Choice Guest Lecture 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

systematically inaccurate choices that don’t reflect a current situation

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3
Q

3 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

The easier it is to remember something, the more likely you’ll think it is to happen in the future

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5
Q

what heuristic can explain why people are afraid of flying but not driving

A

the availability heuristic

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6
Q

representativeness heuristic

A

Tend to make inferences on the basis that small samples resemble the larger population they were drawn from

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7
Q

the representativeness heuristic is related to ___

A

stereotypes, schemas, and other pre-existing knowledge structures

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8
Q

how do people base their judgments of group members?

A

based on similarity

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9
Q

what kinds of biases does the representativeness heuristic result in

A

base-rate neglect & conjunction fallacy

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10
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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11
Q

application of base-rate neglect

A

Important for doctors diagnosing with low incidence populations

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12
Q

conjunction fallacy

A

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

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13
Q

example of the conjunction fallacy

A

Linda the feminist Bank Teller

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14
Q

anchoring and adjustment heuristic

A

Judgments are too heavily influenced by initial values. People start off with one value and adjust accordingly from there

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15
Q

application of anchoring and adjustment in psychology

A

Important when getting ratings from a scale

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16
Q

regression to the mean

A

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

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17
Q

regression to the mean is related to

A
  • illusionary correlations
  • our understanding of the roles of reward and punishment in learning
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18
Q

bounded rational

A

we are limited by both environmental and individual constraints

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19
Q

satisficers

A

look for solutions that are good enough

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20
Q

bounded rationality in humans

A

people are both bounded rational and satisficers

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21
Q

who proposed ecological rationality?

A

Gigerenzer

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22
Q

ecological rationality

A

Sees heuristics not as good enough approaches to solving a problem, but as the optimal approach

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23
Q

does ecological rationality distinguish between descriptivism and prescriptivism?

A

While previous views on heuristics draw a separation between how we should act and how we do act ecological rationality doesn’t distinguish these two

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24
Q

heuristics vs. optimization according to ecological rationality

A

Given the right environment, a heuristic can be better than optimization or other complex strategies

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25
perceptual decision-making
objective, externally defined criterion for making your choice
26
value-based decision-making
subjective, internally-defined criterion for making your choice
27
risk
taking an action despite the outcome being uncertain
28
risk is specific to what kind of decision-making
value-based decision-making
29
ambiguity
when you have incomplete information about the consequences
30
what are most people's risk attitude profile
risk-averse
31
harmful examples of risk-taking
- Stagnant living - Addiction and impulsivity
32
how are risks framed?
as gains and losses
33
risk premium
the difference between the expected gains of a risky option and a certain option
34
risk averse
the decision maker has a positive risk premium (Need a chance at winning a lot more than a certain option to select the risky option)
35
risk-neutral
the decision maker has zero risk premium (no difference in the options)
36
risk-seeking
the decision maker has a negative risk premium (doesn’t need the chance at winning more than the certain option to gamble)
37
3 risk attitude profiles
- risk-seeking - risk-averse - risk-neutral
38
are risk preferences irrational
no
39
what theories account for individuals' risk preferences
Classic (rational) economic theories (Expected Utility Theory)
40
what theories account for individuals' inconsistent preferences
behavioural economics, the framing effect, and prospect theory
41
the framing effect
Inconsistent risk preferences depend on the framing (loss vs. gains) of the problem
42
when are people risk-averse according to the framing effect?
when the options are described as gains
43
when are people risk-seeking according to the framing effect?
when the options are described as losses
44
framing effect study (Gachter et al., 2009)
- 93% of students signed up early when they were told they would pay a penalty fee - But only 67% signed up early when they would get a discount
45
endowment effect
Once ownership is established, people are averse to giving it up
46
what theory is described as the birth of behavioural economics?
prospect theory
47
2 major contributions to prospect theory
- Shape of the utility function (losses vs. gains) - Shape of probability weighting function (unlikely vs. likely events)
48
prospect theory
Describes how people do act, not how they should act
49
utility
subjective value assigned to an object
50
is utility consistent?
no it's context-dependent
51
how is utility typically assigned?
as a function of someone’s current state (reference point) and not in absolute value
52
utility function
describes how people map money to satisfaction
53
shape of the utility function
Asymmetrical: steeper for losses than gains. $1 lost hurts more than one dollar earning
54
extremity of events and perceived probability
- Unlikely events are overestimated - Likely events are underestimated
55
high probability of losses results in
risk-seeking behaviour
56
low probability of losses results in
risk-averse behaviour
57
high probability of gains results in
risk-averse behaviour
58
low probability of gains results in
risk-seeking behaviour
59
dual process theory
It is thought that there are two systems for making decisions
60
system 1
fast, effortless, automatic, intuitive, emotional
61
system 1 relies on
heuristics & biases
62
system 1 neural mechanism,
the limbic system
63
system 2
slow, deliberative, effortful, explicit, logical
64
system 2 relies on
Rational choice
65
neural mechanism behind system 2
Frontal cortex
66
why are risks sometimes described as feelings?
Increased amygdala activity for chosen safe outcomes for gains and chosen risky outcomes for losses suggests that an emotional response may underlie the framing affect
67
assessing risk & emotion
There were higher estimates of death frequency when people were in a negative mood compared to a positive mood
68
prediction error
The difference between what you predicted would happen and what actually happened
69
prediction error is responsible for
learning (especially reinforcement learning)
70
positive prediction error
unexpectedly good outcome
71
negative prediction error
unexpectedly bad outcome
72
how does positive prediction error effect affect
increases positive affect
73
how does negative prediction error effect affect
increases negative affect
74
emotion & risky decision-making
Changes in mood predict risky decision making When people are happy, they are more likely to gamble
75
how is risk preference determined in the utility function?
Deviations from the reference point
76
when do biases occur?
when heuristics are over-applied
77
availability heuristic and political parties
both Democrats & Republicans think the electoral maps work against their party
78
illusory correlations
Linking two co-occurring events and assuming a relationship
79
when do illusory correlations often occur?
when outcomes are overemphasized
80
anchoring and adjustment heuristic and the UN experiment
Participants were given a random number between 0 and 100 and asked if this number was higher or lower than the percentage of African nations in the UN. Those who were given a high random number gave great percent estimates than those given a low random number. this demonstrates that we even anchor estimates to unrelated information
81
gambler's fallacy
The false belief that a predicted outcome of an independent event depends on past outcomes
82
real-world examples of the gambler's fallacy
- U.S. judges in refugee asylum cases are more likely to deny asylum after granting asylum to the previous applicant - Loan officers are more likely to deny a loan application after approving the previous application - People continue to invest after several losses on the stock market
83
the hot hand beleif
Thinking that a person who experiences success will keep having success
84
the hot hand belief and basketball
Asked basketball fans about players’ shooting abilities. 91% of fans thought that a player is more likely to make a shot after taking 2 shots than after missing a shot
85
optimism bias
People overestimate the number of predicted positive events and underestimate the likelihood of negative events
86
optimism bias in depression patients
This optimism bias wasn’t present in depression patients. Presentation differs with the degree of depression
87
heuristics function
making intuitive and rapid judgments
88
overapplication of heuristics can lead to
serious errors in our judgments and reasoning (ex. Stereotyping & Gambling addictions)
89
post-mortem technique
learning from failures
90
pre-mortem technique
anticipate and prevent our mistakes before they result in catastrophe
91
challenges and the availability heuristic
We can remember challenges we had to overcome better than other people’s challenges. We perceive things as harder for us compared to others