But what if it did? It is an interestingly open question, for example, whether race and social class differences on measures of rationality would be found to be as large as those displayed on intelligence tests. Suggestively, Robert Sternberg finds that race and class differences on measures of practical intelligence (the aspect of his broad view of intelligence that is closest to rationality) are less than they are on IQ tests.21 The framework that I have outlined would at least predict that rankings of individuals on assessments of rational thinking would be different from rankings on intelligence. The reason is that rationality involves thinking dispositions of the reflective mind not assessed on intelligence tests.
Indeed, perhaps assessing rationality more explicitly is what is needed in order both to draw more attention toward rational thinking skills and to highlight the limitations of what intelligence tests assess. At present, of course, there is no IQ-type test for rationality—that is, a test of one’s RQ (rationality quotient). But it may be that it would at least help the debate to start talking about such a thing. I am not saying that an RQ test could be constructed tomorrow. Such instruments are not constructed on the back of an envelope. It would of course take an ETS-like effort costing millions of dollars. But the point is that, practically, in terms of the cognitive technology now in place, it is doable. Only issues of demand and cost prevent it.
Rather than debate the logistics of such an endeavor, the main point I wish to emphasize here is that there is nothing conceptually or theoretically preventing us from developing such a test. We know the types of thinking processes that would be assessed in such an instrument, and we have in hand prototypes of the kinds of tasks that would be used in the domains of both instrumental rationality and epistemic rationality. There is no limitation on constructing an RQ test that comes from the technology of ability assessment surrounding rational thought.22 Nor is there a conceptual limitation.
In this book, I have discussed several ways that cognitive scientists test both epistemic rationality and instrumental rationality. There are many more such tests described in the references that I have cited, but that I have not discussed here for a variety of reasons (most often because the task involved was technical, difficult to explain, or somewhat redundant with examples I have given). This book provides a selective survey, not an exhaustive handbook of rational thinking tasks. Nevertheless, I have been able to show how psychologists study aspects of epistemic rationality and irrationality, such as: the tendency to show incoherent probability assessments; the tendency toward overconfidence in knowledge judgments; the tendency to ignore base rates; the tendency not to seek to falsify hypotheses; the tendency to try to explain chance events; the tendency toward self-serving personal judgments; the tendency to evaluate evidence with a myside bias; and the tendency to ignore the alternative hypothesis.
Additionally, I have been able to show how psychologists study aspects of instrumental rationality and irrationality, such as: the ability to display disjunctive reasoning in decision making; the tendency to show inconsistent preferences because of framing effects; the tendency to show a default bias; the tendency to substitute affect for difficult evaluations; the tendency to over-weight short-term rewards at the expense of long-term well-being; the tendency to have choices affected by vivid stimuli; and the tendency for decisions to be affected by irrelevant context.
Finally, there are numerous examples of our knowledge of rational and irrational thinking being used to help people live fuller lives. In studies cited in this book, it has been shown that:
• Psychologists have found ways of presenting statistical information so that we can make more rational decisions related to medical matters and in any situation where statistics are involved.
• Cognitive psychologists have shown that a few simple changes in presenting information in accord with default biases could vastly increase the frequency of organ donations, thus saving thousands of lives.
• Americans annually pay millions of dollars for advice on how to invest their money in the stock market, when following a few simple principles from decision theory would lead to returns on their investments superior to any of this advice. These principles would help people avoid the cognitive biases that lead them to reduce their returns—overreacting to chance events, overconfidence, wishful thinking, hindsight bias, misunderstanding of probability.
• Decision scientists have found that people are extremely poor at assessing environmental risks. This is mainly because vividness biases dominate people’s judgment to an inordinate extent. People could improve, and this would make a huge difference because these poor assessments come to affect public policy (causing policy makers to implement policy A, which saves one life for each $3.2 million spent, instead of policy B, which would have saved one life for every $220,000 spent, for example).
• Psychologists from various specialty areas are beginning to pinpoint the cognitive illusions that sustain pathological gambling behavior—pseudodiagnosticity, belief perseverance, over-reacting to chance events, cognitive impulsivity, misunderstanding of probability—behavior that destroys thousands of lives each year.
• Cognitive psychologists have studied the overconfidence effect in human judgment—that people miscalibrate their future performance, usually by making overoptimistic predictions. Psychologists have studied ways to help people avoid these problems in self-monitoring, making it easier for people to plan for the future (overconfident people get more unpleasant surprises).
• Social psychological research has found that controlling the explosion of choices in our lives is one of the keys to happiness—that constraining choice often makes people happier.
• Simple changes in the way pension plans are organized and administered could make retirement more comfortable for millions of people.
• Probabilistic reasoning is perhaps the most studied topic in the decision-making field, and many of the cognitive reforms that have been examined—for example, eliminating base-rate neglect—could improve practices in courtrooms, where poor thinking about probabilities has been shown to impede justice.
These are just a small sampling of the teachable reasoning strategies and environmental fixes that could make a difference in people’s lives, and they are more related to rationality than intelligence. They are examples of the types of outcomes that would result if we all became more rational thinkers and decision makers. They are the types of outcomes that would be multiplied if schools, businesses, and government focused on the parts of cognition that intelligence tests miss. Instead, we continue to pay far more attention to intelligence than to rational thinking. It is as if intelligence has become totemic in our culture, and we choose to pursue it rather than the reasoning strategies that could transform our world.
NOTES
1 Inside George W. Bush’s Mind
1. On George W. Bush’s IQ, see: Simonton (2006); Immelman (2001); Sailer (2004); Kessler (2004, pp. 23–28); http://www.sq.4mg.com/Presidents.htm (retrieved July 16, 2007).
2. On the SAT as a measure of general intelligence, see Frey and Detterman (2004), Lemann (1999), and Unsworth and Engle (2007).
3. The NFL gives quarterbacks the Wonderlic Test (Wonderlic Personnel Test, 2002).
4. On the changes in the incidence of various disabilities and their causes see Barbaresi, Katusic, Colligan, Weaver, and Jacobsen (2005); Friend (2005); Gernsbacher, Dawson, and Goldsmith (2005); Gordon, Lewandowski, and Keiser (1999); Kelman and Lester (1997); and Parsell (2004).
2 Dysrationalia
1. See Sternberg (2002a) and Perkins (1995, 2002).
2. On intelligence as adaptation, there are many different discussions (see Matthews, Zeidner, and Roberts, 2002; Neisser et al., 1996; Sternberg, 2000b; Sternberg and Detterman, 1986). The distinction between broad and narrow theories of intelligence is also discussed in a variety of sources (Baron, 1985; Gardner, 1983, 1999; 2006a, 2006b; Perkins, 1995, 2002; Sternberg, 1997a, 1997b, 2000b, 2003b; Sternberg and Detterman, 1986;
Sternberg and Kaufman, 1998; Visser, Ashton, and Vernon, 2006).
3. An important caveat is that the behavioral phenomenon that folk psychology marks as surprising is not a single, isolated instance of injudicious behavior, but when ostensibly smart people repeatedly act injudiciously.
4. The theory of fluid and crystallized intelligence has generated a substantial literature (carroll, 1993; Cattell, 1963, 1998; Daniel, 2000; Geary, 2005; Horn and cattell, 1967; horn and Noll, 1997; Kaufman, 2001; McGrew, 1997; McGrew and Woodcock, 2001; Taub and McGrew, 2004). On fluid intelligence in particular see Kane and Engle (2002) and Unsworth and Engle (2005). Some theories define a general factor (g) from the nonzero correlation between Gf and Gc (see Carroll, 1993). This factor may result from the investment of fluid intelligence in the acquisition of knowledge, as in Cattell’s (1971) investment theory (see Ackerman and Kanfer, 2004; Hambrick, 2003). On intelligence-as-process and intelligence-as-knowledge, see Ackerman (1996).
5. Sternberg has conducted numerous studies of folk theories of intelligence (Sternberg, 2000b; Sternberg, Conway, Ketron, and Bernstein, 1981; Sternberg and Grigorenko, 2004; see also Cornelius, Kenny, and Caspi, 1989).
6. There is an extensive empirical literature in cognitive science on people’s tendencies to think rationally (see Baron, 2000; Camerer, Loewenstein, and Rabin, 2004; Evans, 2002a, 2002b, 2004, 2007; Evans and Over, 1996; Gilovich, Griffin, and Kahneman, 2002; Johnson-Laird, 2006; Kahneman, 2003a, 2003b; Kahneman and Tversky, 2000; Koehler and Harvey, 2004; LeBoeuf and Shafir, 2005; Loewenstein, Read, and Baumeister, 2003; Manktelow and Chung, 2004; Nickerson, 2004; Samuels and stich, 2004; shafir and LeBoeuf 2002; Stanovich, 1999, 2004; Stanovich and West, 1998c, 1999, 2000, 2008a, 2008b).
7. The technicalities of the axioms of expected utility theory are beyond our scope here (see Allingham, 2002; Dawes, 1998; Edwards, 1954; Jeffrey, 1983; Luce and Raiffa, 1957; Savage, 1954; von Neumann and Morgenstern, 1944; Wu, Zhang, and Gonzalez, 2004). Suffice it to say that when people’s choices follow certain patterns (the so-called axioms of choice—things like transitivity and freedom from certain kinds of context effects), then they are behaving as if they are maximizing utility.
8. Epistemic rationality is sometimes called theoretical rationality or evidential rationality (see Audi, 1993, 2001; Foley, 1987; Harman, 1995; Manktelow, 2004). On instrumental and epistemic rationality, see Manktelow (2004), Mele and Rawling (2004), Millgram (2001), and Over (2004).
9. For my earliest discussion of dysrationalia, see Stanovich (1993a, 1994a). The discrepancy notion is also at work in definitions that excluded from the learning disability classification children of low intelligence (e.g., the landmark Education for All Handicapped Children Act [PL 94–142]; the National Joint Committee on Learning Disabilities, Hammill, 1990). It is now known that the whole notion of discrepancy measurement in the domain of reading disability was a mistake (Fletcher et al., 1994; Stanovich, 2000, 2005; Stanovich and Siegel, 1994; Stuebing et al., 2002; Vellutino et al., 2004). The proximal cause of most cases of reading difficulty—problems in phonological processing—is the same for individuals of high and low IQ (Stanovich, 2000; Vellutino et al., 2004). Phonological processing is only modestly correlated with intelligence, so that cases of reading difficulty in the face of high IQ are in no way surprising and do not need a special explanation.
3 The Reflective Mind, the Algorithmic Mind, and the Autonomous Mind
1. The consensus on the basic issues surrounding intelligence, particularly fluid intelligence, is a discernible trend in the literature on cognitive abilities (Bouchard, 2004; Carroll, 1993; Deary, 2001; Engle et al., 1999; Flynn, 2007; Geary, 2005; Lubinski, 2004; Neisser et al., 1996; Plomin and Spinath, 2004; Sternberg, 2000a; Unsworth and Engle, 2005).
2. Schmidt and Hunter (1992, 1998, 2004) have done the most sustained and comprehensive research on this issue (see also Deary et al., 2004; Geary, 2005; Kuncel, Hezlett, and Ones, 2004; Ones, Viswesvaran, and Dilchert, 2005).
3. For over two decades Jonathan Evans has contributed to dual-process theory, and his work has influenced my approach considerably (Evans, 1984, 1989, 2003, 2004, 2006a, 2006b, 2008a, 2008b; Evans and Over, 1996, 2004; Evans and Wason, 1976). A dual-process view was implicit within the early writings in the groundbreaking heuristics and biases research program (Kahneman, 2000, 2003a; Kahneman and Frederick, 2002, 2005; Kahneman and Tversky, 1982a, 1996; Tversky and Kahneman, 1974, 1983). Dual-process theories have been developed in numerous subfields within psychology (Brainerd and Reyna, 2001; Epstein, 1994; Feldman Barrett, Tugade, and Engle, 2004; Haidt, 2001; Johnson-Laird, 1983; Metcalfe and Mischel, 1999; Sloman, 1996, 2002; Smith and Decoster, 2000; Stanovich, 1999; Stanovich and West, 2000). A list of over 23 dual-process models is presented in a table in Stanovich (2004). The details and terminology of the various dual-process theories differ, but they all share a family resemblance. Neurophysiological work supporting a dual-process conception continues to grow (Bechara, 2005; Demartino, Kumaran, Seymour and Dolan, 2006; Goel and Dolan, 2003; Greene, Nystrom, Engell, Darley, and Cohen, 2004; Lieberman, 2003; McClure, Laibson, Loewenstein and Cohen, 2004; Prado and Noveck, 2007; Westen, Blagov, Kilts, and Hamann, 2006).
4. There has been much research on each of the different kinds of Type 1 processing (e.g., Atran, 1998; Buss, 2005; Evans, 2003, 2006a; Fodor, 1983; Lieberman, 2000, 2003; Ohman and Mineka, 2001; Pinker, 1997; Smith, Patalino, and Jonides, 1998; Willingham, 1998, 1999). Type 1 processes conjoin the properties of automaticity, quasi-modularity, and heuristic processing as these constructs have been variously discussed in cognitive science (e.g., Bargh and Chartrand, 1999; Barrett and Kurzban, 2006; Carruthers, 2006; Coltheart, 1999; Evans, 1984, 2006b, 2008a, 2008b; Samuels, 2005, 2008; Shiffrin and Schneider, 1977; Sperber, 1994). See Wilson (2002) on the adaptive unconscious.
5. E.g., dempster and Corkill (1999); Hasher, Lustig, and Zacks (2007); Miyake et al. (2000); Zelazo (2004).
6. Hypothetical reasoning and cognitive simulation are central topics in cognitive science (see Barrett, Henzi, and Dunbar, 2003; Buckner and Carroll, 2007; Byrne, 2005; Currie and Ravenscroft, 2002; Decety and Grezes, 2006; Dougherty, Gettys, and Thomas, 1997; Evans, 2007; Evans and Over, 2004; Kahneman and Tversky, 1982b; nichols and Stich, 2003; Oatley, 1999; Roese, 1997; Sterelny, 2001; Suddendorf and Corballis, 2007; Suddendorf and Whiten, 2001).
7. Leslie’s (1987) model can best be understood by adopting the primary/secondary terminology later used by Perner (1991), and I have done so here. Subsequent to Leslie (1987), cognitive decoupling has been discussed in related and somewhat differing ways by a large number of different investigators coming from a variety of different perspectives, not limited to: developmental psychology, evolutionary psychology, artificial intelligence, and philosophy of mind (Atance and o’Neill, 2001; Carruthers, 2000, 2002; Clark and Karmiloff-Smith, 1993; Corballis, 2003; Cosmides and Tooby, 2000; Dennett, 1984; Dienes and Perner, 1999; Evans and Over, 1999; Jackendoff, 1996; Lillard, 2001; Perner, 1991, 1998; Sperber, 2000; Sterelny, 2001; Suddendorf, 1999; Suddendorf and Whiten, 2001; Tomasello, 1999). See Glenberg (1997) on the difficulty of decoupling and Nichols and Stich (2003) on the “possible world box.”.
8. These domains do indeed show greatly restricted variance among people (e.g., Anderson, 2005; Baron-Cohen, 1995; Reber, 1992, 1993; Reber, Walkenfeld, and Hernstadt, 1991; Saffran, Aslin, and newport, 1996; vinter and Detable, 2003; Vinter and Perruchet, 2000; Zacks, Hasher, and Sanft, 1982); however, this not just true of the Darwinian modules. It can be equally true of processes that have become highly overlearned with practice. Ackerman (1988) has demonstrated how the correlation with intelligence drops as a task becomes more thoroughly learned.
9. There may be a few select domains such as behavioral prediction (so-called theory of mind) in which decoupling is not so cognitively demanding because it has been built in by evolution. The speculation that the raw ability to sustain mental simulations while keeping the relevant representations decoupled is
likely the key aspect of the brain’s computational power that is being assessed by measures of fluid intelligence (see Stanovich, 2001a, 2004) is suggested because the correlation between fluid intelligence and executive functioning is substantial (Baddeley, 1992; Baddeley, chincotta, and Adlam, 2001; Duncan, et al., 2000; Fuster, 1990; Gernsbacher and Faust, 1991; Goldman-Rakic, 1992; Gray, Chabris, and Braver, 2003; Hasher, Zacks, and May, 1999; Kane, 2003; Kane and Engle, 2002; Salthouse, Atkinson, and Berish, 2003), as is the correlation between intelligence and working memory (Colom, Rebollo, Palacios, Juan-Espinosa, and Kyllonen, 2004; Conway, Cowan, Bunting, Therriault, and Minkoff, 2002; Conway, Kane, and Engle, 2003; Engle, 2002; Engle, Tuholski, Laughlin, and Conway, 1999; Geary, 2005; Kane, Bleckley, Conway, and Engle, 2001; Kane and Engle, 2003; Kane, Hambrick, and Conway, 2005; Kane, Hambrick, Tuholski, Wilhelm, Payne, and Engle, 2004; Lepine, Barrouillet, and Camos, 2005; Sub, Oberauer, Wittmann, Wilhelm, and Schulze, 2002).
10. My view of individual differences in cognitive decoupling as the key operation assessed by measures of fluid intelligence was anticipated by Thurstone (1927), who also stressed the idea that intelligence was related to inhibition of automatic responses: “Intelligence is therefore the capacity of abstraction, which is an inhibitory process. In the intelligent moment the impulse is inhibited while it is still only partially specified, while it is still only loosely organized. . . . The trial-and-error choice and elimination, in intelligent conduct, is carried out with alternatives that are so incomplete and so loosely organized that they point only toward types of behaviour without specifying the behaviour in detail” (p. 159).
11. On levels of analysis in cognitive science, see Anderson (1990, 1991), Bermudez (2001), Dennett (1978, 1987), Levelt (1995), Marr (1982), Newell (1982, 1990), Oaksford and Chater (1995), Pollock (1995), Pylyshyn (1984), Sloman (1993), Sloman and Chrisley (2003), and Sterelny (1990). The terms for the levels of analysis are diverse. For a discussion of this and the arguments behind my choice of the term algorithmic, see Stanovich (1999, 2004).
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