Behavior Analyst Quotes

The other buzzword that epitomizes a bias toward substitution is “big data.” Today’s companies have an insatiable appetite for data, mistakenly believing that more data always creates more value. But big data is usually dumb data. Computers can find patterns that elude humans, but they don’t know how to compare patterns from different sources or how to interpret complex behaviors. Actionable insights can only come from a human analyst (or the kind of generalized artificial intelligence that exists only in science fiction).

A person caught in a neurotic state, in some respects may well be compared to a man bewitched. Forced to a very low level of behavior, people suffering from a neurosis is capable of acting jarring and so destructive to themselves and to others, with basic or instinctive motivations.

Echophenomena, such as autistic echoing of phrases, are largely considered involuntary, even if such echoing is done voluntarily. (Such are the paradoxes of compliance.) Conversely, imitation, such as complying with a behavioral analyst's demand to mirror her jumping body, is regarded as voluntary, even if it is coerced or scripted.

The way of life is towards fulfillment, however, wherever it may lead. To restore a human being to the current of life means not only to impart self-confidence but also an abiding faith in the processes of life. A man who has confidence in himself must have confidence in others, confidence in the fitness and Tightness of the universe. When a man is thus anchored he ceases to worry about the fitness of things, about the behavior of his fellow-men, about right and wrong and justice and injustice. If his roots are in the current of life he will float on the surface like a lotus and he will blossom and give forth fruit. He will draw his nourishment from above and below; he will send his roots down deeper and deeper, fearing neither the depths nor the heights. The life that’s is in him will manifest itself in growth, and growth is an endless eternal process. He will not be afraid of withering, because decay and death are part of growth. As a seed he began and as a seed he will return. Beginnings and endings are only partial steps in the eternal process. The process is everything … the way … the Tao. The way of life! A grand expression. Like saying Truth. There is nothing beyond it … it is all. And so the analyst says Adapt yourself! He does not mean, as some wish to think—adapt yourself to this rotten state of affairs! He means: adapt yourself to life! Become an adept! That is the highest adjustment—to make oneself an adept.

Your Script Here’s what to tell someone or yourself while you’re totally unable to understand the reason for or source of a problem. Dear [Me/Family Member/Spouse/Overly Logical Friend]: I know it’s hard to understand why a [positive adjectives] person like me should have a problem with [addiction/politics/attraction to morons] but I do, and, to date, treatment with [three analysts/kabbalah/Judge Judy] hasn’t given me an answer that makes a difference. I’ve decided that ignorance is okay, but my problem isn’t, and that from now on I need to do everything I can to improve and manage my behavior, just to be the person I want to be. So I will be open about my problem [in meetings/press releases/tweets], welcome observations about my behavior [with/without retaliating], and track my progress over time [in my computer/Facebook/a secret journal that you should burn if I die]. And I will not give up.

The most-studied evidence, by the greatest number of economists, concerns what is called short-term dependence. This refers to the way price levels or price changes at one moment can influence those shortly afterwards-an hour, a day, or a few years, depending on what you consider "short." A "momentum" effect is at work, some economists theorize: Once a stock price starts climbing, the odds are slightly in favor of it continuing to climb for a while longer. For instance, in 1991 Campbell Harvey of Duke- he of the CFO study mentioned earlier-studied stock exchanges in sixteen of the world's largest economies. He found that if an index fell in one month, it had slightly greater odds of falling again in the next moth, or, if it had risen, greater odds of continuing to rise. Indeed, the data show, the sharper the move in the first, the more likely is is that the price trend will continue into the next month, although at a slower rate. Several other studies have found similar short-term trending in stock prices. When major news about a company hits the wires, the stock will react promptly-but it may keep on moving for the next few days as the news spreads, analysts study it, and more investors start to act upon it.

My own odyssey of therapy, over my forty-five-year career, is as follows: a 750-hour, five-time-a-week orthodox Freudian psychoanalysis in my psychiatric residency (with a training analyst in the conservative Baltimore Washington School), a year’s analysis with Charles Rycroft (an analyst in the “middle school” of the British Psychoanalytic Institute), two years with Pat Baumgartner (a gestalt therapist), three years of psychotherapy with Rollo May (an interpersonally and existentially oriented analyst of the William Alanson White Institute), and numerous briefer stints with therapists from a variety of disciplines, including behavioral therapy, bioenergetics, Rolfing, marital-couples work, an ongoing ten-year (at this writing) leaderless support group of male therapists, and, in the 1960s, encounter groups of a whole rainbow of flavors, including a nude marathon group.

Source credibility is one contributing factor that seems to influence change. People have a tendency to look up to authority figures for knowledge and direction. Expert opinion is effective in establishing the legitimacy of change and is tied to information control. Once a source is accepted on one issue, another issue may be established as well on the basis of prior acceptance of the source. The analyst looks for an audience's perceived image of the source. How does the audience regard the source? Are the people deferential, and do they accept the message on the basis of leadership alone? Is the propaganda agent a hero? Does the audience model its behavior after the propagandist's? How does the propagandist establish identification with the audience? Does she or he establish familiarity with the audience's locality, use local incidents, and share interests, hopes, hatreds, and so on?

By explaining the precise power that held groups together Freud could also show why groups did not fear danger. The members do not feel that they are alone with their own smallness and helplessness, as they have the powers of the hero-leader with whom they are identified. Natural narcissism-the feeling that the person next to you will die, but not you-is reinforced by trusting dependence on the leader's power. No wonder that hundreds of thousands of men marched up from trenches in the face of blistering gunfire in World War I. They were partially self-hypnotised, so to speak. No wonder men imagine victories against impossible odds: don't they have the omnipotent powers of the parental figure? Why are groups so blind and stupid?-men have always asked. Because they demand illusions, answered Freud, they "constantly give what is unreal precedence over what is real." And we know why. The real world is simply too terrible to admit; it tells man that he is a small, trembling animal who will decay and die. illusion changes all this, makes man seem important, vital to the universe, immortal in some way. Who transmits this illusion, if not the parents by imparting the macro-lie of the cultural causa-sui? The masses look to the leaders to give them just the untruth that they need; the leader continues the illusions that triumph over the castration complex and magnifies them into a truly heroic victory. Furthermore, he makes possible a new experience, the expression of forbidden impulses, secret wishes, and fantasies. In group behavior anything goes because the leader okays it. It is like being an omnipotent infant again, encouraged by the parent to indulge oneself plentifully, or like being in psychoanalytic therapy where the analyst doesn't censure you for anything you feel or think. In the group each man seems an omnipotent hero who can give full vent to his appetites under the approving eye of the father. And so we understand the terrifying sadism of group activity.

In conclusion, the American century is not over, if by that we mean the extraordinary period of American pre-eminence in military, economic, and soft power resources that have made the United States central to the workings of the global balance of power, and to the provision of global public goods. Contrary to those who proclaim this the Chinese century, we have not entered a post-American world. But the continuation of the American century will not look like it did in the twentieth century. The American share of the world economy will be less than it was in the middle of the last century, and the complexity represented by the rise of other countries as well as the increased role of non-state actors will make it more difficult for anyone to wield influence and organize action. Analysts should stop using clichés about unipolarity and multipolarity. They will have to live with both in different issues at the same time. And they should stop talking and worrying about poorly specified concepts of decline that mix many different types of behavior and lead to mistaken policy conclusions. Leadership is not the same as domination. America will have to listen in order to get others to enlist in what former Secretary of State Hillary Clinton called a multipartner world. It is important to remember that there have always been degrees of leadership and degrees of influence during the American century. The United States never had complete control. As we saw in Chapter 1, even when the United States had preponderant resources, it often failed to get what it wanted. And those who argue that the complexity and turmoil of today’s entropic world is much worse than the past should remember a year like 1956 when the United States was unable to prevent Soviet repression of a revolt in Hungary, French loss of Vietnam, or the Suez invasion by our allies Britain, France, and Israel. One should be wary of viewing the past through rose-tinted glasses. To borrow a comedian’s line, “hegemony ain’t what it used to be, but then it never was.” Now, with slightly less preponderance and a much more complex world, the United States will need to make smart strategic choices both at home and abroad if it wishes to maintain its position. The American century is likely to continue for a number of decades at the very least, but it will look very different from how it did when Henry Luce first articulated it.

Was this luck, or was it more than that? Proving skill is difficult in venture investing because, as we have seen, it hinges on subjective judgment calls rather than objective or quantifiable metrics. If a distressed-debt hedge fund hires analysts and lawyers to scrutinize a bankrupt firm, it can learn precisely which bond is backed by which piece of collateral, and it can foresee how the bankruptcy judge is likely to rule; its profits are not lucky. Likewise, if an algorithmic hedge fund hires astrophysicists to look for patterns in markets, it may discover statistical signals that are reliably profitable. But when Perkins backed Tandem and Genentech, or when Valentine backed Atari, they could not muster the same certainty. They were investing in human founders with human combinations of brilliance and weakness. They were dealing with products and manufacturing processes that were untested and complex; they faced competitors whose behaviors could not be forecast; they were investing over long horizons. In consequence, quantifiable risks were multiplied by unquantifiable uncertainties; there were known unknowns and unknown unknowns; the bracing unpredictability of life could not be masked by neat financial models. Of course, in this environment, luck played its part. Kleiner Perkins lost money on six of the fourteen investments in its first fund. Its methods were not as fail-safe as Tandem’s computers. But Perkins and Valentine were not merely lucky. Just as Arthur Rock embraced methods and attitudes that put him ahead of ARD and the Small Business Investment Companies in the 1960s, so the leading figures of the 1970s had an edge over their competitors. Perkins and Valentine had been managers at leading Valley companies; they knew how to be hands-on; and their contributions to the success of their portfolio companies were obvious. It was Perkins who brought in the early consultants to eliminate the white-hot risks at Tandem, and Perkins who pressed Swanson to contract Genentech’s research out to existing laboratories. Similarly, it was Valentine who drove Atari to focus on Home Pong and to ally itself with Sears, and Valentine who arranged for Warner Communications to buy the company. Early risk elimination plus stage-by-stage financing worked wonders for all three companies. Skeptical observers have sometimes asked whether venture capitalists create innovation or whether they merely show up for it. In the case of Don Valentine and Tom Perkins, there was not much passive showing up. By force of character and intellect, they stamped their will on their portfolio companies.

The masses look to the leaders to give them just the untruth that they need; the leader continues the illusions that triumph over the castration complex and magnifies them into a truly heroic victory. Furthermore, he makes possible a new experience, the expression of forbidden impulses, secret wishes, and fantasies. In group behavior anything goes because the leader okays it. It is like being an omnipotent infant again, encouraged by the parent to indulge oneself plentifully, or like being in psychoanalytic therapy where the analyst doesn't censure you for anything you feel or think. In the group each man seems an omnipotent hero who can give full vent to his appetites under the approving eye of the father. And so we understand the terrifying sadism of group activity.

The daughter of renowned Admiral Garrick Versio of the Imperial Security Bureau and famous artist Zeehay Versio may be a traitor to the glorious Empire,” holojournalist Alton Kastle stated, with just the right amount of horror in his smooth voice. “Captain Iden Versio has been recorded as spouting lies about the Empire and inciting violence, denouncing the brave subjects of the Death Star battle station who lost their lives while she survived. This is not in keeping with the behavior of the highly decorated captain hitherto, but the words are damning. “She is slated for an immediate court-martial. Hero of the Empire Admiral Nasha Garvan will prosecute, while the specialized legal-analyst droid HM-12 will provide proper defense as required by Imperial Navy law.

major threat to the psychoanalyst’s creativity in working with his patient is the patient’s relentless, aggressive attack on the analyst’s work with him. Attacks of this sort produce narcissistic lesions in the psychoanalyst. It is much easier for the analyst to tolerate aggression against any other aspects of his personality or behavior. The training analyst unable to tolerate the narcissistic candidate-analysand’s aggression may foster an unconscious collusion with the analysand, so that the latter’s aggression, particularly the destructive implications of unconscious envy, will not be explored. The

introspection and self-analysis, a creative capacity, an ability to think under adverse circumstances, ethical behavior that assures avoiding acting out in the counter transference, tolerance for the frustration of psychoanalytic work, particularly the ability to cope with uncertainties and with the temporary loss of the ability to understand. I would add, as related qualities, the analyst’s confidence in the possibility of acquiring new understanding through introspection and insight and of bringing about change through insight in oneself and others, at the same time maintaining respect for the limitations of both understanding and the change derived from it. The

A theory of technique cast in terms of the analyst's behavior is an effort to make the analyst's character disappear. If it did so, we could teach analysis by teaching technique. But it does not work that way. A good analyst does not try to be someone else; he or she tries to use his or her strengths, receptivity, even the willingness to be wrong or blind or deaf at times, to good advantage. (p. 439, emphasis added)

Today’s companies have an insatiable appetite for data, mistakenly believing that more data always creates more value. But big data is usually dumb data. Computers can find patterns that elude humans, but they don’t know how to compare patterns from different sources or how to interpret complex behaviors. Actionable insights can only come from a human analyst (or the kind of generalized artificial intelligence that exists only in science fiction).

single or index variables. As an example, consider the dependent variable “high school violence,” discussed in Chapter 2. We ask: “What are the most important, distinct factors affecting or causing high school violence?” Some plausible factors are (1) student access to weapons, (2) student isolation from others, (3) peer groups that are prone to violence, (4) lack of enforcement of school nonviolence policies, (5) participation in anger management programs, and (6) familiarity with warning signals (among teachers and staff). Perhaps you can think of other factors. Then, following the strategies discussed in Chapter 3—conceptualization, operationalization, and index variable construction—we use either single variables or index measures as independent variables to measure each of these factors. This approach provides for the inclusion of programs or policies as independent variables, as well as variables that measure salient rival hypotheses. The strategy of full model specification requires that analysts not overlook important factors. Thus, analysts do well to carefully justify their model and to consult past studies and interview those who have direct experience with, or other opinions about, the research subject. Doing so might lead analysts to include additional variables, such as the socioeconomic status of students’ parents. Then, after a fully specified model has been identified, analysts often include additional variables of interest. These may be variables of lesser relevance, speculative consequences, or variables that analysts want to test for their lack of impact, such as rival hypotheses. Demographic variables, such as the age of students, might be added. When additional variables are included, analysts should identify which independent variables constitute the nomothetic explanation, and which serve some other purpose. Remember, all variables included in models must be theoretically justified. Analysts must argue how each variable could plausibly affect their dependent variable. The second part of “all of the variables that affect the dependent variable” acknowledges all of the other variables that are not identified (or included) in the model. They are omitted; these variables are not among “the most important factors” that affect the dependent variable. The cumulative effect of these other variables is, by definition, contained in the error term, described later in this chapter. The assumption of full model specification is that these other variables are justifiably omitted only when their cumulative effect on the dependent variable is zero. This approach is plausible because each of these many unknown variables may have a different magnitude, thus making it possible that their effects cancel each other out. The argument, quite clearly, is not that each of these other factors has no impact on the dependent variable—but only that their cumulative effect is zero. The validity of multiple regression models centers on examining the behavior of the error term in this regard. If the cumulative effect of all the other variables is not zero, then additional independent variables may have to be considered. The specification of the multiple regression model is as follows:

Beyond One-Way ANOVA The approach described in the preceding section is called one-way ANOVA. This scenario is easily generalized to accommodate more than one independent variable. These independent variables are either discrete (called factors) or continuous (called covariates). These approaches are called n-way ANOVA or ANCOVA (the “C” indicates the presence of covariates). Two way ANOVA, for example, allows for testing of the effect of two different independent variables on the dependent variable, as well as the interaction of these two independent variables. An interaction effect between two variables describes the way that variables “work together” to have an effect on the dependent variable. This is perhaps best illustrated by an example. Suppose that an analyst wants to know whether the number of health care information workshops attended, as well as a person’s education, are associated with healthy lifestyle behaviors. Although we can surely theorize how attending health care information workshops and a person’s education can each affect an individual’s healthy lifestyle behaviors, it is also easy to see that the level of education can affect a person’s propensity for attending health care information workshops, as well. Hence, an interaction effect could also exist between these two independent variables (factors). The effects of each independent variable on the dependent variable are called main effects (as distinct from interaction effects). To continue the earlier example, suppose that in addition to population, an analyst also wants to consider a measure of the watershed’s preexisting condition, such as the number of plant and animal species at risk in the watershed. Two-way ANOVA produces the results shown in Table 13.4, using the transformed variable mentioned earlier. The first row, labeled “model,” refers to the combined effects of all main and interaction effects in the model on the dependent variable. This is the global F-test. The “model” row shows that the two main effects and the single interaction effect, when considered together, are significantly associated with changes in the dependent variable (p < .000). However, the results also show a reduced significance level of “population” (now, p = .064), which seems related to the interaction effect (p = .076). Although neither effect is significant at conventional levels, the results do suggest that an interaction effect is present between population and watershed condition (of which the number of at-risk species is an indicator) on watershed wetland loss. Post-hoc tests are only provided separately for each of the independent variables (factors), and the results show the same homogeneous grouping for both of the independent variables. Table 13.4 Two-Way ANOVA Results As we noted earlier, ANOVA is a family of statistical techniques that allow for a broad range of rather complex experimental designs. Complete coverage of these techniques is well beyond the scope of this book, but in general, many of these techniques aim to discern the effect of variables in the presence of other (control) variables. ANOVA is but one approach for addressing control variables. A far more common approach in public policy, economics, political science, and public administration (as well as in many others fields) is multiple regression (see Chapter 15). Many analysts feel that ANOVA and regression are largely equivalent. Historically, the preference for ANOVA stems from its uses in medical and agricultural research, with applications in education and psychology. Finally, the ANOVA approach can be generalized to allow for testing on two or more dependent variables. This approach is called multiple analysis of variance, or MANOVA. Regression-based analysis can also be used for dealing with multiple dependent variables, as mentioned in Chapter 17.

knowledge of cardiovascular disease and whether such knowledge reduces behaviors that put people at risk for cardiovascular disease. Simple regression is used to analyze the relationship between two continuous variables. Continuous variables assume that the distances between ordered categories are determinable.1 In simple regression, one variable is defined as the dependent variable and the other as the independent variable (see Chapter 2 for the definitions). In the current example, the level of knowledge obtained from workshops and other sources might be measured on a continuous scale and treated as an independent variable, and behaviors that put people at risk for cardiovascular disease might also be measured on a continuous scale and treated as a dependent variable. Scatterplot The relationship between two continuous variables can be portrayed in a scatterplot. A scatterplot is merely a plot of the data points for two continuous variables, as shown in Figure 14.1 (without the straight line). By convention, the dependent variable is shown on the vertical (or Y-) axis, and the independent variable on the horizontal (or X-) axis. The relationship between the two variables is estimated as a straight line relationship. The line is defined by the equation y = a + bx, where a is the intercept (or constant), and b is the slope. The slope, b, is defined as Figure 14.1 Scatterplot or (y2 – y1)/(x2 – x1). The line is calculated mathematically such that the sum of distances from each observation to the line is minimized.2 By definition, the slope indicates the change in y as a result of a unit change in x. The straight line, defined by y = a + bx, is also called the regression line, and the slope (b) is called the regression coefficient. A positive regression coefficient indicates a positive relationship between the variables, shown by the upward slope in Figure 14.1. A negative regression coefficient indicates a negative relationship between the variables and is indicated by a downward-sloping line. Test of Significance The test of significance of the regression coefficient is a key test that tells us whether the slope (b) is statistically different from zero. The slope is calculated from a sample, and we wish to know whether it is significant. When the regression line is horizontal (b = 0), no relationship exists between the two variables. Then, changes in the independent variable have no effect on the dependent variable. The following hypotheses are thus stated: H0: b = 0, or the two variables are unrelated. HA: b ≠ 0, or the two variables are (positively or negatively) related. To determine whether the slope equals zero, a t-test is performed. The test statistic is defined as the slope, b, divided by the standard error of the slope, se(b). The standard error of the slope is a measure of the distribution of the observations around the regression slope, which is based on the standard deviation of those observations to the regression line: Thus, a regression line with a small slope is more likely to be statistically significant when observations lie closely around it (that is, the standard error of the observations around the line is also small, resulting in a larger test statistic). By contrast, the same regression line might be statistically insignificant when observations are scattered widely around it. Observations that lie farther from the

In passing we mention Joseph Weizenbaum’s celebrated program ELIZA that mimics conversation between a patient and an analyst. It attracted a lot of attention, even a belief in the psychotherapist it simulates, to the extent that its inventor came to be surprised and even embarrassed by the misguided enthusiasm that the ELIZA program generated. The code supporting the program is simple, but the behavior is, at first, quite impressive. What we are after, however, is a code that rests on a pattern theoretic analysis of the human mind specifying the details of mental processes, and such codes will have to be complex. As we shall see it will take some complex software to achieve our goal, even roughly. To facilitate programming we shall write in MATLAB although this will result in slow execution. In a later stage we may compile the code into C++ or into executables, but at the moment

In passing we mention Joseph Weizenbaum’s celebrated program ELIZA that mimics conversation between a patient and an analyst. It attracted a lot of attention, even a belief in the psychotherapist it simulates, to the extent that its inventor came to be surprised and even embarrassed by the misguided enthusiasm that the ELIZA program generated. The code supporting the program is simple, but the behavior is, at first, quite impressive. What we are after, however, is a code that rests on a pattern theoretic analysis of the human mind specifying the details of mental processes, and such codes will have to be complex. As we shall see it will take some complex software to achieve our goal, even roughly. To facilitate programming we shall write in MATLAB although this will result in slow execution. In a later stage we may compile the code into C++ or into executables, but at the moment we are not concerned with computational speed.

the analyst finds that maintaining silence and a failure to respond to the most provocative and outrageous behavior by a patient is the cleverest way to get to the psychological truth of those actions.

And still my research continued. Foreign diplomatic sources informed me that, in spite of his stated rejection of any containment of an Iranian bomb, Obama would settle for capping Iran’s ability to make a bomb within one year—the so-called threshold capacity. Other analysts claimed the president regarded Iran as an ascendant and logical power—unlike the feckless, disunited Arabs and those troublemaking Israelis—that could assist in resolving other regional conflicts. I first heard this theory at Georgetown back in 2008, in conversations with think tankers and former State Department officials. They also believed that Iran’s radical Islam was merely an expression of interests and fears that the United States could, with sufficient goodwill, meet and allay. Such ideas initially struck me as absurd. After all, even irrational regimes such as Nazi Germany could take rational steps to reach fanatical goals. But Obama, himself, now began describing Iran’s behavior as “strategic” and “not impulsive.” The ayatollahs, he told Jeffrey Goldberg, “have their worldview, and they see their interests, and they respond to costs and benefits….[They] are not North Korea.” Suddenly, it seemed plausible that an America freed of its dependence on Middle Eastern oil and anxious to retreat from the region could view Iran as a dependable ally. The only hurdle remained that pesky nuclear program.

Amazon could use the data it has about buying behavior to help make these ads much more effective," said Karsten Weide, an analyst at researcher IDC. "Marketers would love to have another viable option beyond Google and Facebook for their advertising.

There is in the world today a great and mysterious force that shapes the fortunes of millions of people. It is called the stock market. There are people who claim to have special insights into this force. They are called stock analysts. Most of them have often been wrong about the market’s future behavior, and many of them have been wrong most of the time. In fact, it’s not clear that their advice is worth anything at all. Reputable economists have argued that you’re better off picking stocks randomly than seeking guidance from stock analysts; either way it’s the blind leading the blind, but in one case you don’t have to pay a commission. Nonetheless, stock analysis is a profitable line of work, even for some manifestly inept practitioners. Why? Because whenever people sense the presence of a puzzling and momentous force, they want to believe there is a way to comprehend it. If you can convince them that you’re the key to comprehension, you can reach great stature. This fact has deeply shaped the evolution of religion, and it seems to have done so since very near the beginning. Once there was belief in the supernatural, there was a demand for people who claimed to fathom it. And, judging by observed hunter-gatherer societies, there was a supply to meet the demand.

And indeed, much of the evidence presented in this book so far would appear to confirm this. From the Boeing executives who built faulty planes, to the Goldman Sachs analysts who lied to their clients before being bailed out by the taxpayer, the capitalist class seems to provide the best evidence that society is made up of innately selfish individuals whose cooperative impulses extend, at best, to their immediate family and friends. But this view is highly one-sided. As we will see in this chapter, people are capable of amazing feats of ingenuity, compassion, and cooperation -even in a social order as brutal and competitive as our own. Capitalism, of course, rewards the opposite behavior: ruthlessness, competitiveness, and self-interest. No wonder these are the behaviors we see most prominently on display at the top of our society. And those at the top are precisely those who benefit from the belief that everyone is just like them. You don't have to look particularly hard to find the view of humanity as inherently selfish repeated by those in positions of authority. The managers at Lucas Aerospace certainly shared this view. And it is no coincidence that Golding was a schoolmaster -he was probably quite used to being disobeyed by his students, and likely saw this as an indication of man's inherent selfishness. But disobedience to authority is not an indication of selfishness; it's an assertion of an individual's autonomy. In fact, the willingness to disobey is precisely what separates genuinely civilized societies from barbarous ones. One only has to listen to the testimony at the Nuremberg trials to see what can happen when people unquestionably obey their superiors.

Economists see the world through a different lens than anthropologists, biologists, classicists, or practitioners of any other discipline. They analyze issues and problems using economic theories that are based on particular assumptions about human behavior. These assumptions tend to be different than the assumptions an anthropologist or psychologist might use. A theory is a simplified representation of how two or more variables interact with each other. The purpose of a theory is to take a complex, real-world issue and simplify it down to its essentials. If done well, this enables the analyst to understand the issue and any problems around it. A good theory is simple enough to understand, while complex enough to capture the key features of the object or situation you are studying.

Three of the leading opponents of behavioral genetics collaborated on a book that set out to deconstruct the new science and reverse the biological tide. The book was Not in Our Genes, and the authors were three of the most vigilant critics of the genetic view: Richard Lewontin, a population geneticist at Harvard; the indefatigable Leon Kamin, who was then at Princeton’s psychology department; and Steven Rose, a neurobiologist at England’s Open University. Although the book had slight impact, it is worth examining as a compendium of the arguments and methods of the opponents of behavioral genetics, arguments that these critics, and their shrinking band of allies, continue to make despite repeated refutations. Throughout the text the authors, with admirable candor, proclaim their Marxist perspective and their “commitment to … a more socially just—a socialist—society.” Few pages go by without references to “dialectics,” “bourgeois society,” and “capitalist values.” The authors’ apparently feel their clean breast about their politics permitted wholesale assumptions about those of their opponents. We are leftists is their implicit claim; but you on the other side of the scientific fence are reactionaries. Liberals, they appeared to be saying, can have only one scientific view, theirs; any other must be right-wing and antiliberal. “Biological determinist ideas,” they say, “are part of the attempt to preserve the inequalities of our society and to shape human nature in its own image.” It must surely have come as unpleasant news to Sandra Scarr, Jerome Kagan, and other liberal psychologists to learn that they were striving to preserve society’s inequalities. In addition, the authors’ nasty assumptions of their opponents’ motives must have been an eye-opener to the hundreds of microbiologists, lab technicians, DNA scanners, rat-runners, statistical analysts, and all the others engaged in behavioral genetics research who learned from the book that they were going to work each day “to preserve the interests of the dominant class, gender, and race.” But the falsity of the authors’ premise goes well beyond slandering a few individuals. Throughout the text, the writers deny the possibility that scientists could exist who place their curiosity about the world ahead of their political agendas. Lewontin, Kamin, and Rose deny as well the possibility of any man or woman, including themselves, separating science from politics. (“Science is not and cannot be above ‘mere’ politics.”) They leave no room for the scientist who is so intrigued by new information, in this case gene-behavior discoveries, that he or she is oblivious to alleged political consequences. For the authors, all scientists who seek out biological influences on behavior, from Darwin to Robert Plomin, are willing servants of the status quo, if not promoters of a return to feudalism.

For organizational behavior expert Charles Handy, the S-curve is the essential form of how businesses, social organizations and political systems develop over time, “it is the line of all things human.”7 Tech analyst Paul Saffo advises to “look for the S-curve,” noting that the uptake of new technologies—from personal robots to driverless cars—is destined to follow its shape.8 Scholars have used the sigmoid curve to describe the rise and fall of ancient civilizations like the Roman Empire, but also to predict modern-day shifts, such as the decline of the United States as a global superpower.9 In the field of systems thinking, the authors of the Club of Rome’s 1972 report The Limits to Growth put the S-curve at the heart of their analysis.10 More recently, economist Kate Raworth has shown that mainstream economics assumes that GDP growth follows an “exponential curve left hanging in mid-air,” when the reality is that it is far more likely to level off into the shape of the S-curve.

This brings us to the necessity of Fall: what the Kantian link between dependence and autonomy amounts to is that Fall is unavoidable, a necessary step in the moral progress of man. That is to say, in precise Kantian terms: "Fall" is the very renunciation of my radical ethical autonomy; it occurs when I take refuge in a heteronomous Law, in a Law which is experience as imposed on me from the outside, i.e., the finitude in which I search for a support to avoid the dizziness of freedom is the finitude of the external-heteronomous Law itself. Therein resides the difficulty of being a Kantian. Every parent knows that the child’s provocations, wild and "transgressive" as they may appear, ultimately conceal and express a demand, addressed at the figure of authority, to set a firm limit, to draw a line which means "This far and no further!", thus enabling the child to achieve a clear mapping of what is possible and what is not possible. (And does the same not go also for hysteric’s provocations?) This, precisely, is what the analyst refuses to do, and this is what makes him so traumatic – paradoxically, it is the setting of a firm limit which is liberating, and it is the very absence of a firm limit which is experienced as suffocating. THIS is why the Kantian autonomy of the subject is so difficult – its implication is precisely that there is nobody outside, no external agent of "natural authority", who can do the job for me and set me my limit, that I myself have to pose a limit to my natural "unruliness." Although Kant famously wrote that man is an animal which needs a master, this should not deceive us: what Kant aims at is not the philosophical commonplace according to which, in contrast to animals whose behavioral patterns are grounded in their inherited instincts, man lacks such firm coordinates which, therefore, have to be imposed on him from the outside, through a cultural authority; Kant’s true aim is rather to point out how the very need of an external master is a deceptive lure: man needs a master in order to conceal from himself the deadlock of his own difficult freedom and self-responsibility. In this precise sense, a truly enlightened "mature" human being is a subject who no longer needs a master, who can fully assume the heavy burden of defining his own limitations. This basic Kantian (and also Hegelian) lesson was put very clearly by Chesterton: "Every act of will is an act of self-limitation. To desire action is to desire limitation. In that sense every act is an act of self-sacrifice.

[The search for the Magical Other] accounts for the fact that so many couples move from naive relatedness to the joustings of power. If you do not act as I wish, I shall bring about your compliance by my actions. I will control you, criticize you, abuse you, withdraw from you, sabotage you…And so, through tactics of dependence or anger or control, mixed with emotional and sexual withdrawal, one [of the partners] tries to force the Other back into one’s original, imaginary mold. Seldom are these attitudes and behaviors conscious.

Given the recent remarkable advances in artificial intelligence, scouting will probably involve “algorithmic warfare,” with competing AI systems plowing through vast amounts of data to identify patterns of enemy behavior that might elude human analysts. Identifying enemy operational tendencies may also aid commanders in employing their forces more effectively, similar to the way the introduction of operations research aided the allies in identifying effective convoy operations during the Battle of the Atlantic in World War II.30 AI could potentially assist efforts to develop malware, which could be used to erase or corrupt enemy scouting information, including the enemy’s AI algorithms themselves. If these efforts are successful, enemy commanders may lose confidence in their scouts, producing a “mission kill,” in which much of the enemy’s scouting force continues to operate but where its product is suspect.

My thesis holds that a revolution in the nature and content of communication—the Fifth Wave of information—has ended the top-down control elites exerted on the public during the industrial age. For this to be the case, I need to show how the perturbing agent, information, can influence power arrangements. Information must be seen to have real-life effects, and those effects must be meaningful enough to account for a crisis of authority. A century of research on media and information effects has delivered confusing if not contradictory findings. The problem for the analyst is again one of complexity and nonlinearity. Intuitively, it should be a simple matter to establish the effects of information. I see a truck bearing down on me, for example: that’s information. I move out of the way: that’s behavior caused by information. Or I watch television news of the US invasion of Iraq: that’s information. I form an opinion for or against, and agitate politically accordingly: that’s behavior caused by media information.

The ability to make rational decisions is limited, or bounded, by the extent of people’s information. To broaden employees’ understanding, a firm should promote a tradition of teamwork and interdependence and develop future leaders by rotating them among work assignments in different departments and geographic locations. In order to reduce structural secrecy, there may be short-term opportunity costs, but the long-term benefits are significant.12 Firms must think about long-term greed and what it means. Through actions and training, leaders must explain the pressures on short-term thinking and how the firm resolves the conflicts of short- and long-term goals. Potentially conflicting or confusing organizational goals, such as putting clients first while also having a duty to shareholders, require strong signals from leadership as to what is acceptable and unacceptable behavior. These nuances cannot be left to statements of principles; they must be modeled by leaders’ actions each day. Leaders must understand that external influences can shape the culture. For example, there are competitive, technological, and regulatory pressures. Responses to them can have unintended consequences, including drifting from principles. This can increase the probability of an organizational failure. An organization needs to understand to what extent models impact behavior, decisions made by business leaders, and organizational culture. For example, boards of directors of public companies should ask questions if earnings per share (EPS) estimates are too consistent with analysts’ estimates. They should ask whether the firm is managing to models or to what is in the best long-term interests of the firm. Leaders get too much credit and too much blame. Leaders need to uphold the firm’s shared values—and that is a key component to leadership.13 But too little emphasis is given to the organizational elements that shape behavior or provide an environment for leadership or change. An organization’s structure, incentives, and values last longer and have more impact than those of individual leaders. Usually when there is a change or loss or failure there is a tendency to blame one thing or one person, when typically there are complex organizational cultural reasons. It is the duty of leaders and board members to examine what is responsible, not who is responsible.

A schizophrenic’s apartment tends to be messy. The internal personality disorder—the mental fracture—often manifests in an external disorder, to the point where some schizophrenics engage the services of a housekeeper. On the other hand, the apartment of a behavioral analyst demands a certain rigor, mirroring a rectilinear mind accustomed to compartmentalizing pieces of information the way you’d arrange shoes in a storage cubby. As such, Sharko’s apartment pulled in two different directions. While the coffee cups piled up in the sink and the wrinkled suits and ties amassed in a corner of the bathroom, various other rooms, all very neat and tidy, made it look like the residence of a peaceful family. A lot of photos in frames, a small plant, a child’s room with old stuffed toys, the yellow wallpaper with its frieze of dolphins.