evolutionary explanations for ‘irrationality’ leeann breeze

Evolutionary Explanations for ‘Irrationality’Leeann Breeze

“In formal logic, a contradiction is the signal of defeat, but in the evolution of real knowledge it marks the first step in progress toward a victory.”

- -Alfred North Whitehead

EVOLUTIONARY PSYCHOLOGY

& reasoning todayAll humans today carry cognitive traits that served to help our

ancestors survive and reproduce in prehistoric environments.

Today’s world is much DIFFERENT than the worldin which our ancestors lived and evolved…So the traits we observe today may have been valuable in the past, but some no longerserve any evolutionary advantage, given the nature of modern environments

This includes the psychological strategies we have evolved to use…

EVOLUTIONARY PSYCHOLOGY& reasoning today

…THUS NON-NORMATIVE REASONING EXISTS TODAY

Because we evolved cognitive modules that served for efficiency, reproductive/social

success, and environmental safety/typicality in prehistoric contexts

So, where Alfred Whitehead is concerned, the contradiction between Normative and Descriptive theory is a failure for formal logic (which is

hard to argue against) BUT the fact that we evolved to demonstrate this contradiction because of ecologically sound reasoning marks the

success of “the evolution of real knowledge”

HOW IS IRRATIONALITY ADAPTIVE?

LET’S BEGIN DEMONSTRATING THE ECOLOGICAL BENEFIT OF IRRATIONAL

BEHAVIOR AND COGNITIVE PROCESSES BY OUTLINING THE FORCES THAT

GUIDED THE DEVELOPMENT OF HUMAN COGNITIVE TRAITS, ACCORDING TO

EVOLUTIONARY THEORY

PRINCIPLES OF EVOLUTION by Natural Selection, from Darwin1. Traits show variation

2. Some variation is heritable

3. Individuals differ in fitness (the number of offspring they are able to produce)

4. A correlation exists between phenotype and fitness

EVOLUTIONARY INTERPRETATIONS

A trait’s adaptiveness is determined by its frequency in the population of interest

An adaptive phenotype will have an advantage for personal fitness, those who exhibit it will more frequently survive to reproductive age,

and the trait will be inherited by offspring, increasing the trait’s frequency in the

population

EVOLUTIONARY TIMEHumans are biological creatures programmed

by evolution to act, think, feel, and learn in ways that have fostered survival over many

past generations.

Traits we see today exist because they survived challenges of past environments in

which our ancestors lived


& REASONSince cognition is not a physical trait, selection acts upon manifested behaviors that result from cognitive ability or task construal. Evolutionary psychology works on the assumption that cognitive traits we observe today developed as responses to problems our ancestors faced over thousands of years of evolution in prehistoric, savanna-style, hunter-gatherer, societies that relied on social interaction to thrive

EVOLUTIONARY PSYCHOLOGY“Evolved psychological mechanisms are

functional; they function to solve recurrent adaptive problems that confronted our ancestors.”

–David Buss interview in Barker, 2006, pp. 69-70

RATIONALITY & EEA

According to hypotheses that reference the Environment of Evolutionary Adaptiveness(EEA), our mental modules have structures that are better adapted to past environments than the present.

WHERE RATIONALITY IS CONCERNED:

Where do these environmental discrepancies apply?


& RATIONALITYBecause our cognitive modules evolved to serve SURVIVAL AND REPRODUCTION in the highly social, hunter-gatherer, savannah-style EEA, our reasoning abilities today do not appear to fit modern normative theories of logic…resulting in apparent reasoning “errors” defined as mismatching between descriptive and normative models of logic

EVOLUTION and CHANGES

The rapidly changing technological environment in which we live makes these previous adaptations

seem even more out-of-date in their modern context

Because even today, we appear to be designed to more readily respond to tasks with the influence of:

1. Typicality of events & Natural Sampling2. Social Contexts

3. Time/Effort-Saving Heuristicseven when these strategies produce obviously

incorrect responses to modern problems

LET’S REVIEW:

WHAT IS RATIONAL? BARON: anything that helps us achieve

our goals DAWES: rationality is avoidance of self-

contradiction Ascribing to formal (normative) rules of logic

Empirical demonstrations of irrationality

WASON 4-CARD PROBLEM

BAYESIAN INFERENCE

PROBABILITY ESTIMATES

PART I: WASON 4 CARD PROBLEMLeda Cosmides and John ToobyThe Scenario:

GROUP 1: 4 cards are on a tableThere is ONE RULE:

To have a B, there must be 21 or higher on the other side

WASON 4 CARD PROBLEM

GROUP 1: What is the maximum number of cards you must check to be SURE this rule is

satisfied?


GROUP 2: 4 cards are on a tableThere is ONE RULE:

To have a beer a person must be 21 or older


GROUP 1: What is the minimum number of cards you must check to be SURE this rule is

satisfied?


FINDINGS: although the 2 problems have the same logical structure, less than 25 percent of college students can solve the problem for group 1, but roughly 75 percent of college students answer the problem of group 2 correctly

After re-designing the problem to eliminate issues of familiarity, Cosmides and Tooby conclude

that we seem to be predisposed to more easily solve the problems that involve

CHEAT DETECTION

WASON 4 CARD PROBLEM& irrationality

Therefore, people seem to violate Dawe’s definition of rationality by failing to be consistent when the 2 problems have the same logical structure

People also violate the 3rd law of rationality when they are placed with problems like group 1 by failing to follow normative models

WASON 4 CARD PROBLEM& evolutionary theory

Robert Trivers, evolutionary psychologist, has argued that reciprocal altruism is crucial to the social evolution of our species.

Additionally, reciprocity can only be spread if non-reciprocators are punished

WASON 4 CARD PROBLEM& evolutionary theory

In light of Triver’s theory of reciprocal altruism, Cosmides and Tooby interpret their findings as being indicative of an evolved mental capacity for recognizing when some one has cheated by violating a SOCIAL CONTRACT

WASON 4 CARD PROBLEM& cheat detection

Evolutionary strategy holds that individuals are controlled by behaviors that will serve to maximize the success of their OWN genes

THUS THE BEST STRATEGY WOULD BE TO CHEAT (getting all possible gains for oneself & profit from the good nature of others) AND NEVER RECIPROCATE

WASON 4 CARD PROBLEM& reciprocal altruism

THEORY: altruism/reciprocity gene and cheater gene are both FREQUENCY DEPENDENT.

Because if there were too many cheats, competition would override. But, eventually a random mutation for a set of ‘altruist genes’ in the cheater population would begin to have an advantage. Likewise, in an entirely altruist population, the best strategy is to be a cheat. and in a mixed population the best strategy is to be an altruist with cheater-detection, share with other altruists and punish cheats. So cheaters and

alrtuists hold a balance in our population…

WASON 4 CARD PROBLEM& cheat detection

…and in a mixed population the best strategy is to be an altruist with cheater-detection, share with other altruists and punish

cheats.

THUS, WE HAVE EVOLVED TO HAVE PREDISPOSITION TO GIVE THE NORMATIVELY CORRECT ANSWER TO SCENARIOS INVOLVING CHEAT DETECTION. AN

APOLOGIST/EVOLUTIONARY PSYCHOLOGIST WOULD SAY THE REASON FOR THE NON-NORMATIVE RESPONSE TO THE ABSTRACT PROBLEM IS BECAUSE WE HAVE NOT

EVOLVED IN ENVIRONMENTS THAT PROMOTE THE DEVELOPMENT OF THE RIGHT EQUIPMENT TO INTERPRET THE PROBLEM IN A WAY THAT ALLOWS US TO ANSWER IT

CORRECTLY.

PART II: PROBABILITY ESTIMATES


THE LINDA PROBLEMLinda is 31, single, outspoken, and very bright. She

majored in philosophy. As a student, she was deeply concerned with issues of discrimination and social justice, and participated in anti-nuclear and anti-war demonstrations. .What happened to Linda? Rank order the following possible outcomes:(a) Linda failed to graduate from college(b) Linda works as a bank teller(c) Linda works for Green Peace(d) Linda works as a bank teller and is active in the feminist movement


The probability that Linda is a bank teller must be at least as large as the probability that Linda is a bank teller and active in the feminist movement, by shear odds

occurrence of ONE event is much more likely than the combined occurrence of TWO events

PROBABILITY ESTIMATES& The Linda Problem

WHY THE ERROR?

Evolutionarily, people have adapted to assume continuity in the environment. This

seems to have had a consequential effect on the human affinity for narrative.

We adopt a story of Linda from the snippet of info, and continue it in our estimates of

likelihood for her future narrative.

PROBABILITY ESTIMATES& The Linda Problem

This is adaptive because it served to give us appropriate responses to social environments. According to Geoffrey Miller, it is adaptive to assume people are generally consistent, because it serves our “cheat detection” and “trustworthy mate” concepts, helping us to better deem who is a safe reproductive partner—improving our reproductive success.

So, we may not answer the normative answer to the Linda problem, statistically speaking…but, we are answering with the most ecologically-appropriate response. (Panglossian)

PROBABILITY ESTIMATES& percentages vs.

frequenciesPROBLEM 1: You are a gynecologist who conducts breast cancer screening in your region using mammography. The probability that a woman in this region has breast cancer is 1%.If a woman has breast cancer, the probability she tests positive is 80% (sensitivity).If she does not have breast cancer, the probability she tests positive is 9.6% (false positive rate).A woman tests positive. What is the probability that she has breast cancer?


frequenciesPROBLEM 2: You are an experienced physician in a preliterate society. You have no books or surveys, only your accumulated experience. A severe disease is plaguing your people. You have discovered a symptom that signals the disease, but not with certainty. Over the years you have seen many people & most don’t have the disease. Of those who did have the disease, 8 had the symptom. Of those who did not have the disease, 95 had the symptom. Now you meet a patient who has the symptom. What is the chance he has the disease?


frequenciesWhich was easier to solve? IN PROBLEM 2, the solution is simple. Total

people=8+95=103. of that 103, only 8 had the disease—thus the likelihood of a person coming in and having the disease is 8 out of 103=VERY LOW(7.8 percent)

PROBLEM 1: I will go into detail on HOW to solve problem 1 in the next section. For now, know the answer here too is 7.8%, and more math is required.

Physicians who typically solve problem 2 correctly give estimates of problem 1 of roughly 70-80% -- nearly 10 times too high!


frequenciesWhy is the normatively correct answer only intuitive in problem version 2?

The difference between the problems is the use of percentages in version 1 and frequencies in version 2

In fact, Cosmides and Tooby (1996) found that when they converted relevant info from probability to frequency formats in an experiment, their subjects’ performance improved in parallel

SO WHY DID WE ADAPT TO PREFER FLAT RATES INSTEAD OF PERCENTAGES?

PROBABILITY ESTIMATES& percentages

Why frequency preference adaptive?1. Probabilities and percentages were not an everyday

encounter until the 20th century2. Formal percentages began as scientific notation

during the 19th century3. Mathematical probability arose in the mid-17th

century Thus, the Environment of Evolutionary

Adaptiveness didn’t have selection pressures involving these mathematical structures BECAUSE

THEY DID NOT EXIST IN THE EEA.


Instead, the EEA built our probability estimates on naturally occurring phenomena.

Therefore, we base our conclusions on NATURAL SAMPLING– taking census of events in the environment and

judging likelihoods based

on past encounters


Using natural sampling, we set an event counter each time some event occurs. Humans seem to spontaneously count events, and because this is so automatic to us, our cognitive processing is more conducive to problems that suit this type of format.

So, as the apologists say, we are doing the best we can with the equipment we have evolved.

PART III: SOLVING PROBLEM # 1:BAYESIAN INFERENCETo find the normative answer to problem 1, we

need to use BAYESIAN INFERENCE.

This is a formula for using base rates, likelihoods/probabilities of 2 events to come to a final likelihood estimate for one occurrence, given some evidence.

BAYESIAN INFERENCE

Suppose we have two events, C and T, with probabilities P(c) and P(t)There are two conditional probabilities, P(U|K) and P(c|t)We define P(c|t) = P(c)*P(t/c) / P(c)*P(t/c)+

P(not c)*P(t/not c)This tells us how to go from one conditional probability

to the otherIf we know P(c|t), P(c), and P(t), we can calculate P(t|c)

** assume c is the unknown state (a hypothesis that the patient has cancer)t is the known information (i.e., evidence a positive on the mammogram )I.e., we use t to update our probability of c

BAYESIAN INFERENCE

By solving the formula with the given values, we can reason that the probability of cancer is .078=7.8%

BUT THIS IS NOT HOW WE REASON…WHY?- fast and fruegal heuristics are more evolutionarily

adaptive than normative reasoning skills- We haven’t evolved the capacity to be sensitive to

base rates, in the way that we would need to be to if we had intuitive guide towards using bayes’ theorem

BAYES THEOREMwhy fast and frugal

heuristics?Gigerenzer points out that we use our impression of what is representative or what is more familiar to us in order to solve problems, even when that is not going to produce normatively correct responses.

This is because ‘FAST AND FRUGAL HEURISTICS’ are much more effective at dolving real-world problems quickly with minimum information

BAYES’ THEOREMheuristics/evolution

when you look at it from the point of view of evolution, this makes sense. The adaptive value of saving in the EEa time was very high. Using utility theories, Bayes theorem, and doing the math to find the probability of attack from a wild animal given the evidence that you see him approaching quickly, but you are unsure of how long it has been since he has eaten could cost you your life. It is better to use a HEURISTIC—and err on the side of saftey: an over-generalized false positive is much less detrimental in these circumstances than a false negative. So, it is suggested that we have adapted to have less sensitivity to the occurrence of false-negative rates and we hone in on false positives.

BAYES’ THEOREM& base rate neglect

TVERSKY AND KAHNEMAN consider the breast cancer example to include a type of cognitive bias called BASE RATE NEGLECT

In this specific example, the overall rarity of breast cancer is being ignored.

Gigerenzer references back to our bias for frequency data as to why we may neglect base rates: because in the EEA, a concept such as base rates would not have existed. Our minds have evolved algorithms that can only work on the sort of input that would’ve been available in the EEA, so input such as base rates are commonly ignored.

EVOLUTION AND RATIONALITYOur cognitive processes were designed by selection to solve

problems our ancestors faced in the EEACognitive errors arise from rules made based on typicality & natural

sampling that do not fit probability scenarios and contemporary mathematics

Other cognitive errors arise from our predisposition to favor reasoning that promotes sociality, rather than normative logic

Additional problems occur because of our tendency to conserve effort and time by using heuristics

EVOLUTIONARY THEORISTS ACT AS APOLOGISTS CLAIMING THAT ALL OF THESE ERRORS ARE THE RESULT OF

MAKING THE BEST USE OF OUR COGNITIVE CAPACITIES GIVEN OUR LIMITATIONS

EVOLUTION AND RATIONALITY

the end

evolutionary explanations for ‘irrationality’ leeann breeze

Documents

traits frequency

cognitive modules

cognitive processes

cognitive ability

prehistoric environments

evolutionary advantage

normative reasoning

evolutionary explanations