Lecture 9. Judgement, reasoning, decision making

Judgement

• the process of drawing conclusions from encountered evidence

• Sometimes accurate conclusions are drawn from life experience. Other times not

Attribution substitution

• Many judgment begins with a frequency estimate: assess how often a given event occurred in the past, but we don’t have direct access to the frequency data

• Attribution substitution: strategy of relying on easily assessed info as a proxy for needed information

Availability heuristic

• Heuristics are efficient strategies that usually lead to the correct answer

• Availability heuristic: The ease with which examples come to mind is proxy for frequency/likelihood

  • Typically accurate: frequent events or objects are often readily available in memory

• Heuristics can still result in errors

Range of availability effects

• People regularly overestimate the frequency of rare events (e.g. airplane crashes/accidents)

• Rare events are likely to be well-recorded in memory, and thus more available than common events

Representativeness heuristic

• An instance/individual resembles the prototype, or vice versa ⇒ that instance/individual must have the property or the prototype, or vice versa

• Assumption of homogeneity: expecting each individual to be representative of the category

• Likelihood of category membership judged by resemblance

• True to category ⇒ true to individual/instance

Covariation

• Covariation: X and Y “covary” if the presence (or magnitude) of X can be predicted by the presence or magnitude of Y, and vice versa

• It’s like correlation but expanded to include presence/absence

• or -

• Can vary in strength

• If 2 things covary then we start asking if there’s causal relation

• If 2 things covary then we start asking if there’s a causal relation

Illusions of covariation

• Incorrect perceptions that one variable predicts another

  • Astrological signs and personality

  • Social stereotypes

  • Superstitions

• Confirmation bias: tendency to be more alert to evidence that confirms one’s beliefs than to evidence that challenges them

Base rate information

• information about how frequently something usually occurs

  • Neglecting base-rate information can lead to inaccurate estimates of covariation

Diagnostic information

info that may indicate whether an individual belongs to a category

Judgement based on base-rate or diagnostic information

• When only base-rate information is provided, judgments are based on base rate (i.e. no neglect of base rate)

• When base-rate and diagnostic information are provided, judgements are based on diagnostic information

Base-rate neglect

• partly a consequence of attribute substitution

  • Whether someone is a category member ⇒ whether someone resembles their idea of a category member

  • Relies on representativeness heuristic

Type 1 thinking

fast and automatic thinking, relies on heuristics

Type 2 thinking

slower, effortful thinking, more likely to be correct

Type 1 thinking can be sophisticated and considers base-rate if

• Base-rate is presented as frequencies, not probabilities or proportions (e.g. 12 out of every 1000 cases)

• The role of random chance is emphasized ⇒ attend to quantity, sensitive to chance fluctuations

• Can be trained to understand that large samples are more reliable than small ones

Deduction

• process through which you start with “givens” and ask what follows from these premises

  • For example, if you believe that relationships based on physical attraction never last, what follows from this belief?

Induction

process through which you forecast about new cases based on observed cases

Confirmation bias

• A greater sensitivity to confirming evidence and a tendency to neglect disconfirming evidence

• When assessing a belief/hypothesis ⇒ likely to seek confirming evidence

• Take confirming evidence at face value, reinterpret disconfirming evidence to reduce its impact

• Fail to adjust belief when disconfirming evidence is provided

• Remember confirming evidence better, remember disconfirming evidence in distorted form

• Fail to consider alternative hypothesis

Belief perseverance

A tendency to continue endorsing a belief even when disconfirming evidence is undeniable

Categorical syllogism

• logical arguments containing two premises and a conclusion

• E.g. All M are B, all D are M ⇒ All D are B

Belief bias

• If people happen to believe the conclusion, they’re likely to judge it as following logically from the premises

• If they happen to believe the conclusion to be false, they’re likely to reject the conclusion as invalid, i.e. does not follow logically from the premises

Decision making

• English philosophers Jeremy Bentham and John Stuart

  • Principle of utility maximization or choosing the option with the greatest expected value

  • Balance of costs and benefits

• Problem: decisions are often guided by factors that have nothing to do with utility maximization

  • The need for justification: framing effect, endowment effect

  • Emotion

Maximizing utility vs. seeing reasons

• Instead of utility maximization, maybe decision-making is based on reason=based choice

• Our goal is simply to make decisions that we feel good about because we feel they are reasonable and justified

• When framed differently, different justifications are needed

Emotions

• People’s decisions are powerfully influenced by emotions

• Assessment of risk in emotional terms

• Use of somatic markers to evaluate options

• Reliance on “gut feelings” may favor options that trigger positive feelings

Predicting emotions

• Affective forecasting: your predictions about your own future emotions

• People can usually predict whether their reaction would be positive or negative

• They are often inaccurate as to the duration of the feelings

• Also inaccurate as to the extent of the feelings

• People tend to overestimate the extent of their future feelings