24. For details of financial crises throughout the ages, see Mackay (1932), Kindleberger (1978), and Reinhart and Rogoff (2009).
25. There are, of course, several overlapping traditions in philosophy that already take a suspicious view of what I am calling common sense as their starting point. One way to understand the entire project of what Rawls called political liberalism (Rawls 1993), along with the closely related idea of deliberative democracy (Bohman 1998; Bohman and Rehg 1997), is, in fact, as an attempt to prescribe a political system that can offer procedural justice to all its members without presupposing that any particular point of view—whether religious, moral, or otherwise—is correct. The whole principle of deliberation, in other words, presupposes that common sense is not to be trusted, thereby shifting the objective from determining what is “right” to designing political institutions that don’t privilege any one view of what is right over any other. Although this tradition is entirely consistent with the critiques of common sense that I raise in this book, my emphasis is somewhat different. Whereas deliberation simply assumes incompatibility of commonsense beliefs and looks to build political institutions that work anyway, I am more concerned with the particular types of errors that arise in commonsense reasoning. Nevertheless, I touch on aspects of this work in chapter 9 when I discuss matters of fairness and justice. A second strand of philosophy that starts with suspicion of common sense is the pragmatism of James and Dewey (see, for example, James 1909, p. 193). Pragmatists see errors embedded in common sense as an important obstruction to effective action in the world, and therefore take willingness to question and revise common sense as a condition for effective problem solving. This kind of pragmatism has in turn influenced efforts to build institutions, some of which I have described in chapter 8, that systematically question and revise their own routines and thus can adapt quickly to changes that cannot be predicted. This tradition, therefore, is also consistent with the critiques of common sense developed here, but as with the deliberation tradition, it can be advanced without explicitly articulating the particular cognitive biases that I identify. Nevertheless, I would contend that a discussion of the biases inherent to commonsense reasoning is a useful complement to both the deliberative and pragmatist agendas, providing in effect an alternative argument for the necessity of institutions and procedures that do not depend on commonsense reasoning in order to function.
CHAPTER 2: THINKING ABOUT THINKING
1. For the original study of organ donor rates, see Johnson and Goldstein (2003). It should be noted that the rates of indicated consent were not the same as the eventual organ-donation rate, which often depends on other factors like family members’ approval. The difference in final donation rates was actually much smaller—more like 16 percent—but still dramatic.
2. See Duesenberry (1960) for the original quotation, which is repeated approvingly by Becker himself (Becker and Murphy 2000, p. 22).
3. For more details on the interplay between cooperation and punishment, see Fehr and Fischbacher (2003), Fehr and Gachter (2000 and 2002), Bowles et al. (2003), and Gurerk et al. (2006).
4. Within sociology, the debate over rational choice theory has played out over the past twenty years, beginning with an early volume (Coleman and Fararo 1992) in which perspectives from both sides of the debate are represented, and continued in journals like the American Journal of Sociology (Kiser and Hechter 1998; Somers 1998; Boudon 1998) and Sociological Methods and Research (Quadagno and Knapp 1992). Over the same period, a similar debate has also played out in political science, sparked by the publication of Green and Shapiro’s (1994) polemic, Pathologies of Rational Choice Theory. See Friedman (1996) for the responses of a number of rational choice advocates to Green and Shapiro’s critique, along with Green and Shapiro’s responses to the responses. Other interesting commentaries are by Elster (1993, 2009), Goldthorpe (1998), McFadden (1999), and Whitford (2002).
5. For accounts of the power of rational choice theory to explain behavior, see Harsanyi (1969), Becker (1976), Buchanan (1989), Farmer (1992) Coleman (1993) Kiser and Hechter (1998), and Cox (1999).
6. See Freakonomics for details (Levitt and Dubner 2005). For other similar examples see Landsburg (1993 and 2007), Harford (2006), and Frank (2007).
7. Max Weber, one of the founding fathers of sociology, effectively defined rational behavior as behavior that is understandable, while James Coleman, one of the intellectual fathers of rational choice theory, wrote that “The very concept of rational action is a conception of action that is ‘understandable’ action that we need ask no more questions about” (Coleman 1986, p. 1). Finally, Goldthorpe (1998, pp. 184–85) makes the interesting point that it is not even clear how we should talk about irrational, or nonrational behavior unless we first have a conception of what it means to behave rationally; thus even if it does not explain all behavior, rational action should be accorded what he calls “privilege” over other theories of action.
8. See Berman (2009) for an economic analysis of terrorism. See Leonhardt (2009) for a discussion of incentives in the medical profession.
9. See Goldstein et al. (2008) and Thaler and Sunstein (2008) for more discussion and examples of defaults.
10. For details of the major results of the psychology literature, see Gilovich, Griffin, and Kahneman (2002) and Gigerenzer et al., (1999). For the more recently established behavioral economics see Camerer, Loewenstein, and Rabin (2003). In addition to these academic contributions, a number of popular books have been published recently that cover much of the same ground. See, for example, Gilbert (2006), Ariely (2008), Marcus (2008), and Gigerenzer (2007).
11. See North et al. (1997) for details on the wine study, Berger and Fitzsimons (2008) for the study on Gatorade, and Mandel and Johnson (2002) for the online shopping study. See Bargh et al. (1996) for other examples of priming.
12. For more details and examples of anchoring and adjustment, see Chapman and Johnson (1994), Ariely et al. (2003), and Tversky and Kahneman (1974).
13. See Griffin et al. (2005) and Bettman et al. (1998) for examples of framing effects on consumer behavior. See Payne, Bettman, and Johnson (1992) for a discussion of what they call constructive preferences, including preference reversal.
14. See Tversky and Kahneman (1974) for a discussion of “availability bias.” See Gilbert (2006) for a discussion of what he calls “presentism.” See Bargh and Chartrand (1999) and Schwarz (2004) for more on the importance of “fluency.”
15. See Nickerson (1998) for a review of confirmation bias. See Bond et al. (2007) for an example of confirmation bias in evaluating consumer products. See Marcus (2008, pp. 53–57) for a discussion of motivated reasoning versus confirmation bias. Both biases are also closely to related to the phenomenon of cognitive dissonance (Festinger 1957; Harmon-Jones and Mills 1999) according to which individuals actively seek to reconcile conflicting beliefs (“The car I just bought was more expensive than I can really afford” versus “The car I just bought is awesome”) by exposing themselves selectively to information that supports one view or discredits the other.
16. See Dennett (1984).
17. According to the philosopher Jerry Fodor (2006), the crux of the frame problem derives from the “local” nature of computation, which—at least as currently understood—takes some set of parameters and conditions as given, and then applies some sort of operation on these inputs that generates an output. In the case of rational choice theory, for example, the “parameters and conditions” might be captured by the utility function, and the “operation” would be some optimization procedure; but one could imagine other conditions and operations as well, including heuristics, habits, and other nonrational approaches to problem solving. The point is that no matter what kind of computation one tries to write down, one must start from some set of assumptions about what is relevant, and that decision is not one that can be resolved in the same (i.e., local) manner. If one tried to resolve it, for example, by starting with some independent set
of assumptions about what is relevant to the computation itself, one would simply end up with a different version of the same problem (what is relevant to that computation?), just one step removed. Of course, one could keep iterating this process and hope that it terminates at some well-defined point. In fact, one can always do this trivially by exhaustively including every item and concept in the known universe in the basket of potentially relevant factors, thereby making what at first seems to be a global problem local by definition. Unfortunately, this approach succeeds only at the expense of rendering the computational procedure intractable.
18. For an introduction to machine learning, see Bishop (2006). See Thompson (2010) for a story about the Jeopardy-playing computer.
19. For a compelling discussion of the many ways in which our brains misrepresent both our memories of past events and our anticipated experience of future events, see Gilbert (2006). As Becker (1998, p. 14) has noted, even social scientists are prone to this error, filling in the motivations, perspectives, and intentions of their subjects whenever they have no direct evidence of them. For related work on memory, see Schacter (2001) and Marcus (2008). See Bernard et al. (1984) for many examples of errors in survey respondents’ recollections of their own past behavior and experience. See Ariely (2008) for additional examples of individuals overestimating their anticipated happiness or, alternatively, underestimating their anticipated unhappiness, regarding future events. For the results on online dating, see Norton, Frost, and Ariely (2007).
20. For discussions of performance-based pay, see Hall and Liebman (1997) and Murphy (1998).
21. Mechanical Turk is named for a ninteenth-century chess-playing automaton that was famous for having beaten Napoleon. The original Turk, of course, was a hoax—in reality there was a human inside making all the moves—and that’s exactly the point. The tasks that one typically finds on Mechanical Turk are there because they are relatively easy for humans to solve, but difficult for computers—a phenomenon that Amazon founder Jeff Bezos calls “artificial, artificial intelligence. See Howe (2006) for an early report on Amazon’s Mechanical Turk, and Pontin (2007) for Bezos’s coinage of “artificial, artificial intelligence.” See http://behind-the-enemy-lines.blogspot.com for additional information on Mechanical Turk.
22. See Mason and Watts (2009) for details on the financial incentives experiment.
23. Overall, women in fact earn only about 75 percent as much as men, but much of this “pay gap” can be accounted for in terms of different choices that women make—for example, to work in lower-paying professions, or to take time off from work to raise a family, and so on. Accounting for all this variability, and comparing only men and women who work in comparable jobs under comparable conditions, roughly a 9 percent gap remains. See Bernard (2010) and http://www.iwpr.org/pdf/C350.pdf for more details.
24. See Prendergast (1999), Holmstrom and Milgrom (1991), and Baker (1992) for studies of “multitasking.” See Gneezy et al. (2009) for a study of the “choking” effect. See Herzberg (1987), Kohn (1993), and Pink (2009) for general critiques of financial rewards.
25. Levitt and Dubner (2005, p. 20)
26. For details on the unintended consequences of the No Child Left Behind Act, see Saldovnik et al. (2007). For a specific discussion of “educational triage” practices that raise pass rates without impacting overall educational quality, see Booher-Jennings (2005, 2006). See Meyer (2002) for a general discussion on the difficulty of measuring and rewarding performance.
27. See Rampell (2010) for the story about politicians.
28. This argument has been made most forcefully by Donald Green and Ian Shapiro, who argue that when “everything from conscious calculation to ‘cultural inertia’ may be squared with some variant of rational choice theory … our disagreement becomes merely semantic, and rational choice theory is nothing but an ever-expanding tent in which to house every plausible proposition advanced by anthropology, sociology, or social psychology.” (Green and Shapiro, 2005, p. 76).
CHAPTER 3: THE WISDOM (AND MADNESS) OF CROWDS
1. See Riding (2005) for the statistic about visitors. See http://en.wikipedia.org/wiki/Mona_Lisa for other entertaining details about the Mona Lisa.
2. See Clark (1973, p. 150).
3. See Sassoon (2001).
4. See Tucker (1999) for the full article on Harry Potter. See (Nielsen 2009) for details of their Facebook analysis. See Barnes (2009) for the story on movies.
5. For the story about changes in consumer behavior postrecession, see Goodman (2009). Bruce Mayhew (1980) and Frank Dobbin (1994) have both made a similar argument about circular reasoning.
6. This argument was made long ago by the physicist Philip Anderson in a famous paper titled “More Is Different” (Anderson 1972).
7. For Thatcher’s original quote, see Keay (1987).
8. The definition of “methodological individualism” is typically traced to the early twentieth century in the writings of the Austrian economist Joseph Schumpeter (1909, p. 231); however, the idea goes back much earlier, at least to the writings of Hobbes, and was popular among the thinkers of the Enlightenment, for whom an individualistic view of action fit perfectly with their emerging theories of rational action. See Lukes (1968) and Hodgson (2007) for a discussion of the intellectual origins of methodological individualism, as well as a scathing critique of its logical foundations.
9. I am oversimplifying here, but not a lot. Although the original models of business cycles did assume a single representative agent, more recent models allow for multiple agents, each of which represents different sectors of the economy (Plosser 1989). Nevertheless, the same essential problem arises in all these models: the agents are not actually real people, or even firms, who pay attention to what other people and firms are doing, but rather are representative agents who make decisions on behalf of a whole population.
10. A number of excellent critiques of the representative individual idea have been written, most notably by the economist Alan Kirman (1992). That the criticism is so well known, however, and yet has had so little influence on the actual practice of social science, should demonstrate how difficult a problem it is to expunge.
11. Even rational choice theorists—who are as much as anyone the inheritors of methodological individualism—are in practice just as comfortable applying the principle of utility maximization to social actors like households, firms, unions, “elites,” and government bureaus as to individual people. See Becker (1976), Coleman and Fararo (1992), Kiser and Hechter (1998), and Cox (1999) for numerous examples of representative agents employed in rational choice models.
12. See Granovetter (1978) for details of the “riot model.”
13. For more details on the origins of social influence, see Cialdini (2001) and Cialdini and Goldstein (2004)
14. For examples of cumulative advantage models, see Ijiri and Simon (1975), Adler (1985), Arthur (1989), De Vany and Walls (1996), and De Vany (2004).
15. For the “army in a lab” quote, see Zelditch (1969). Experiments, it should be noted, are not entirely foreign to sociology. For example, the field of “network exchange” is one area of sociology in which it is common to run lab experiments, but these networks generally comprise only four or five individuals (Cook et al. 1983; Cook et al. 1993). Cooperation studies in behavioral economics, political science, and sociology also use experiments, but once again the groups involved are small (Fehr and Fischbacher 2003).
16. See Salganik, Dodds, and Watts (2006) for a detailed description of the original Music Lab experiment.
17. See Salganik and Watts (2009b; 2009a) for more background on Music Lab, and details of follow-up experiments.
CHAPTER 4: SPECIAL PEOPLE
1. The movie The Social Network, about the founding of Facebook, was released in 2010. The Fosters beer commercial is available at http://www.youtube.com/watch?v=nPgSa9djYU8.
2. For a history of social network analysis, see Freeman (2004). For summaries of the more recent liter
ature on network science, see Newman (2003), Watts (2004), Jackson (2008), and Kleinberg and Easley (2010). For more popular accounts, see Watts (2003) and Christakis and Fowler (2009).
3. See Leskovec and Horvitz (2008) for details of the Microsoft instant messenger network study.
4. See Jacobs (1961, pp. 134–35).
5. Milgram did not invent the phrase “six degrees of separation,” referring only to the “small world problem.” Instead, it was the playwright John Guare who wrote a play with that title in 1990. Oddly, Guare has credited the origin of the phrase to Guglielmo Marconi, the Italian inventor and developer of radiotelegraphy, who reportedly said that in a world connected by the telegraph, everyone would be connected to everyone else via only six degrees of separation. According to numerous citations on the web (see, e.g. http://www.megastarmedia.us/mediawiki/index.php/Six_degrees_of_separation), Marconi is supposed to have made this claim during his Nobel Prize lecture in 1909. Unfortunately, the speech itself (http://nobelprize.org/nobel_prizes/physics/laureates/1909/marconi-lecture.html) makes no mention of the concept; nor have I been able to locate the source of Marconi’s quote anywhere else. Regardless of the ultimate origin of the phrase, however Milgram deserves the credit for having been the first to put some evidence behind it.
6. As a number of critics have noted, Milgram’s results were less conclusive than they have sometimes been portrayed (Kleinfeld 2002). In particular, of the three hundred chains that started out to reach the target, a third began in Boston itself, and another third began with individuals in Omaha who were investors in the stock market—which at the time would have required them to have access to a stockbroker. Seeing as the sole target of the experiment was a Boston stockbroker, it is not so surprising anymore that these chains could reach him. Thus the most compelling evidence for the small-world hypothesis came from the ninety-six chains that began with randomly selected people in Omaha, and only seventeen of these chains actually made it. Given these uncertainties, one has to be careful when placing too much weight on the role of people like Mr. Jacobs, who could easily have been a statistical fluke. Indeed, Milgram himself noted as much, claiming only that “the convergence of communication chains through common individuals is an important feature of small world nets, and it should be accounted for theoretically.”
Everything Is Obvious Page 30