you know they are not. This is the famous Müller-Lyer illusion. To resist the illusion, there is only one thing you can do: you must learn to mistrust your impressions of the length of lines when fins are attached to them. To implement that rule, you must be able to recognize the illusory pattern and recall what you know about it. If you can do this, you will never again be fooled by the Müller-Lyer illusion. Not all illusions are visual. There are illusions of thought, which we call cognitive illusions. For example, there is a psychopathic charm concept which means that although a psychotherapist might have a strong attraction to a new patient with a repeated history of failed treatment it is a danger sign and causes a cognitive illusion. And like with the parallel lines the best solution would be to recognize such situations and not to believe it or act on it. The question that is most often asked about cognitive illusions is whether they can be overcome. Because System 1 operates automatically and cannot be turned off at will, errors of intuitive thought are often difficult to prevent. Biases cannot always be avoided, because System 2 may have no clue to the error. But even if it knows about errors they could be prevented only by constant monitoring by System 2 which is very impractical. So, the best solution here would be to learn to recognize situations in which mistakes are likely and try harder to avoid significant mistakes when the stakes are high. Useful Fictions In this book the author refers to Systems 1 and System 2 as subjects with its own characters and limitations. Although this has provoked some discussion among professionals about whether this is acceptable, the author believes that this is helpful for understanding. First is that the mind—especially System 1—appears to have a special aptitude for the construction and interpretation of stories about active agents, who have personalities, habits, and abilities than about some objects. Second is that “System 1” and “System 2” are very short notations and therefore take less space in our working memory. This matters, because anything that occupies your working memory reduces your ability to think. pp. 35 – 38 from Chapter 2 The response to mental overload is selective and precise: System 2 protects the most important activity, so it receives the attention it needs; “spare capacity” is allocated second by second to other tasks. The sophisticated allocation of attention has been honed by a long evolutionary history which helps to improve chances for survival not only for humans. Even now System 1 takes over in emergencies and assigns total priority to self-protective actions. The pattern of activity associated with an action depends on skill level and intelligence level. The more skilled or/and intelligent a person is the less effort is needed and the fewer brain regions are involved. A general “law of least effort” applies to cognitive as well as physical exertion. The law asserts that if there are several ways of achieving the same goal, people will eventually gravitate to the least demanding course of action. In the economy of action, effort is a cost, and the acquisition of skill is driven by the balance of benefits and costs. The tasks that we studied varied considerably in their effects on the pupil. For some easy tasks pupils dilated much more than for others more effortful tasks. What makes some cognitive operations more demanding and effortful than others? Effort is required to maintain simultaneously in memory several ideas that require separate actions, or that need to be combined according to a rule—rehearsing your shopping list as you enter the supermarket, choosing between the fish and the veal at a restaurant, or combining a surprising result from a survey with the information that the sample was small, for example. A crucial capability of System 2 is the adoption of “task sets”: it can program memory to obey an instruction that overrides habitual responses. It will be effortful to set yourself up for a new exercise you have never done before, and effortful to carry it out, though you will surely improve with practice. One of the significant discoveries of cognitive psychologists in recent decades is that switching from one task to another is effortful, especially under time pressure. The ability to control attention and switch from one difficult task to another is among others a measure of intelligence. Time pressure is another driver of effort. The rush could be cause by either the metronome or by load of memory. The rate at which material decays in memory forces the pace, driving you to refresh and rehearse information before it is lost. So, any task that requires you to keep several ideas in mind at the same time has the same hurried character. The most effortful forms of slow thinking are those that require you to think fast. pp. 44 – 49 from Chapter 3 The Lazy System 2 One of the main functions of System 2 is to monitor and control thoughts and actions “suggested” by System 1, allowing some to be expressed directly in behavior and suppressing or modifying others. How closely does System 2 monitor the suggestions of System 1? The author describes 3 different experiments which try to check how system 2 works: The first experiment is to give intuitive answer to the this problem: A bat and ball cost $1.10. The bat costs one dollar more than the ball. How much does the ball cost? Result: Many thousands of university students have answered the bat-and-ball puzzle, and the results are shocking. More than 50% of students at Harvard, MIT, and Princeton ton gave the intuitive—incorrect—answer that the ball cost 10 cents. At less selective universities, the rate of demonstrable failure to check was in excess of 80%. If you check you will see that the correct answer is that the ball costs only 5 cents. The bat- and-ball problem is our first encounter with an observation that will be a recurrent theme of this book: many people are overconfident, prone to place too much faith in their intuitions. They apparently find cognitive effort at least mildly unpleasant and avoid it as much as possible. The second task is to determine logical validity of this conclusion and check if the conclusion follows from the two premises or not: All roses are flowers. Some flowers fade quickly. Therefore some roses fade quickly. Result: A large majority of college students endorse this syllogism as valid. In fact the argument is flawed, because it is possible that there are no roses among the flowers that fade quickly. Just as in the bat-and-ball problem, a plausible answer comes to mind immediately but it appears to be wrong. This experiment has discouraging implications for reasoning in everyday life. It suggests that when people believe a conclusion is true, they are also very likely to believe arguments that appear to support it, even when these arguments are unsound. If System 1 is involved, the conclusion comes first and the arguments follow. The third task is to quickly give answer to the following question: How many murders occur in the state of Michigan in one year? Result: The idea is that Detroit, a high-crime city, is in Michigan. And the respondents who were students from college in United States were aware of that. However, facts that we know do not always come to mind when we need them. People who remember that Detroit is in Michigan give higher estimates of the murder rate in the state than people who do not, but a majority of Frederick’s respondents did not think of the city when questioned about the state. We see that because the average guess by people who were asked about Michigan is lower than the guesses of a similar group who were asked about the murder rate in Detroit. Blame for a failure to think of Detroit can be laid on both System 1 and System 2. Whether the city comes to mind when the state is mentioned depends in part on the automatic function of memory which is an attribute of System 1. However, everyone has the option of slowing down to conduct an active search of memory for all possibly relevant facts—just as they could slow down to check the intuitive answer in the bat-and-ball problem. The extent of deliberate checking and search is a characteristic of System 2, which varies among individuals. Conclusion about all experiments: all three experiments have something in common. Failing these minitests appears to be, at least to some extent, a matter of insufficient motivation, not trying hard enough. Though anyone who can be admitted to a good university is certainly able to solve all of these problems but they are easily tempted to accept superficially plausible answer that comes readily to mind and stop thinking further. The author describes their System 2 by word laziness. On the contrary, those who avoid the sin of intellectual sloth and more skeptical to their intuition could be called “engaged.” Intelligence, Control, Rationality Researchers have applied diverse methods to examine the connection between thinking and self-control. Some experiments were conducted to answer this question. First experiment was conducted on four-year-old children who were given a choice between a small reward (one Oreo) which they could have at any time or a larger reward (two cookies) for which they have to wait for 15 minutes alone in a room facing a desk with just two objects: a single cookie and a bell that the child could ring at any time to call in the experimenter and receive the one cookie. Result: About half the children managed the feat of waiting for 15 minutes, mainly by keeping their attention away from the tempting reward. Ten or fifteen years later, a large gap had opened between those who had resisted temptation and those who had not. The resisters had higher measures of executive control in cognitive tasks, and especially the ability to reallocate their attention effectively. As young adults, they were less likely to take drugs. A significant difference in intellectual aptitude emerged: the children who had shown more self-control as four-year-olds had substantially higher scores on tests of intelligence. Second experiment was conducted on children aged four to six who were exposed during five 40-minute sessions to various computer games which required attention and control to succeed and become trickier with time. Result: The testers found that training attention not only improved executive control; scores on nonverbal tests of intelligence also improved and the improvement was maintained for several months. Other research concluded that specific genes and parenting techniques also affect the ability to control attention while attention ability is closely connected with the ability to control emotions. Third test was conducted on students who were given some tasks which invite an intuitive answer that is both compelling and wrong (as with bat- and-ball problem). Result: The results were similar to bat-and-ball problem in a sense that those who who score very low on this test—the supervisory function of System 2 is weak in these people—and found that they are prone to answer questions with the first idea that comes to mind and unwilling to invest the effort needed to check their intuitions. Individuals who uncritically follow their intuitions about puzzles are also prone to accept other suggestions from System 1. Fndings suggest that the characters of our psychodrama have different “personalities.” System 1 is impulsive and intuitive; System 2 is capable of reasoning, and it is cautious, but at least for some people it is also lazy. We recognize related differences among individuals: some people are more like their System 2; others are closer to their System 1. This simple test has emerged as one of the better predictors of lazy thinking. Keith Stanovich originally introduced the terms System 1 and System 2. He draws a sharp distinction between two parts of System 2—indeed, the distinction is so sharp that he calls them separate “minds.” One of these minds (he calls it algorithmic) deals with slow thinking, demanding computation, solves intelligence tests and switches from one task to another quickly and efficiently. However,

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