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Brooklyn Law SchoolBrooklynWorksFaculty Scholarship2007A Liberal Challenge to Behavioral Economics: TheCase of ProbabilityAlex SteinBrooklyn Law SchoolFollow this and additional works at: https://brooklynworks.brooklaw.edu/facultyPart of the Other Law CommonsThis Article is brought to you for free and open access by BrooklynWorks. It has been accepted for inclusion in Faculty Scholarship by an authorizedadministrator of BrooklynWorks.Recommended Citation2 N.Y.U. J.L. & Liberty 531 (2006-2007)NYU JOURNAL OFLAw & LIBERTYA LIBERAL CHALLENGE TOBEHAVIORAL ECONOMICS: THE CASEOF PROBABILITYALEX STEIN*This paper argues that the Behavioral Economics move-ment (BE for short) needs to be liberally inclusive in formulating thecriteria for rationality against which to evaluate people's cognitiveability and performance. It is illiberal to require that individuals usea single cognitive methodology where more than one sound meth-odology is available. This prescription is appropriate both forevaluating people's probabilistic reasoning and for studying peo-ple's utility valuations. This paper focuses primarily on BE's as-sessment of people's probabilistic performance. Specifically, it ex-amines the famous "Blue Cab" experiment upon which several be-havioral studies have grounded their assessment of an average per-son as "probabilistically challenged."* Visiting Professor of Law, Yale Law School. Professor of Law, Cardozo Law School.LL.B., LL.M. Hebrew University of Jerusalem; Ph.D. University of London. E-mail:alex.stein@yale.edu. Website: www.professoralexstein.com. I thank Samuel Buell,David Carlson, Claire Hill and J.D. Trout for comments and suggestions.NYU Journal of Law & LibertyPart IBE challenges liberalism by questioning its "free agency"assumption that people are generally able to make rational choicesas to what is right for them. This assumption postulates that, by andlarge, people perform reasonably well in maximizing their welfareand in determining facts needed for their decisions. This dual com-petence-economic and epistemic-comes along with two norma-tive implications. First, government must not interfere with peo-ple's choices as to how to go about their lives, except for special rea-sons. If a person's mental capacity is not substantially impaired andhis actions do not externalize harm upon others, the governmentshould leave that person alone. Second, government must not im-pose upon people any rationality criteria for fact-determination.Facts upon which people proceed in their lives should be free fromofficial dogma (an extreme version of which is portrayed by the"Ministry of Truth" in Orwell's dystopial). By the same token-andcoming closely to this paper's specific point-government must notcondition one's designation as a juror in a trial upon any specialintellectual qualifications. To properly function as a juror, a personneed not be a logician, a statistician or a scientist. A lay person canadequately determine what is "beyond all reasonable doubt" andwhich factual allegations are "more probable than not."2BE challenges the "free agency" assumption by empiricaldemonstrations that people systematically err. According to BE,people form value-preferences that are economically irrational andcombine those preferences in ways that reduce their welfare, ratherthan augmenting it.3 They also mishandle fact-finding tasks by1 See GEORGE ORWELL, 1984 7 (1949).2 See L. Jonathan Cohen, Freedom of Proof 16 ARCHIV FOR RECHTS-UNDSOZIALPHILOSOPHIE 1, 21 (1983).3 See, e.g., Christine Jolls, Cass R. Sunstein & Richard Thaler, A Behavioral Approach toLaw and Economics, 50 STAN. L. REV. 1471 (1998); Russell B. Korobkin & Thomas S.Ulen, Law and Behavioral Science: Removing the Rationality Assumption From Law andEconomics, 88 CAL. L. REV. 1051 (2000); Russell B. Korobkin, Bounded Rationality, Stan-dard Form Contracts, and Unconscionability, 70 U. CHI. L. REV. 1203 (2003). See RichardA. Posner, Rational Choice, Behavioral Economics and the Law, 50 STAN. L. REV. 1551[Vol. 2:5312007] A Liberal Challenge to Behavioral Economicsbreaking the most basic rules of probabilistic reasoning.4 These cog-nitive failures are both systematic and harmful. Government, there-fore, ought to step in and do what is right.This, in a nutshell, is BE's challenge to liberalism. Liberal-ism elevates individual autonomy over authority, but an autono-mous person's bounded rationality will bring him down. To pre-vent this downfall, the person clings to his benevolent governmentthat keeps him up. He acts like a medical patient, putting his faithin a doctor's prescription of Prozac without investigating its chem-istry and impact. This person subordinates his reason and deci-sions5 to those that his authority (another person or agency) devel-ops for him. He knows that insubordination is good for his auton-omy-which happens to be an important liberal value-but he alsoknows that this celebration of autonomy would not last for long ifhe really needs Prozac but takes aspirin instead.Part IILiberalism, however, makes an additional point that BEfails to consider seriously. Under liberalism, rationality is multifac-eted and diverse, rather than single-faceted and monistic. Crucial tothe present debate, this pluralist vision originates from uncertaintyrather than toleration. Liberalism does not merely tolerate people'sdiverse viewpoints as to what counts as rational, it also supportsthose viewpoints affirmatively by giving them equal epistemic cre-dentials. Rawls's "overlapping consensus,"6 for example, is notprimarily a method for developing mutual respect among members(1998), for criticism. See BEHAVIORAL LAW AND ECONOMICS (Cass R. Sunstein ed.,2000), for a good collection of essays documenting BE experiments and findings.4 See Amos Tversky & Daniel Kahneman, Judgment under Uncertainty: Heuristics andBiases, 185 SCIENCE 1124 (1974); see also JUDGMENT UNDER UNCERTAINTY: HEURISTICSAND BIASES (Daniel Kahneman, Paul Slovic & Amos Tversky eds., 1982).- See Joseph Raz, Authority and Justification, 14 PHIL. & PUB. AFF. 3 (1985) (developingan account of authority based on preemptive reasons).6 See JOHN RAWLS, POLITICAL LIBERALISM 133-34, 145-53 (expanded ed., 2005).NYU Journal of Law & Libertyof a pluralistic society (which is not a bad thing in itself). Rather, itis a rational preference-maximizing framework of "public reason." 7To have a concrete example from the area of economics,consider the famous "sunk cost" problem. 8 Under the standard eco-nomic model, in estimating the utility of her prospective endeavor,a rational person must look forward, not backward. Specifically, aperson must ignore her "sunk costs." For example, after investingmoney and effort into acting, Jane ought to ignore this investmentin deciding whether to study law and become an attorney. All sheneeds to consider is the difference between her net expected bene-fits from acting and from lawyering. In reality, however, people doaccount for their "sunk costs." According to BE, this "sunk cost fal-lacy" is a paradigmatic example of bounded rationality.9But what if Jane considers her ongoing acting endeavor asimportant to the definition of her life? 10 For her, not abandoning animportant endeavor and not succumbing to temptations of the mo-ment determine what kind of person she is in the larger scheme ofthings.1 This course of action is perfectly rational, although not ra-tional in the narrow economic sense. If the narrow paradigm of ra-tionality fails to account for this action, why treat it as a baseline forassessing people's performance as welfare maximizers? Why con-sider other forms of rationality as inadmissible? Why not adopt, inother words, the inclusive liberal position that perceives rationalityas a complex and multifaceted phenomenon?This, in a nutshell, is a liberal challenge to BE. This chal-lenge has many important implications for designers of social pol-icy. In what follows, I examine these implications in the domain ofprobabilistic reasoning.7 Id. at 150-53, 212-13.8 See, e.g., Hal R. Arkes & Catherine Blumer, The Psychology of Sunk Cost, 35 ORG.BEHAV. & HUMAN DECISION PROCESSES 124, 126-36 (1985).9Id.10 See ROBERT NOZICK, THE NATURE OF RATIONALITY 22 (1993).1 See id. at 23.[Vol. 2:53120071 A Liberal Challenge to Behavioral EconomicsPart IIITo make this discussion manageable, I focus on a singleprobabilistic issue: the famous "Blue Cab" experiment. Accordingto BE, this experiment and its findings provide a paradigmatic ex-ample of people's bounded rationality in probabilistic reasoning.' 2Factfinders considered a car accident that occurred in a cityin which 85% of cabs were Green and the remaining 15% were Blue.The factfinders heard a witness testify that the cab involved in theaccident was Blue, and then accepted as uncontested backgroundfact that the testifying witness correctly identified cabs in 80 out of100 cases. Factfinders participating in that experiment systemati-cally failed to determine the probability of the victim's case againstthe Blue Cab Company. 13 Their typical estimation-80%-coincidedwith the given credibility of the witness, 14 but not with the basicrules of probabilistic calculus, which would take into account therelative frequency of Blue and Green cabs as well. Under theserules, the prior odds attaching to the scenario in which the cab in-volved in the accident was Blue rather than Green-P(B)/P(G)-equaled 0.15/0.85. To calculate the posterior odds-P(B I W) /P(G I W), with W denoting the witness's testimony-theseprior odds had to be multiplied by the likelihood ratio. This ratiohad to be determined by the odds attaching to the scenario in whichthe witness identified the cab's color correctly, rather than incor-rectly: P(W I B)/P(W I G). The posterior odds consequently equaled(0.15x0.8)/(0.85x0.2), that is, 12/17. The probability of the victim'sallegation against the Blue Cab Company thus equaled 12/(17+12),that is, 41%-an outcome that fails to satisfy the preponderance-of-the-evidence standard that applies in civil litigation. This outcometherefore undermined the rationality of the factfinders' decisionthat the victim should prevail. 1512 See Kahneman, Slovic & Tversky, supra note 4, at 156-57.13 Id. at 156-59.14 Id.15 Id.NYU Journal of Law & LibertyThis experiment is faulty in one crucial respect.1 6 The criti-cal datum that the factfinders had to process was unclear. Report-edly, "The court tested the reliability of the witness under the samecircumstances that existed on the night of the accident and con-cluded that the witness correctly identified each one of the two col-ors 80% of the time and failed 20% of the time." 17 But did the courtconsider the prior odds in reaching this conclusion about the wit-ness? Did it calculate, in other words, that "the witness correctlyidentified each one of the two colors 80% of the time and failed 20%of the time" after taking into account the distribution of Blue andGreen cabs in the city? If the court did so, the factfinders' ascriptionof an 80% probability to the victim's case would then be obviouslycorrect. This scenario would exhibit no probabilistic errors and nobounded rationality whatsoever.This scenario, however, may be unduly optimistic. What ifthe court did not consider the prior odds in calculating the probabil-ity of the witness's correctness? Failure to consider these oddsmakes the factfinders' assessment of the probability of the victim'scase defective-but then one should inquire about the reason for nottelling the factfinders about the need to take the prior odds into ac-count. The factfinders processed the witness's 80% credibility asinvariant across all possible cab distributions. They assumed, inother words, that the distribution of Blue and Green cabs in the citywas causally irrelevant to the witness's ability to identify colors cor-rectly.' 8This understanding of the evidence was not irrational. Informal terms, the factfinders assumed that P(B I W)=0.8. The factthat the prior probability-P(B) -was relatively low (0.15) does notmake this assumption irrational, because the likelihood ratio mayhave been estimated as sufficiently high. This ratio may have been16 1 have made this point briefly in ALEX STEIN, FOUNDATIONS OF EVIDENCE LAW 60-63(2005).17 See Kahneman, Slovic & Tversky, supra note 4, at 156.18 See L. Jonathan Cohen, Can Human Irrationality be Experimentally Demonstrated?, 4BEHAV. & BRAIN Sci. 317, 328-29 (1981).[Vol. 2:5312007] A Liberal Challenge to Behavioral Economicshigh enough because, once again, the cab distribution in the citywas causally irrelevant to the credibility of the witness's account. Bethat as it may, bounded rationality was not the factfinders' problem.The problem was the experiment's design.Having said this, I am still ready to assume that the ex-perimenters did have a good reason for not telling the factfindersthat the cab distribution was (somehow) causally relevant to theaccuracy of the witness's account. Perhaps the factfinders were ex-pected to come to this understanding by themselves. The factfindersthen may have decided the case erroneously due to their failure tocome to this understanding. The exact origin of the factfinders' er-ror, however, is still crucial for determining what went wrong intheir decision. The experimenters and their BE followers interpretthis error as a probabilistic miscalculation. They claim that the fact-finders failed to count the base rates in determining the probabilityof correctness that attached to the witness's account. They also ar-gue, quite convincingly, that this cognitive phenomenon is wide-spread. This interpretation, however, is questionable at best becausethe factfinders did not miscalculate any probability. Their mistake (ifthey committed one) was epistemic rather than operational. Themistake was the factfinders' decision to cast away the informationabout cab distribution as causally irrelevant to the witness's accu-racy. Under the irrelevancy assumption, the prior odds of the vic-tim's case were 1/1. But if the cab-distribution was in fact relevantto the accuracy of the witness's account-a possibility that the fact-finders evidently failed to consider-these prior odds could then be0.15/0.85. The posterior probability of the victim's case would con-sequently decline.This understanding is the most that BE can make of the"Blue Cab" experiment. If so, the problem that BE has identified isnot systematic and can be fixed. The "Blue Cab" and similar find-ings are about people's cognitive performance, rather than cognitivecompetence'9-a crucial distinction that BE systematically fails toNYU Journal of Law & Libertyconsider. The point of the distinction is this: people remain cogni-tively competent even when they err. This means that people canavoid errors in probability computations (or other decisions) whenproperly alerted to those errors. Admittedly, people often fall intotraps set by BE experimenters in order to test their rationality. Thesetraps, however, can only function as the conjurer's sleight of hand:each trick can be played only once. As in the teleological paradox, 20the play uncovers and thereby destroys the trick.Part IVAs I said before, the factfinders' "mistake" may not havebeen a mistake after all. The factfinders knew nothing about thecorrelation (let alone the causation) between cab distribution in thecity and the accuracy of cab-identifying witnesses. They thereforehad an epistemological warrant to believe the witness by assessingthe accuracy of his cab identification as 80% probable. This assess-ment was as rational as one that does take the cab distribution intoaccount. The choice between the two approaches depends on howone wants to allocate the risk of error; there is more than one ra-tional way of doing it.21Furthermore, as Jonathan Cohen pointed out, the factfind-ers may have been focusing on the Baconian case-specific probabil-ity.22 That is, they may have been assessing the strength of the evi-dential support for the victim's case-specific allegation that "thiswitness in this particular instance identified the cab's color cor-20 This paradox looms in ethics and economics. Targeting a particular goal (such asesteem or friendship) is sometimes counterproductive to its attainment-a predica-ment that places the goal out of reach. See T. M. SCANLON, WHAT WE OWE TO EACHOTHER 383 n.15 (1998); Zev Trachtenberg, Book Review, 115 ETHICS 809, 810 (2005)(reviewing GEOFFREY BRENNAN & PHILIP PETIT, THE ECONOMY OF ESTEEM: AN ESSAYON CIVIL AND POLITICAL SOCIETY (2004)) (observing that "people who strive for es-teem will be disesteemed on that account.").21 See STEIN, supra note 16, at 40-56; see also id. at 107-40 (arguing that evidence law isgenerally about apportionment of the risk of error).22 See Cohen, supra note 18, at 328-30.[Vol. 2:5312007] A Liberal Challenge to Behavioral Economicsrectly." 23 The experimenters assumed that the factfinders' only goalwas to calculate the witness's chances to have testified correctly.Their frame of reference was Pascalian (aleatory) probability, whichhappens to be one of the two basic modes of probabilistic reasoning.The other mode is Baconian (inductivist) probability. These twomodes are logically distinct from each other. As Jonathan Cohenexplains,Baconian probability-functions . . .deserve a place along-side Pascalian ones in any comprehensive theory of non-demonstrative inference, since Pascalian functions gradeprobabilification on the assumption that all relevant facts arespecified in the evidence, while Baconian ones grade it bythe extent to which all relevant facts are specified in the evi-dence.24The experimenters' choice of the Pascalian mode would have beenabsolutely appropriate had they put the factfinders "on the samepage." The experimenters' failure to do so is another flaw in theirexperiment's design.25Part VBE offers an array of fruitful methodologies for testing therationality of people's reasoning. Consonantly with the liberal tradi-tion, however, BE ought to recognize that people's rationality, in23Id.24 L. Jonathan Cohen, On the Psychology of Prediction: Whose is the Fallacy?, 7COGNITION 385, 389 (1979). For detailed accounts of Baconian probability see L.JONATHAN COHEN, THE PROBABLE AND THE PROVABLE 121-216 (1977); L. JONATHANCOHEN, AN INTRODUCION TO THE PHILOSOPHY OF INDUCTION AND PROBABILITY 4-13,145-75 (1989). For its implications on adjudicative fact-finding and evidence law, seeSTEIN, supra note 16, at 64-106.25 See Cohen, supra note 18, at 325, 330; see also Charles M. Yablon, The Meaning ofProbability Judgments: An Essay on the Use and Misuse of Behavioral Economics, 2004 U.ILL. L. REV. 899 (demonstrating that multiplicity of probability concepts often frus-trates cognitive theories that attribute probabilistic irrationality to lay reasoners).540 NYU Journal of Law & Liberty [Vol. 2:531both economic and epistemic areas, is a complex, dynamic and mul-tifaceted phenomenon. There are many different rationalities, andBE's experimental designs need to take this pluralism into account."Blue Cab" and similar experiments have failed to do so. As a re-sult, these experiments do not prove that people systematically mis-judge probabilities.BE also needs to separate cognitive performance from cog-nitive competence. Cognitive performance depends upon trial anderror and upon the information that people have and do not have.As such, it can be improved through direct learning (as opposed toindirect debiasing techniques that counter cognitive incompetence).Cognitive competence is an immanent human condition that a sim-ple acquisition of information cannot undo. "Blue Cab" and similarexperiments are about cognitive performance, not competence.They do not establish people's cognitive incompetence in the prob-abilistic domain.

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