Lecture 3 - Functional Biases in Social Cognition

Question 1

Temporary Goals

Answer 1

These may influence how risk seeking / risk averse someone is.

Self protection goal -> risk averse
Mate attraction goal -> risk taking

Presence of attractive women found to increase risk-taking behavour in young males (Ronay & von Hippel, 2010).

Question 2

Summary

Answer 2

Humans are not wholly rational creatures.

However rather than being errors, these biases may serve an adaptive function they may be design features rather than design flaws.

Important to understand the “evolution of error” to be able to balance personal, social, political and economic risks (Johnson et al, 2013).

Question 3

Signal Detection

Answer 3

True positive = hit
False positive = false alarm
False negative = miss
True negative = correct rejection

False negatives are generally more costly.

Question 4

Biological example of signal detection

Answer 4

Immune response:

more likely to respond when no pathogen present e.g hay fever, than no responding when a real danger is present e.g. immune dysfunction.

Question 5

Psychological example

Answer 5

Disease detection:

More likely to avoid people who look like they have a disease as it would be more costly to be exposed to a potential pathogen than assume that they are healthy and it is just a cosmetic issue.

Question 6

Smoke Detector Principle

Answer 6

Nesse (2005)

Smoke detectors make many systematic errors (false positives) but they are functional.

It may not be accurate but it is adaptive.

Question 7

Error Management Theory

Answer 7

Haselton & Buss (2000)

When making a decision under uncertainty = risk involved. Have evolved to a bias towards those risks that are least reproductively costly.

In these examples the costliness of the errors depends on your sex. For women it is more costly to have a partner that is uncommitted, for men it is more costly to miss out on an opportunity to reproduce.

Johnson et al (2013) EMT offers a framework for understand decision making under uncertainty.

Question 8

Kin recognition biases

Answer 8

Feeler & Navarette (2004)

FN = failing to detect kin. May be more costly (committing incest).

The costs may be higher for females. Women show greater aversion to incest. Find sex with a friend almost as disgusting, Relevance - women display more false negatives as it is more costly for them to have a disabled child to rear.

Question 9

Committment under-perception bias

Answer 9

Haselton & Buss (2000)

For women it is more costly to conceive a child with a man that is uncommitted. Cyrus et al (2011) - Found that post-menopausal women do not show this bias. Suggest that this is therefore a functional adaptation.

Question 10

Clinical implications of EMT

Answer 10

Tolin et al (2014)

Exaggerated cognitive biases may lead to anxiety disorders.

Question 11

Sexual over-perception bias

Answer 11

Haselton &Buss (2000). Men tend to over-perceive women as expressing sexual interest. Phenomena does not occur with own sister.

Maner et al (2005)
Men primed with mating goals perceived neutral faces of women as being sexually aroused.

Evaluation - not clear whether bias is in behavior or cognition.

Question 12

Hostile intentions

Answer 12

Haselton & Nettle (2006)
FN = failure to detect hostility
FP = assume hostile intentions when not present.

FN more costly so people biased towards seeing anger in hostile faces and assuming conspiracies.

Taken to extremes may account for paranoid personality disorders.

Question 13

Beliefs about one’s own talents

Answer 13

Biased towards believing one is talented when one is not.

May contribute to narcissistic personality disorder.

Question 14

Individual differences

Answer 14

People differ in how risk seeking vs risk averse they are.

Young males are esp biased towards risk taking behavior as they have the most to gain.

Question 15

Definition of bias

Answer 15

Systematic errors in judgement or inference.

Question 16

Descriptive theories / models

Answer 16

Describing and explaining how people actually make decisions and judgments.

Question 17

Normative / prescriptive theories

Answer 17

The optimal way of making judgments - what rational beings would do.

Question 18

Why do we have biases?

Answer 18

Processing of information is energetically expensive. Heuristics act as short-cuts which save time and energy. however, these lead to systematic errors.

However…

Normative theories assume that the main function of cognition is to generate true beliefs. BUT inaccurate beliefs may be more ADAPTIVE

Question 19

Tversky & Kahneman (1974)

Answer 19

First to show that humans are not rational beings and that many decisions and judgments are made quickly and unconsciously via heuristics.

Evaluation:
Supported with neuro evidence - different areas activated during controlled and automatic processes (Lieberman, 2007).

Criticised for using evidence that could support a single-systems approach (Girgerenzer, 2010).

Question 20

2 x 2 matrix

Answer 20

2 correct responses, 2 errors. 1 error is more costly than the other.

E.g. in science we are biased towards making less type I than type II errors are the former are more costly (seeing an effect where there isn’t one).

Question 21

In-group / out-group biases

Answer 21

Just because we are prone to these biases doesn’t mean we have to act on them. They can be overcome through education and culture. We are living in the era of lowest ever prejudice.

Question 22

Representativeness Heuristic

Answer 22

Tversky & Kahneman (1974)

For use with categories - e.g. deciding whether someone is a criminal. Compare individual against a PROTOTYPE of that category.

Question 23

Ignorance of Base Rates

Answer 23

Tversky & Kahneman (1974)

An example of representativeness heuristic.

Rather than making decisions based on base rates and probabilities, people tend to substitute similarity. Kahneman called this WYSIATI (What you see is all there is). When posed with difficult questions we often unconsciously substitute it for as easier one and answer that instead!

Question 24

Conjunction fallacy

Answer 24

An example of representativeness heuristic.

Breaks rules of probability. E.g. “Bill is intelligent but unimaginative!” people more likely to rate him as an accountant who plays jazz for a hobby than just having jazz as a hobby. In reality the probability of the 2 things occurring together is less than one occuring alone but because people are judging Bill on how representative he is of accountants and jazz players they make an error of judgement.

Question 25

Availability Heuristic

Answer 25

Availability = ease with which something can be brought to mind.

AH = using this availability when making decisions.

E.g. violent deaths and accidents are easily remembered and brought to mind so people mistakenly believe they are more likely to die in an air crash than from a stroke, which is one of the biggest causes of death.

Question 26

Criticism of bias reseach

Answer 26

Jussim (2012)

Bias research presents people as low wattage (not that bright, lazy - > irrational conclusions about world). He believes that the data actually shows people as being high-wattage (bright, engaged, energetic => valid conclusions about the world).

Sees biases as only short-lived and weak.

Reviews major contributions to bias literature and believes data supports stereotypes as accurate.

Many studies not replicable (find PLOS one study).

Accuracy studies have received less funding and attention than bias studies.

Evaluation -