Philosophy of Irrationality Research Paper

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1. The Aristotelian Tradition Vs. The Heuristics And Biases Program

There is a philosophical tradition, reaching at least as far back as Aristotle, which maintains that man is a rational animal. According to this Aristotelian traditional, human beings are intrinsically rational, though of course even the most ardent defender of this view would admit that people’s decisions and thought processes are sometimes very irrational indeed. When people are tired, or drunk, or in the grip of rage, they can think and act in ways that no account of rationality would condone. To accommodate this obvious fact, contemporary defenders of human rationality often appeal to a distinction between competence and performance similar to the one invoked by contemporary linguists (Chomsky 1965, Samuels et al. 1999). The claim that human beings are rational is interpreted to mean that normal humans posses a rational reasoning competence—a tacit knowledge of normatively appropriate principles for reasoning and decision-making. Under ordinary circumstances these principles are reflected in people’s thinking and their actions, though sometimes, for various reasons, our performance can fail to reflect this underlying rational competence.

In the early 1970s, however, Amos Tversky, Daniel Kahneman, and a number of other psychologists began reporting findings suggesting that the Aristotelian view of human rationality is seriously mistaken. What these studies demonstrated is that even under quite ordinary circumstances where fatigue, drugs, and strong emotions are not factors, people reason and make decisions in ways that appear systematically to violate familiar canons of rationality on a broad array of problems. Those first surprising studies sparked the growth of an enormously influential research program whose impact has been felt in a wide range of disciplines including psychology, economics, political theory, and medicine. The expression ‘heuristics and biases’ is often used as a label for this tradition, since it holds that much of our reasoning and decision-making relies on heuristics and biases rather than rational principles.

In the sections that follow we will offer some examples of the sort of experimental findings that many have interpreted as showing that the reasoning and decision-making competence of normal humans is far from rational. (For more comprehensive reviews of the literature see Dawes 1988 and Baron 1994.) But first we need to say what standards of rationality are being applied by those who think the experimental findings demonstrate widespread irrationality. Though writers in the Heuristics and Biases tradition rarely offer an explicit and general theory of rationality, the most plausible reading of their work is that they are assuming some version of what Edward Stein (1996) calls the ‘standard picture’. On this view, to be rational is to reason and make decisions in accordance with principles that are based on the rules of logic, probability theory, and decision theory. Sometimes, of course, it is far from clear how these theories are to be applied—a problem that we will return to in Sect. 4. For the moment, however, we will follow the lead of those who work in the Heuristics and Biases tradition and assume that the irrationality manifested in the experiments we describe is intuitively obvious.

2. Irrationality In Reasoning

2.1 The Conjunction Fallacy

In what has become perhaps the most famous experiment in the Heuristics and Biases tradition, Tversky and Kahneman (1982) presented people with the following task.

Linda is 31 years old, single, outspoken, and very bright. She majored in philosophy. As a student, she was deeply concerned with issues of discrimination and social justice, and also participated in antinuclear demonstrations.

Please rank the following statements by their probability, using 1 for the most probable and 8 for the least probable.

(a) Linda is a teacher in elementary school.

(b) Linda works in a bookstore and takes Yoga classes.

(c) Linda is active in the feminist movement.

(d) Linda is a psychiatric social worker.

(e) Linda is a member of the League of Women Voters.

(f) Linda is a bank teller.

(g) Linda is an insurance sales person.

(h) Linda is a bank teller and is active in the feminist movement.

In a group of naive subjects with no background in probability and statistics, 89 percent judged that statement (h) was more probable than statement (f ) despite the obvious fact that one cannot be a feminist bank teller unless one is a bank teller. When the same question was presented to statistically sophisticated subjects—graduate students in the decision science program of the Stanford Business School—85 percent made the same judgment! Results of this sort, in which subjects judge that a compound event or state of affairs is more probable than one of the components of the compound, have been found repeatedly since Tversky and Kahneman’s pioneering studies, and they are remarkably robust. This pattern of reasoning has been labeled ‘the conjunction fallacy.’

2.2 Base Rate Neglect

On the familiar Bayesian account, the probability of a hypothesis on a given body of evidence depends, in part, on the prior probability of the hypothesis. However, in a series of experiments, Kahneman and Tversky (1973) showed that subjects often seriously undervalue the importance of prior probabilities. One of these experiments presented half of the subjects with the following ‘cover story.’

A panel of psychologists have interviewed and administered personality tests to 30 engineers and 70 lawyers, all successful in their respective fields. On the basis of this information, thumbnail descriptions of the 30 engineers and 70 lawyers have been written. You will find on your forms five descriptions, chosen at random from the 100 available descriptions. For each description, please indicate your probability that the person described is an engineer, on a scale from 0 to 100.

The other half of the subjects were presented with the same text, except the ‘base-rates’ were reversed. They were told that the personality tests had been administered to 70 engineers and 30 lawyers. Some of the descriptions that were provided were designed to be compatible with the subjects’ stereotypes of engineers, though not with their stereotypes of lawyers. Others were designed to fit the lawyer stereotype, but not the engineer stereotype. And one was intended to be quite neutral, giving subjects no information at all that would be of use in making their decision. Here are two examples, the first intended to sound like an engineer, the second intended to sound neutral:

Jack is a 45-year-old man. He is married and has four children. He is generally conservative, careful, and ambitious. He shows no interest in political and social issues and spends most of his free time on his many hobbies which include home carpentry, sailing, and mathematical puzzles.

Dick is a 30-year-old man. He is married with no children. A man of high ability and high motivation, he promises to be quite successful in his field. He is well liked by his colleagues.

As expected, subjects in both groups thought that the probability that Jack is an engineer is quite high. Moreover, in what seems to be a clear violation of Bayesian principles, the difference in cover stories between the two groups of subjects had almost no effect at all. The neglect of base-rate information was even more striking in the case of Dick. That description was constructed to be totally uninformative with regard to Dick’s profession. Thus the only useful information that subjects had was the base-rate information provided in the cover story. But that information was entirely ignored. The median probability estimate in both groups of subjects was 50 percent.

Before leaving the topic of base-rate neglect, we want to offer one further example illustrating the way in which the phenomenon might well have serious practical consequences. Here is a problem that Casscells et al. (1978) presented to a group of faculty, staff, and fourth-year students at Harvard Medical School.

If a test to detect a disease whose prevalence is 1/1,000 has a false positive rate of 5 percent, what is the chance that a person found to have a positive result actually has the disease, assuming that you know nothing about the person’s symptoms or signs?- percent.

Under the most plausible interpretation of the problem, the correct Bayesian answer is 2 percent. But only 18 percent of the Harvard audience gave an answer close to 2 percent. Forty-five percent of this distinguished group completely ignored the base-rate information and said that the answer was 95 percent.

3. Irrationality In Decision-Making

3.1 Framing

In a study that is widely believed to illustrate a deeply irrational feature of human decision-making, Tversky and Kahneman (1981) presented a group of subjects with the following problem:

Imagine that the US is preparing for the outbreak of an unusual Asian disease, which is expected to kill 600 people. Two alternative programs to combat the disease have been proposed. Assume that the exact scientific estimate of the consequences of the programs are as follows:

If Program A is adopted, 200 people will be saved.

If Program B is adopted, there is a 1/3 probability that 600 people will be saved, and a 2/3 probability that no people will be saved.

A second group of subjects was given an identical problem, except that the programs were described as follows:

If Program C is adopted, 400 people will die.

If Program D is adopted, there is a 1/3 probability that nobody will die and a 2/3 probability that 600 people will die.

On the first version of the problem most subjects chose Program A. But on the second version most chose Program D, despite the fact that the outcome described in A is identical to the one described in C.

3.2 The Ultimatum Game

Consider a game that works as follows: There are two players, an ‘Allocator’ and a ‘Recipient’ whose identities are unknown to each other. At the beginning of the game the Allocator is given a sum of money (say $10) and asked to divide it between himself and the other player. The only restriction is that the Allocator must offer something. So, if the smallest unit of money available is $1, then the Allocator must offer at least this much to the Recipient. Once the Allocator has divided the money, the Recipient gets to decide whether to accept or reject the amount offered. If the Recipient accepts, each player gets to keep the sum specified by the Allocator. If the Recipient rejects the offer, then both players receive nothing. The game is not repeated, and the players know from the outset that they will play only once.

On one widely accepted analysis of the problem, it is never rational for a Recipient to reject an offer, since it is better to get some money rather than none. If this is right, then it is always rational for the Allocator to offer the Recipient the smallest amount of money possible, since rational Recipients will always accept the offer, and this will maximize the amount of money the Allocator receives. However, people who have played the game rarely make these choices. Indeed, in many studies the modal offer is to divide the money equally. Moreover, Recipients frequently reject offers of less than 25 percent of the total, preferring instead to go home empty-handed. (For an overview of the literature see Thaler 1992.)

4. ‘Bleak Implications’, Or ‘Ecological Rationality’?

The results we’ve sketched are just a tiny sample of an enormous and growing literature on human reasoning and decision-making. But what conclusions about human rationality—and irrationality—should we draw from these findings? On this question opinions are sharply divided. In one often quoted comment, two leading investigators in the Heuristics and Biases tradition claimed that the experimental results have ‘bleak implications’ for human rationality (Nisbett and Borgida 1975). Other researchers have concluded that ‘individuals are generally affected by systematic deviations from rationality’ (Bazerman and Neale 1986). Still others have suggested that the fault may be in our genes, or at least in our evolutionary history— ‘that people lack the correct programs for many important judgmental tasks … [because we] … have not had the opportunity to evolve an intellect capable of dealing conceptually with uncertainty’ (Slovic et al. 1976). But many other theorists have argued that conclusions like these are unwarranted. In what follows we discuss two of the more important kinds of argument proposed by those who reject the bleak implications view. (For an extended review of the debate see Samuels et al. 2001.)

4.1 Problems With Specific Experiments

There is a substantial literature arguing that one or another experiment in the Heuristics and Biases tradition is flawed and thus does not really demonstrate that the subjects’ performance is irrational. Some of the putative flaws are methodological. One charge that obviously has some merit is that it is often less than clear that the subjects understand the problem in the way that the experimenters want them to. For example, principles of conversational implicature might lead subjects in the ‘feminist bank teller’ experiment to assume that choice (f ) (Linda is a bank teller) means that she is a bank teller who is not active in the feminist movement (Schwarz 1996). Other putative flaws turn on the way that the experimenters propose to apply the normative principles to particular problems. For instance, Gigerenzer (2000) argues that there are typically several different ways in which the principles of statistics and probability can be applied to a given problem and that these different analyses of the problem lead to different answers—or in some cases to no answer at all. If this is correct, then obviously we cannot conclude that subjects are being irrational simply because they do not give the answer that the experimenters prefer. Similarly, it has been urged that it is far from clear that a rational Recipient in the Ultimatum Game ought to accept all offers.

4.2 Darwinian Problems

A second response to the claim that the human mind is prone to ‘systematic deviations from rationality’ comes from recent work by evolutionary psychologists. These theorists argue that the ability to use probabilistic information effectively would have been highly advantageous to our hominid forebears, and therefore, they maintain, it would be surprising if we had not evolved ‘an intellect capable of dealing conceptually with uncertainty.’ But, the evolutionary psychologists continue, we should expect this capacity to manifest itself most clearly when probabilistic information is presented in a format that would have been common in ancestral environments. In these environments, probabilistic information would almost invariably have been presented in the form of information about frequencies as opposed to single events. Thus, evolutionary psychologists argue, we should expect people to do much better on probabilistic reasoning tasks if the problems are presented in a frequency format. It appears that they do. In the ‘feminist bank teller’ problem, for example, if the description of Linda is followed by a question like the one below, the number of subjects who commit the conjunction fallacy drops from over 90 percent to only about 10 percent.

There are 100 people who fit the description above. How many of them are:

…

(f ) bank tellers?

…

(h) bank tellers and active in the feminist movement?

…

Further evidence comes from Cosmides and Tooby’s (1996) systematic exploration of the ‘Harvard Medical School problem’ discussed in Sect. 2.2. They showed that subjects find it much easier to use base rate information rationally on ‘frequentist’ versions of the problem, like the one that follows.

1 out of every 1,000 Americans has disease X. A test has been developed to detect when a person has disease X. Every time the test is given to a person who has the disease, the test comes out positive. But sometimes the test also comes out positive when it is given to a person who is completely healthy. Specifically, out of every 1,000 people who are perfectly healthy, 50 of them test positive for the disease.

Imagine that we have assembled a random sample of 1,000 Americans. They were selected by lottery. Those who conducted the lottery had no information about the health status of any of these people.

Given the information above:

on average,

How many people who test positive for the disease will actually have the disease? out of .

On this version of the problem, 76 percent of subjects—as opposed to the mere 18 percent in Casscells et al.’s original study—gave the correct Bayesian answer.

In light of findings like these, evolutionary psychologists have introduced a notion of ‘ecological rationality’ (Gigerenzer et al. 1999). An inferential or judgmental strategy is ecologically rational if it is both accurate and efficient on the sorts of tasks that were important in the environments in which we evolved. If we interpret Aristotle’s thesis as the claim that man is an ecologically rational animal, evolutionary psychologists maintain that there is a growing body of evidence indicating that he was right.

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