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Cognition > decision making: uncertainty and risks > Flashcards

decision making: uncertainty and risks Flashcards

1
Q

heuristic

A

mental shortcut or rule of thumb that can be used to get a quick and mostly accurate response in some situations but may lead to errors in others

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2
Q

bias

A

deviations from rationality (errors) that are caused by using heuristics

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3
Q

what are the three categories of biases

A
  • biases that affect how we interpret information
  • biases that affect how we judge frequency (how often something happens)
  • biases that affect how we make predictions
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4
Q

availability heuristic

A

estimate the probability of an event based on the ease at which it can be brought to mind

leads us to overestimate the probability of events based on how salient they are in our minds

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5
Q

representativeness heuristic

A

tend to make inferences on the basis that small samples represent the larger population they were drawn from
- related to stereotypes, schemas, and other pre existing knowledge structures
- basing judgements of group membership based on similarity

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6
Q

base rate neglect

A

when you fail to use information about the prior probability of an event to judge the likelihood of an event

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7
Q

conjunction fallacy

A

false belief that the conjunction of two conditions is more likely than either single condition

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8
Q

anchoring and adjust heuristic

A

judgements are too heavily influenced by initial values

people start off with one value and adjust accordingly from there

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9
Q

regression to the mean

A

when a process is somewhat random (i.e. weak correlation), extreme values will be closer to the mean (i.e. less extreme) when measured a second time

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10
Q

illusionary correlations

A

people tend to see causal relationships when there are none

related to our understanding of the roles of reward and punishment on learning

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11
Q

bounded rationality

A

idea that there is a limitation to our cognitive capacity caused by both environmental constraints and individual constraints

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12
Q

satisficing

A

people are satisficers: look for solutions that are “good enough”

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13
Q

ecological rationality

A

see heuristics not as a “good enough” approach, but as the optimal approach

given the right environment, a heuristic can be better than optimization or other complex strategies - better than more deliberate strategies

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14
Q

when does regression towards the mean happen

A

where there is not a perfect correlation

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15
Q

why do we use heuristics

A

because we are boundedly rational

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16
Q

why does the conjunction fallacy arise

A

because people use the representativeness heuristic

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17
Q

perceptual decision making

A

objective (externally defined) criterion for making your choice

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18
Q

value based decision making

A

subjective (internally defined) criterion) for making your choice - depends on motivational state and goal

ie. what do I want for dinner?

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19
Q

risk

A

taking an action despite the outcome being uncertain

specific to value based decision making

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20
Q

ambiguity

A

can be defined when you have incomplete information about the consequences

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21
Q

extremes in risk taking

A

stagnant living or addiction and impulsivity

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22
Q

how can we frame risks

A

as gains or losses

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23
Q

risk premium

A

difference between expected gains of a risky option and a certain option

24
Q

risk averse

A

decision maker has positive risk premium
- need a chance at winning a lot more than a certain option to select the risky option

25
Q

risk neutral

A

decision maker has zero risk premium
- no difference in the options

26
Q

risk seeking

A

decision maker has negative risk premium
- doesn’t need the chance at winning more than the certain option to gamble

27
Q

behavioural economics

A

how do people act

arised from the gap between assumptions made by classical economic theories and how people actually act

28
Q

the framing effect

A

inconsistent risk preference depending on the framing (loss vs gains) of the problem

people are risk averse when the options are described as gains

people are risk seeking when the options are described as losses

29
Q

endowment effect

A

once ownership is established, people are averse to give it up

people are averse to losses

30
Q

prospect theory

A

describes how people behave - what people do instead of what people should do

predicts that we have different risk patterns depending on the probability and losses and gains

two major parts:
- shape of utility function
- shape of probability weighting function

31
Q

utility

A

subjective value assigned to an object
context dependent

utility is assigned to a monetary amount as a function of someone’s current state (reference point) and not in absolute value (not inherent)

deviations from reference point will determine risk preference

32
Q

utility function

A

first part of prospect theory

mathematical function that describes how people map money to satisfaction/treat gains and losses

losses loom larger than gains - linked to the framing effect

describes extra satisfaction you get from gaining a dollar when you only have $1 compared to when you have $1million

33
Q

probability weighting function

A

describes how people understand likelihoods

extremity pf event related to perceived probability

availability of an option changes the perceived frequency of the option

means that people tend to overestimate rare events and underestimate mundane events

34
Q

dual process theory

A

it is thought that there are two systems for making decisions

system 1: fast, effortless, automatic, intuitive, emotion
- heuristics and biases
- limbic system (emotions)

system 2: slow, deliberative, effortful, explicit, logical
- rational choice

35
Q

prediction error

A

the difference between what you predicted would happen and what actually happened

drive learning (reinforcement learning)
can be positive or negative

36
Q

mood affect real world gambling

A

changes in mood predict risky decision making —- when people are happy they are more likely to gamble

37
Q

changes in mood and assesment of risk level

A

negative mood increase people’s estimated frequency of negative events

38
Q

risky choices

A

related to affective (as opposed to deliberative) decision making

  • activity in brain areas implicated in emotional processeing
39
Q

modus ponens

A

affirming the antecedent

idea that if we observe the antecendent is true, we can conclude that the consequent is true

40
Q

modus tollens

A

denying the consequent

occurs when we observe the consequent is false and conclude that the antecedent must be false as well

41
Q

expected utility hypothesis

A

classical economic theory idea that assumes when people are faced with multiple options, they will choose the one that returns the highest likely value

42
Q

propositions

A

possible facts about the world - can be true or false and can refer to properties of the external world or about our own experiences

43
Q

deduction vs induction

A

deduction - conclusion follows logically from the initial premises

induction - relies on generalizing from a certain set of information and extending it to make an informed guess

44
Q

syllogism

A

a kind of reasoning in which a conclusion is derived from two or more propositional statements

most common: categorical syllogism, which consists of three statements: two premises and one conclusion

45
Q

conditional or hypothetical syllogism

A

contain a conditional claim, which states a rule that relates two propositions

if P, then Q

P=antecedent
Q= consequent

46
Q

What we tend to do when evaluating syllogisms (evans)

A

we have a mistaken tendency to try to confirm a syllogism as valid versus establishing that it is invalide

47
Q

what is the key to testing a rule (watson)

A

check cases that have the potential to prove it wrong or falsify it

checking cases that may be consistent with it but that can’t disprove it have no utility in testing whether the rule is true

48
Q

belief bias

A

a tendency to rate conclusions that are more believable as more valid

49
Q

atmosphere effect

A

a tendency to rate conclusions as more valid when the qualifying words in the premises match those in the conclusion

50
Q

mental models

A

mental simulation of the world, based on descriptions in the syllogism - if it involves concrete concepts, people will generate visualizations of the sentences and then mentally explore them to see whether the model breaks down

51
Q

generalization

A

refers to cases in which we extrapolate from a limited number of observations to draw a conclusion about the broader population or category

52
Q

statistical syllogism

A

going from observations about a group to an inference about an individual

53
Q

argument from analogy

A

when we observe that two things share some set of properties and conclude that they must share a different property

54
Q

one shot learning

A

when a concept is learned from a single example - requires a lot of inductive reasoning

55
Q

bayesian inference

A

mathematical model for incorporating existing beliefs, called the prior, with new data, in order to make an educated inference

56
Q

status quo bias

A

a tendency to leave things as they currently are, rather than making a change

shown by samuelson and zeckhauser’s inheritance study

57
Q

emotional factors in decision making

A

integral emotions: directly related to the decision
incidental emotions: not directly related to the decision but that happen to be the state of the person at the time they are making the decision

Cognition (20 decks)

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