We Know Human Nature Intuitively

Let’s start with Homo economicus. We assume that individuals are rational, calculating costs and benefits. Why do we calculate costs and benefits? We are motivated to do so. The concept of rationality is itself a “psychological interpretation” of observed behavior, hence the natural connection between economics and psychology. How do we know that humans are motivated, consciously or otherwise, to be rational? J.N. Keynes, in his book The Scope and Method of Economics (1955), says that the basic principles of economics, including the principle of rational behavior, are a priori. That is, we know them both before and independent of observing human behavior. The “facts of human nature,” according to Keynes, are not directly observed; rather they were the result of “an introspective survey” of human motives (Lewin 1996, 1298). Economic laws, including the law of rational behavior, are thus derived from facts about human nature that are intuitive or obvious.

Max Weber argued that because we are human beings we understand the motives behind human behavior through our own introspections: “This verstehen, or intuitive understanding of human motivation, is what distinguishes the human sciences from the physical sciences” (cited in Lewin 1996, 1298). Verstehen is nothing more than Adam Smith’s concept of sympathy. On the other hand, the majority opinion on this subject within the economics profession is that economics as a “science” has little need for verstehen or intuition, or concepts such as consciousness or understanding. Understanding, in fact, is a “meaningless pursuit,” as science should limit itself to “observable empirical regularities” (ibid., 1305) and hence to describing these regularities. Slutsky, Hicks, Allen, and Samuelson were among the group preaching economics as a science approach. Slutsky focused on observable utility as expressed in price and quantity. Hicks and Allen continued this by replacing marginal utility with the marginal rate of substitution. Samuelson continued with revealed preferences (Schumpeter, 1954).

Behavioral economics assumes that cognitive activity—information processing—precedes behavior, serving as an intermediary between changes in the environment and changes in behavior. Human behavior is thus not mechanical, at least in the sense that it is variable. Understanding mechanical behavior requires an owner’s manual, a calculator, a computer program, or perhaps only a well-defined production or cost function. Understanding nonmechanical behavior—unpredictable, untaught, capricious, variable—makes verstehen, or intuition, more important. In a changing environment, an individual must seek patterns or similarities with known environments and/or know another person’s mind to predict how that person may behave. The fact is, human behavior comes in both mechanical and nonmechanical varieties. Robin Hogarth in his book Educating Intuition says that “humans have a variety of different information-processing systems that vary from the innate [intuitive] to the fully conscious, [and] that most of these systems operate continuously” (2001, 179).

In addition, none of the components of nonmechanical behavior may be motivated by utility maximization or psychological hedonism. William James rejected this one-motive approach to all human behavior, referring to it as unscientific and “narrow teleological superstition” (cited in Lewin 1996, 1299). Economists such as Keynes and Marshall understood that much is left out of economists’ theory of human behavior, but that this is inescapable in our attempt to be scientific. Harvey Leibenstein’s X-efficiency theory was based in part on the hypothesis that human behavior varies in the degree to which it exhibits rationality; he called this “selective rationality” (Leibenstein 1966). Herbert Simon referred to it as “bounded rationality” (Simon 1982).

The study of intuition may also yield significant payoffs because it is an ingredient in altruism. In The Heart of Altruism, Kristin Monroe states, “Early discussions of what contemporary scholars refer to as empathy and altruism utilize the term sympathy, Adam Smith being but one notable example” (1996, 243 n. 47). Furthermore, she reports that the word empathy comes from the German Einfühlung, meaning “the process of intuiting one’s way into an object or event to see it from the inside” (ibid.). Collard (1978) and Ickes (1997) have also discussed altruism and its relationship with empathy, sympathy, and intuition.

Intuition Is a Tool for Decision Making Under Uncertainty

A classic statement about uncertainty is that of Frank Knight in Risk, Uncertainty, and Profit (1964). What is not well known is that in Knight’s work, intuition plays a central part in dealing with uncertainty. According to Knight, perfect competition or an “imaginary society” is a “heroic abstraction.” First, this imaginary society contains rational people. Rational people have “practical omniscience,” and hence there is a lack of ignorance. Rational people know what they want; their motives are known consciously and are stable and consistent. Their responses are deliberate, and they know the consequences of their actions. Second, there is perfect mobility and no costs of adjustment. Third, there is costless intercommunication among people. Fourth, people make decisions independent of all others. Fifth, all activity is free and voluntary. These are the necessary conditions of perfect competition. Under perfect competition there is “general fore-knowledge of progressive changes” or knowledge of the “law of change.” Under these conditions profits will move toward zero.

In real life, perfect intercommunication and hence perfect knowledge do not exist. In real life there is uncertainty, inertia, indifference, and habit, and hence the possibility of profit. Knight reviews literature associating profits with many factors, including a reward for risking capital, bargaining power stemming mainly from “superior knowledge and foresight” about the direction of change in an ever-changing environment, “frictions” created by uncertainty hindering the competitive process, and dynamic changes that lower costs. However, it is not change as such that creates profit, but ignorance of change, unpredictable change, or error.

In order to distinguish change from ignorance, or predictable change from change that is not predictable, Knight distinguishes risk from uncertainty. Risk refers to situations in which there is measurable randomness, while uncertainty refers to unknowable randomness—ignorance. Uncertainty about human behavior stems from Knight’s belief that, unlike objects of the natural world, we are not unconscious mechanisms restricted to mechanistic behavior. We have consciousness and free will, feelings and emotions, and react to the same stimuli in various ways. We are motivated by love and hate, exhibit capriciousness, and are subject to persuasion. We are rational, deliberative, and purposive, but also emotional. Humans do not remain the same through time. We have memory and we adjust to experience. Unlike atoms, no two people are exactly the same, no two people react exactly the same to the same experience, and no two people experience the same “objective” environment exactly the same.

In Part 3 of Risk, Uncertainty, and Profit Knight examines the assumption of “practical omniscience.” Knowledge begins with consciousness, or awareness. Consciousness is “forward-looking”—it anticipates the future, it sees things coming before they materialize. Knight says that the biological purpose of the nervous system is for adapting to the environment to better one’s chances of survival, and this requires seeing ahead. Yet while Knight says that he is interested in the relationship between consciousness and knowledge and behavior, he also makes it clear that he is not interested in “the ultimate nature of reality or any other philosophical position.”

The process of human inference is, in short, a nonmechanical process, a “fundamental mystery,” and subject to error. Because of uncertainty we are forced to draw inferences about the meaning of a twinkle in another’s eye, lines around the mouth, tone of voice. Following Adam Smith (see Frantz 2000), Knight says that it is consciousness that allows us to make inferences through “‘sympathetic introspection’ into what is going on in the ‘mind’ of the other person(s).” This ability is the “mysterious capacity of interpretation.” Knight’s theory of knowledge is not a theory of “exact knowledge” offered by logic. Knight is not sure that the world is understandable to any great extent, but if it can be understood, this is done through logical processes. Even the “ordinary decisions of life are made on the basis of ‘estimates’ of a crude and superficial character” and based on a process that is “very obscure.” Hence logicians and psychologists have paid little attention to them. The obscurity, the subconscious nature, the apparent absence of logic, and the “mental rambling” nature of the process do not imply irrationality. This mental rambling is called judgment, common sense, and intuition. Knight considers intuition to be based on memory, association, and experience, a type of “unconscious induction,” and made more valuable when combined with analysis. In these ways he is similar to other economists, notably Mill (see Frantz 2002) and Simon (see Frantz 2003). Intuitions are subject to error, but at the same time the ability to make correct judgments is the prime determinant of an individual’s value and success in business.

Ronald Heiner in his 1983 paper “The Origin of Predictable Behavior” presents an interesting hypothesis: that uncertainty (caused by cognitive limits, the inability to make correct inferences from past experiences, and incorrect expectations) leads individuals to be cautious and follow rule-based behavior. Following rules, behavior becomes both predictable and more geared toward satisficing than maximizing. On the other hand, the lack of uncertainty leads individuals to “throw caution to the wind.” This leads behavior to be less predictable and more geared toward maximizing than satisficing. Hence, maximizing behavior, made possible by the lack of uncertainty, leads to unpredictable behavior.

Standard theory attempts to explain choices based on the individual’s competence (c) and the difficulty (d) of the decision, and assumes that (c – d) ~ 0. However, Heiner’s point is that the (c – d) gap creates uncertainty that leads to rule-based behaviors. The (c – d) gap is generated by two broad classes of variables: environmental and perceptual. The former determine the degree of complexity faced, while the latter determine competence for dealing with complexity. Uncertainty increases as the former increases and/or the latter decreases. Uncertainty also increases the chance of making the wrong decision or the right decision at the wrong time. Choosing right or wrong is determined by “whether some process—conscious or not—will cause (or prevent) an ‘alertness’ or ‘sensitivity’ to information that might prompt selection of an action” (Heiner 1983, 565). Being alert to information is a developed skill, and greater uncertainty and a desire for making choices require more of the being-alert-to-information skill. Heiner makes use of the word intuition with phrases such as “intuitively measure” (ibid., 565), “intuitively interpret” (ibid., 566), “this intuitively means” (ibid., 567), and “as intuitively suggested” (ibid., 568). He also says that it is intuitive that without uncertainty, maximum flexibility of behavior—the ability to “loosen up”—yields the largest benefit (ibid., 563).

Intuition/Emotions as Well as Reason Is an Instrument in Decision Making

Yaniv Hanoch says, “Indeed people use reason to respond to . . . motivations, but they also use emotions. What sets the stage is our emotional mechanism, while one function of reason is to explore the possible paths to get there. That is, while ends cannot be determined logically by reason, once ends are determined, it is the role of reason to take us there” (Hanoch 2002, 3). Emotions interact with reason (rational thinking) in at least two important ways: by limiting the number of options considered and by limiting the aspects of the environment considered. This is contrasted with subjective expected utility (SEU) theory, which assumes that individuals make a thorough examination of all options and aspects of the environment until a probability about the future can be constructed. Being boundedly rational means having the ability to discriminate between different pieces or sets of information, focus on a subset of available information, produce alternative scenarios, gather facts about the environment, and draw inferences from these facts (ibid., 6). Emotions serve these functions. Emotions have been designed by evolution to assist us in being boundedly rational (ibid., 7).

In his book Descartes’ Error: Emotion, Reason, and the Human Brain neurologist Antonio Damasio shows that intuition, emotions, and feelings play a positive role in rational decision making. A very important reason is that “the strategies of human reason probably did not develop, in either evolution or any single individual, without the guiding force of the mechanisms of biological regulation, of which emotion and feeling are notable expressions” (Damasio 1994, xii). Not all human decisions involve choosing and reasoning in the normal sense used by economists (conscious evaluation of the costs and benefits of various options). First, there are automatic bodily processes by which the body moves to a state of equilibrium. For example, a drop in blood sugar triggers physical changes in the body, leading to a state of hunger. We are neither conscious of nor have any control over these physical changes. Second, we engage in survival strategies that are automatic or instinctive. For example, when we see an oncoming car we automatically move away from it. We know that an oncoming car is dangerous and that the appropriate response or choice is to move. While we are conscious of what is going on, the movement away from the car is automatic. Third, there are many choices we make in our life—concerning career, family, friendships, recreation, vacations, saving, voting—that require us to reason and choose in the usual sense of the terms. These choices involve short- and long-run costs and benefits, all of which are shrouded by complexity and uncertainty. Descartes referred to the first two as being part of our “animal spirit,” while the third is characteristic of our “human spirit” (ibid., 165–68). The third category of decisions are those traditionally believed to be optimized through logic or “rationality” and in the absence of emotions.

The difficulty with rational decision making is that calculating costs and benefits so as to maximize subjective expected utility will take too much time and is subject to too much error. Two reasons are offered: the human attention span is too short, and the capacity of our working memory is too small. Second, the strategy of eliminating emotion from decision making “has far more to do with the way patients with prefrontal damage go about deciding than with how normals usually operate” (ibid., 172). In other words, the economic theory of rational decision making is best illustrated by brain-damaged individuals. The real-world decision-making process of individuals with normal brain functioning involves intuition. According to Damasio, the human mind at the beginning of a decision-making process is not a “blank slate” but contains numerous images gleaned from experience. Depending upon the circumstances surrounding the decision, a subset of the available images will be automatically activated. Even before reasoning takes place, when the mind considers an option with a bad outcome, the individual experiences an unpleasant gut feeling in the body. If the option contains a positive outcome, the gut feeling is pleasant. Because the feeling is in the body, Damasio uses the term somatic (soma being the Greek word for “body”). The gut feeling in the body “marks” an image, hence the term somatic marker. Damasio says that somatic markers are an example of “feelings generated from . . . emotions. Those emotions and feelings have been connected, by learning, to predicted future outcomes of certain scenarios” (ibid., 174). Feelings and emotions are not identical. An emotion is a physical phenomenon with bodily correlates that are often automatic and prompted within the subconscious. For example, fear affects the heart rate and facial and/or other muscles. Emotions are often automatic and prompted by the subconscious.

The somatic marker creates a feeling in the body that “forces attention on the negative outcome to which a given action may lead, and functions as an automated alarm signal which says: Beware of danger ahead if you choose the option which leads to this outcome. . . . The automated signal protects you against future losses, without further ado, and then allows you to choose from among fewer alternatives” (ibid., 173). Somatic markers, having screened alternatives, allow any subsequent cost-benefit calculations to be more accurate, and allow the decision-making process to be more efficient. There are two important implications. First, somatic markers make use of both attention and working memory, but it is our values that drive the process. After all, pleasant and unpleasant gut feelings imply values or preferences. Second, there is an optimal level of emotion because emotions can be either beneficial or costly in the process of decision making. Third, emotion and logic (or intuition and analysis) are complements rather than substitutes. While Pascal said, “The heart has reasons that reason does not know at all,” Damasio says, “The organism has some reasons that reason must utilize” (ibid., 200). We are not always conscious of somatic markers. Somatic markers also act subconsciously, affecting those parts of the brain that control our appetites. Thus, for no apparent reason we would feel drawn to or away from some particular behavior. He says, “This covert mechanism would be the source of what we call intuition, the mysterious mechanism by which we arrive at the solution of a problem without reasoning toward it” (ibid., 188).

Damasio reports the results of gambling experiments illustrating his somatic marker hypothesis. The experiment involves players turning over cards from four decks of cards. Some cards in decks A and B paid the player $100 (in play money), but others required payments in excess of $1,000. In decks C and D, some cards paid $50, while other cards required payments of less than $100 on average. Players without frontal lobe brain damage began by sampling cards from all four decks. Seeing high rewards from decks A and B, they showed a preference for these decks. As the game continued and they were forced to pay large sums by cards in decks A and B, they switched to decks C and D. Players with frontal lobe brain damage began by sampling cards from all four decks, then showed a preference for the high-reward decks, A and B. However, having lost large sums of money, they returned to their preference for decks A and B, lost all their money, and were forced to borrow more. Despite being attentive, riskaverse, and intelligent and possessing a preference to win, frontal-lobe-damaged individuals act “irrationally.” Damasio’s explanation is that people with frontal lobe damage lack somatic markers, thereby lacking an association between a stimulus and an appropriate somatic response. They act, therefore, as if they have an inappropriate preference for the present at the expense of the future. They have in Damasio’s terms, a “myopia for the future” (ibid., 218). It is as if they do not retain what they learned through education or experience; they do not have a theory of their own mind.

In another article on the same topic the author, Gretchen Vogel, states, “Intuition may deserve more respect than it gets these days. Although it’s often dismissed along with emotion as obscuring clear, rational thought, a new study suggests that it plays a critical role in humans’ ability to make smart decisions” (Vogel 1997, 1269). Four neuroscientists from the University of Iowa College of Medicine studied patients with damage to their ventromedial prefrontal cortex. People with damage to this part of the brain score high on IQ tests and memory tests as often as non-brain-damaged persons. However, they tend to be more indecisive and make poor choices in real-life situations. Brain-damaged patients and a control group were given four decks of cards, two “good” decks and two “bad” decks. Each person was given $2,000, and each card listed an amount of money they won or lost. In the long run, choosing from the bad deck led to net losses, while the good deck led to net gains. The brain-damaged patients showed no emotion (measured by no physiological changes that accompany nervousness) as their net losses continued to increase and did not tend to switch to the good deck. Members of the control group showed signs of nervousness after a series of losses and switched to the good decks. They also began switching to the good decks even before they could articulate to the researchers that the good decks were a better longterm strategy. In other words, members of the control group had a hunch about which deck to choose from even before their conscious mind could formulate a reason. An explanation for the result is that the ventromedial prefrontal cortex is the part of the brain that stores memories of past rewards and punishments and creates an unconscious response to current rewards and punishments, which we call a hunch or an intuition. The brain-damaged patients lack this intuitive ability and hence make poor decisions.

Intuition as a Component of Heuristics

Intuition can be an expression or form of a heuristic because both usually bypass all conscious thinking processes. Why use a heuristic or intuition? Because in a world that contains much risk and uncertainty, objective measures of probability are not always available. Human cognition processes may be divided into two broad groups: intuition and reason. Humans use both because human cognition is a dual process. Adjectives used to describe the intuitive process include automatic, effortless, rapid, parallel, affective, nonverbal, and experiential. Adjectives used to describe reason include analytical, deliberative, verbal, rational, and rule-based (Slovic 2001, 4). Kahneman and Tversky (1982) refer to intuition as a “natural assessment,” one with some advantages over reason. First, the intuitive process produces results faster than the analytical system. Second, under conditions of uncertainty, when objective measures of probability are not available, intuition becomes the best method for subjectively evaluating the probability of events. Third, because intuition is the product of a subconscious process, the conscious mind remains free to undertake other tasks and hence is more flexible. Fourth, in a complex environment, speed and flexibility are advantageous. In some sense, therefore, our intuitive system is more efficient than reason.

Evaluating intuitively based judgments implies a standard of comparison. One standard often used is how well intuitive judgments compare to those made by analytical methods such as the rules of probability. For example, the extension rule is a basic rule of probability and states that if A > B, then P(A) = P(B). The extension rule can also be stated as the conjunction rule, P(A & B) = (B). For example, are there more seven-letter words ending in -ing (A) or seven-letter words whose sixth letter is n (B)? Since -ing > -n-, the correct answer is B. Yet surveys show that people’s intuitions choose the former. Comparing actual intuitions to rules of probability creates a bias against intuitive judgments. In fact, rules of probability are statements of logic. Since nothing can be more logical than logic, intuitions can never be superior to the rules of probability. In any contest between intuition and logic, intuition’s best outcome is a tie. The Tversky and Kahneman research agenda on biases and errors in judgment from using heuristics (intuition) shows that intuition is at best only as good as logic. And the emphasis is on the shortcomings of intuition.

The fact is that “people do not normally analyze daily events into exhaustive lists of possibilities or evaluate compound probabilities by aggregating elementary ones. Instead, they commonly use a number of heuristics” (Tversky and Kahneman 2002, 20). Hence, intuitive judgments are not made by listing possibilities and evaluating compound probabilities. In Kahneman and Tversky’s prospect theory, intuitive judgments are shown to take many forms, including creating similarities or making associations between two or more events or people, perceptions of causality, and thinking about salient characteristics or archetypes of events or people. In each case, people are attempting to turn a difficult question into an easier one. In the example of -ing and -n- words, people can more easily remember the former, and thus they tend to believe that there are more of the former. During a hiring seminar a tenured faculty member is really trying to answer a difficult question: whether a candidate will remain intellectually active and is good enough to receive tenure. A simpler question is asked: how good is the candidate’s presentation? In attempting to answer the difficult question of whether a particular person is a librarian or a salesperson, people answer an easier question: are the known characteristics of that person more similar to those of a librarian or those of a salesperson? People make intuitive judgments by creating mental images of their environment in which relationships and rules are obvious, even if less detailed. This means that intuition is the result of mental model building.

The mental model and the form of the intuition are dependent upon the question being answered. For example, in answering the question of what percentage of men who have suffered a heart attack are over age sixty, we ask ourselves to picture the typical heart attack victim (the exemplar or archetype) from memory of stories we have seen and/or read. This is known as the availability heuristic. If we are asked to choose an occupation for someone we do not know based only on a sketch of their personality, we look for similarities between the personality sketch and the representative personality of a person in a particular occupation. This is called the representative heuristic. If we are asked to make an assessment of something we know nothing about, such as the number of countries in the United Nations, we draw upon whatever data we are given. This is known as anchoring. Intuitions are a natural assessment or judgment mechanism of the human brain, and may be the best choice when no other means of judgment is available. No one expects models to be accurate and full of detail. In fact, the model-as-map analogy states that the power of a map or a model is that it does not have too much detail. In turning difficult questions into simpler ones and in building a generalized mental map of the environment, people would seem to be rational in using their intuition. Unfortunately, our mental images of the world and the real world are not always consistent with each other. And just as models don’t always predict accurately, neither does intuition.

At the same time, when people attempt to think logically they often fail. It seems intuitive, therefore, that the true comparison should be between intuitive judgments and actual judgments when people are trying to be logical. If it’s correct that “people are not accustomed to thinking hard” (Kahneman and Frederick 2002, 58), then perhaps one reason we use intuition is because we are lazy. At the very least, intuition may be a second-best way of making decisions. In their preface to Heuristics and Biases, Gilovich, Griffin, and Kahneman state, “The core idea of the heuristics and biases program is that judgment under uncertainty is often based on a number of simplifying heuristics rather than more formal and extensive algorithmic processing. These heuristics typically yield accurate judgments but can give rise to systematic error” (2002, xv). In other words, intuition can be accurate, often complementing analysis, but is subject to systematic error. At the same time, the series of experiments by psychologists Amos Tversky and Daniel Kahneman have been acknowledged by economists as demonstrating that human decision making deviates significantly from the predictions of economic theory. For example, in Rethinking Intuition (1998), Tamara Horowitz, a philosopher, argues that the results of the Tversky and Kahneman experiments demonstrates that people’s intuitions produce decisions that are at odds with economic theory.

At the same time, what seems intuitively obvious to the casual observer today often turns out to be just plain wrong tomorrow. Once upon a time it was common sense that the earth was at the center of the universe. Once upon a time it was common sense that nature could not contain a vacuum. Once upon a time it was common sense that heavier objects fall faster than lighter objects. Galileo’s thought experiments in his “mind’s eye”—that is, his intuition—led to the new commonsense idea among physicists that all objects fall through a vacuum at the same speed. Once upon a time Newtonian physics was common sense among physicists. It was replaced by the common sense of Einstein’s theory of special relativity. From Aristotle and the Greeks to Galileo, Newton, and Einstein is a movement from one commonsense idea to another (Miller 1996). In one respect, it is common sense that common sense changes as we evolve and gain understanding of the world. While it may seem counterintuitive that what we consider to be common sense changes, it actually is intuitively obvious that common sense changes!

Kahneman and Tversky emphasized the representative, availability, an anchoring heuristics. Paul Slovic introduced economists to the “affect heuristic” (Slovic 2001). While economists generally assume that decisions are the result only of cognition, Slovic argues that affect proceeds and influences cognition: affect “lubricates reason” (ibid., 3–4). Hence, the existence of “dual-process” theories of how we think, know, process information, and make decisions. These two processes are “intuitive, automatic, natural, non-verbal, narrative, and experiential,” on one hand, and “analytical, deliberative, verbal, and rational,” on the other (ibid., 4). The intuitive system is affective in nature and is faster than the analytical system. The intuitive system is, therefore, also believed to be a more efficient way to interact with an uncertain, complex environment. The intuitive/affective system also relies on feeling states of which we may not be aware. In comparison, the analytical system relies on cognitions such as probabilities. There is a large body of research supporting the importance of affect in decision making. For example, we may have a positive feeling about strawberry Jell-O, but a negative feeling when hearing the name Bowl Championship Series.

While economists have focused on anticipated feelings such as regret and disappointment, psychologists have focused on immediate feelings and “visceral” or affective states occurring at the time of decisions (Lowenstein 2000; Slovic 2001). Visceral factors, or passions, include anger, fear, hunger, thirst, sexual desire, emotions, pain, and (drug) cravings. Unlike preferences, which are assumed to be stable and consistent in the short run, visceral states change quickly and are affected by the external environment and the condition of the body. Visceral states have long been assumed to be destructive of behavior, but they are essential to humans. They affect survival and reproduction and hence quality of life. They are essential in decision making, yet we tend to underestimate them, preferring instead to see our decisions as rationally formulated. Visceral factors are powerful enough to create an internal conflict in us between what we want to do and what we otherwise believe is the rational course of action. One example is that a visceral state such as fear can neutralize a rational evaluation of uncertainty (risk). Thus, utility maximization in the presence of visceral states, especially alternating “hot” and “cold” visceral states, is difficult. At high levels of visceral intensity we feel “out of control” and may be led to behave in ways contrary to what we believe to be our self-interest.

Affect affects our perception of risk. For example, the perception of risk from various hazards is positively correlated with feelings of danger about that hazard. Despite the fact that the benefits and costs of various hazards need not have any particular correlation, in laboratory studies people’s perception of benefit and cost are negatively correlated with each other. That is, if people feel that the benefits of nuclear power or pesticide use in farming are high, then they tend to judge the risks as being low. And where the risks are said to be low, the benefits are perceived to be high (Slovic et al. 2002, 410–11). Studies of toxicologists asked about the risks of exposure to very low levels of various chemicals (1/100th of the exposure level warranting regulators’ concern) show negative correlations between affect—the danger posed by the chemical—and perceived risk. Studies also show that people overpay for insurance when the object is beloved, regardless of its condition. Affective responses are part of almost every response or perception we have (Zajonc 1980). That is, we see a lovely sky, not a sky; a pretty face, not a face; an attractive house, not a house. Affect, therefore, affects preferences. In addition, the affective may be more important than is usually suggested when looking at the world through a cognitive or rational framework. Zajonc writes, “We sometimes delude ourselves that we proceed in a rational manner and weight all the pros and cons of the various alternatives. But this is probably seldom the actual case. Quite often, ‘I decided in favor of X’ is no more than ‘I liked X’” (ibid., 155). The affective is considered part of our experiential system of thinking or information processing, as opposed to our analytical system. The experiential also includes intuition.

“Fast and frugal” heuristics are decision-making strategies that rely on cues. For example, are there more homeless people per million population in New York or Chicago? To answer this without researching the answer, you look for cues, such as the existence of rent control and public housing; unemployment, vacancy, and poverty rates; and average temperature. In the “minimalist” heuristic, you randomly select a cue; if you select rent control, since cities with rent control tend to have more homeless people, and since New York has rent control and Chicago does not, then you would choose New York as probably having more homeless people. In the “take the best” heuristic, you pick the most important cue. The “choosing by default” heuristic means choosing the first option you think about. This is a classic way of making decisions intuitively. Choosing by default is known as an “automated choice heuristic” (Frederick 2002).

In a review of fast and frugal heuristics, Gigerenzer, Czerlinski, and Martignon (2002) find that their performance is comparable with multiple regression and Bayesian networks. In 1992, Spencer Johnson, coauthor of The One Minute Manager (Blanchard and Johnson 1982), published a book, “Yes” or “No”: The Guide to Better Decision Making (Johnson 1992), in which he described three questions you ask yourself when solving a problem: “Am I meeting the real need?” “Am I informing myself of options?” and “Am I thinking it through?” If your first thought about question 1 is yes, then you move on to question 2. If the answer to question 1 is no, then you begin analyzing what the real need is. When you get through with question 3, then you have made a better choice than you otherwise would.

Errors in judgment due to the use of intuition or heuristics are not limited to, say, undergraduates. Individuals of all levels of education and skill make such errors. Under- and overoptimism occur in predictions made by doctors, weather forecasters, lawyers, sports commentators, professional gamblers, economists, and stockbrokers (Koehler, Brenner, and Griffin 2002). Werner DeBondt and Richard Thaler studied the one- and two-year earnings-per-share forecasts by a group of professional forecasters. The result of their statistical analysis is that forecasters overreact and that earnings-per-share forecasts are unrealistically optimistic. The same overreaction has been reported in the literature for exchange rate and macroeconomic forecasts. DeBondt and Thaler conclude that the analysts surveyed are “decidedly human. The same pattern of overreaction found in the predictions of naïve undergraduates is replicated in the predictions of stock market professionals. Forecasted changes are simply too extreme to be considered rational. . . . When practitioners describe market crashes as panics, produced by investor overreaction, perhaps they are right” (2002, 685).

Herbert Simon’s studies of MBA students and experienced business executives asked to analyze a situation show that the two groups come to similar conclusions. However, the experienced executives came to their conclusion in much less time, “with the usual appearance of intuition” (Simon 1997, 136). The work of the MBA students, on the other hand, “was done slowly, with much conscious and explicit analysis” (ibid.). The conclusion Simon reaches is that experience allows people to make decisions intuitively, that is, to make judgments “without careful analysis and calculation” (ibid.). In a study of decision making among physicists, Simon and Simon studied the protocols of two people solving a physics problem by recording them verbalizing what they were thinking while solving the problem. One of the persons was a novice at this type of problem solving, the other an expert. The expert solved the problem in less time, did not follow the reason-only steps, required fewer steps to solve the problem, spent less time per step, did not write down as many relevant facts or equations to solve, and expressed more confidence. In essence, the skilled person took a series of appropriate shortcuts. These shortcuts imply that the expert used what Simon calls physical intuition—intuition used by physicists. That is, the expert read the problem, created a mental representation, and created a set of equations based on that mental representation to solve the problem. While the expert’s approach is more “physical” or “primitive” (Simon and Simon 1989, 224), the novice’s approach is more algebraic. The conclusion that physical intuition “accounts for the superior ability of physicists to solve physics problem should occasion no surprise. Physicists and teachers of physics have been saying that for years” (Simon and Simon 1989, 230).