Chapter 11: Making Decisions Flashcards

1
Q

Rationality

A

Rational decision making has to do with selecting ways of thinking and acting to serve your goals or moral imperatives, as well as the environment permits

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2
Q

Cognitive Overload

A

When available info overwhelms the cognitive processing available

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3
Q

Phases of Decision Making

A

Setting/revising goals
Make plans
Gather info
Structure the decision
Make a final selection

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4
Q

Setting Goals

A

Decision maker takes stock of their future plans, principles and values, or priorities
Those answers influence decision making

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5
Q

Gathering Info

A

Need information before making a decision
Need to understand various options
Short and long term consequences
Who is affected in each option
Do effects change over time

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6
Q

Structuring the Decision

A

Decision structuring: the way a decision maker manages information and considerations for a decision
Need a way of organizing info for complex decisions
Especially when there are many options or many considerations to be used in making the decision

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7
Q

Making A Choice

A

Selecting from among the final set of options
Can involve objective choice (e.g. coin flip) or more complex process
May involve other decisions (e.g. when to stop gathering info, which info is more relevant)

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8
Q

Evaluating

A

Evaluation of entire decision process
Often an omitted step
Reflect on process and identify aspects to be improved, and those who should be used again

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9
Q

Probability

A

Measurement of a degree of uncertainty
Probabilities are numbers between 0 and 1
0 = complete certainty that an event will not happen
1 = complete certainty that an event will happen
People’s intuitions about probability are often wrong

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10
Q

Subjective Probabilities

A

Influenced by characteristics of probability estimator
If in a bad mood, probability estimates of success tend to be lower

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11
Q

Objective Probabilities

A

Not influenced by the person doing the estimation
Many real life circumstances are not objective

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12
Q

Biases

A

Ways of thinking that lead to systematic errors
Biases are usually understandable and often justifiable ways of thinking but can lead to error when misapplied

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13
Q

Cognitive Illusions

A

Systematic biases
Analogy to perceptual illusions
Errors of cognition that come about for understandable reasons and provide info relevant to understanding normal functioning

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14
Q

Heuristics

A

Shortcuts or rules of thumb used when estimating probability/frequency/numerosity

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15
Q

Availability Heuristic

A

Assessing the ease with which the relevant mental operation of retrieval, construction, or association can be carried out
Instances that are more easily thought of, remembered, or computed stand out more in one’s mind

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16
Q

Examples of Availability Heuristics

A

Husbands/wives are more likely to report they do more household chores because their own chores are more salient
We think words _ _ _ _ i n g are more frequent than _ _ _ _ _ n _
People judging more common cause of death is plane vs car

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17
Q

When Does Availability Heuristic Work Well

A

When we are sure that ease of constructing or calling instances to mind is unbiased

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18
Q

When Availability Heuristics Don’t Work

A

Trying to decide what occurs more often

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19
Q

Representativeness Heuristic

A

People expect that a random process will always produce results that look random

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20
Q

Examples of Representative Heuristic

A

People think its more likely to have GBBGBG than BBBGGG in birth order of siblings because it looks more random and representative

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21
Q

Gambler’s Fallacy

A

A random process will not always produce results that look random
E.g. think its more likely to spin a red if black was spun the previous time, even though it’s still 50/50

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22
Q

Law of Small Numbers

A

People expect small samples to resemble in every respect the population they are drawn from
But in reality smaller samples are more likely to deviate from the population and are not reliable to build conclusions on

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23
Q

Man Who Arguments

A

Ignoring base rate information and paying as much attention to small sample sizes as to large ones
E.g. I know a man who smoked three packs a day and lived to 110

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24
Q

Framing Effects

A

People evaluate outcomes as changes from a reference point/current state
Description ‘frames’ the decision
Depending on how current state is described, they perceive certain outcomes as gains/losses

25
Q

Example of Framing Effect

A

Gas for $1/liter at Station A and $.95/liter at Station B, but station A has 5 cent cash discount and station B has 5 cent surcharge for credit
Actually are the same price, but people prefer station A
We treat losses more seriously than gains

26
Q

Anchoring

A

An initial starting point has a huge effect on final estimates
We begin by guessing a first approximation (anchor) and then make adjustments based on additional information

27
Q

Sunk Cost Effect

A

Greater tendency to continue an endeavor once an investment in money, effort, or time has been made
But money spent or resources used are already gone regardless of continuing on or stopping something

28
Q

Illusory Correlation

A

Seeing nonexistent relationships due to expectations
More likely to search for confirmatory information for your expectations
Seek out evidence that is consistent with expectations

29
Q

Example of Illusory Correlation

A

Hair twisters observed, then tested on stress
Data showed that there was no relationship between stress and hair twisting, but people still believed there was an effect because it sounds plausible

30
Q

Hindsight Bias

A

Tendency to consistently exaggerate what could have been anticipated in foresight when looking back on an event

31
Q

Confirmation Bias

A

Tendency to search only for information that will confirm one’s initial hypothesis, and overlook/ignore other info

32
Q

Examples of Confirmation Bias: 2-4-6 Task

A

Need to find out the rule this follows by generating other triplets to test rule
People tend to try sets that follow their rule instead of testing against their rule
Instead, need to generate a counter-example to disconfirm it

33
Q

Examples of Confirmation Bias: Cheater Detection

A

There’s a dedicated mechanism for detecting those who default on social contracts
People perform better in real life situations than with arbitrary numbers and letters (e.g. can someone drink beer)

34
Q

Overconfidence

A

Confidence ratings are higher than actual accuracy
Overconfidence is an impediment to decision making, makes you weight intuition more heavily than objective information

35
Q

Calibration Curve

A

Plotting confidence against accuracy
Closer to a 45 degree line, the better the calibration/fit between confidence and accuracy
Deviations from the curve below this line are said to indicate overconfidence
Deviations below the line would indicate under-confidence (rare)

36
Q

Sources of Decision Difficulty

A

Conflict: Decision maker must make trade offs across different dimensions (e.g. car power vs mileage)

Uncertainty: Outcome of decision often depends on uncertain variables or events (e.g. future demand for a product)

37
Q

Utility Models of Decision Making

A

Normative
Prescriptive
Descriptive

38
Q

Normative Models

A

Ideal performance under ideal circumstances

39
Q

Prescriptive Models

A

Tells us how we ought to make decisions
Take into account that circumstances of decision making is rarely ideal
Provide guidance about how to do the best we can

40
Q

Descriptive Models

A

Detail what people actually do when they make decisions
Not necessarily endorsement of good ways of thinking, but just describe actual performance

41
Q

Expected Utility Theory

A

Calculate expected value/utility of each outcome in a decision
EU = E(pi x ui)

42
Q

Utility

A

Ideas of happiness, pleasure, and satisfaction coming from achieving one or more personal goals

43
Q

Measuring Utility

A

Select one outcome to assign as 0, assign other values using this as a reference point
Final decision depends on differences in EUs, not on absolute value of utilities

44
Q

Why EU Is Not Normative

A

EU provides account only of making the final selection from set of alternatives, not of making decisions in which one faces a status quo versus make a change option

45
Q

Image Theory

A

In making real life decisions, people rarely go through a formal structuring process
Most of decision making work is done during the prechoice screening of options phase

46
Q

Screening Options

A

When decision makers winnow number of options under consideration to a small number
Ask themselves whether the new goal/plan/alternative is compatible with three images;
Options judged as incompatible with one or more of the images are dropped from consideration

47
Q

Three Images

A

Value image: containing the decision maker’s values, morals, and principles
Trajectory image: containing the decision maker’s goals and aspirations for the future
Strategic image: the way in which the decision maker plans to attain their goals

48
Q

Recognition Primed Decision Making

A

Experts are most likely to rely on intuition, mental simulation, making metaphors or analogies, and recalling or creating stories
Compare current issue with previous instances
Experts consider one option at a time, mentally simulating the likely effect of a particular decision

49
Q

Neuroeconomics

A

Field examining how the brain interacts with the environment to enable us to make complex decisions

50
Q

Ultimatum Game

A

If people receive one time offer to split $10 with partner, when offered only $1 people refuse and neither get the money, but accept with $5
Even though the best choice would be to take any money over none

51
Q

Ultimatum Game In The Brain (Unfair Offers)

A

Anterior cingulate cortex: Conflict between choices/responses

Right dorsolateral prefrontal cortex: Effortful processing, cognitive effort

Right and left insula: Implicated in disgust and discomfort, Visceral negative responses

52
Q

Improving Decision Making: Biases

A

Telling people about biases in decision making and planning results in little/no improvement
Bias reduction requires extensive practice with task, individual performance feedback, and means of making the statistical or probabilistic aspects of decisions clearer
Even brief 30-minute training sessions in statistical reasoning could improve people’s ability to apply statistical principles to everyday life

53
Q

Improving Decision Making: Feelings & Expectations

A

Often better, fairer, more rational, and more humane to use decision aids than to rely exclusively on human intuition
People are proficient as figuring out which variables are good predictors
Human shortcomings show up when trying to integrate all info relevant to a decision

54
Q

Decision Analysis

A

Emerging technology that helps people gather and integrate info by using human feelings, beliefs, and judgements of relevance, but helps ensure integration of info is carried out without bias

55
Q

Split Brain & Two Things With One Hand

A

Joe has hard time doing two different things with each hind (e.g. draw a circle and square with opposite hands)
But when present instructions to each side of brain simultaneously (e.g. on each side of a screen), problem is fixed

56
Q

Split Brain & Fruit Faces

A

When present face made out of fruit to different sides, sees it differently
Right hemisphere saw the face made out of vegetables (presented on left of visual field)
Left hemisphere saw fruit/veggies (presented on right of visual field)

57
Q

Decision Making In Split Brain

A

Participants had to guess where a block was going to appear (top/bottom, on left hemisphere and on right hemisphere)
Stimuli presented very quickly
More frequent presentations on the top than on the bottom

Right hemisphere presentation
Maximized
More rational thing to do
Always chose the option that has occurred the most frequently in the past
100% of the time guessing it will appear at the most frequent location

Left hemisphere
Frequency matched
Matched the responses to their guesses
Neural processes responsible for searching for patterns in events are housed in the left hemisphere

58
Q

Causal Reasoning In Split Brain

A

Perceptual event
Had to respond if the dots moving on a screen were causal or not

Blicket task/Causal inference
One colour or diff pattern of colour would cause a box to change colour
Had to look at pattern to judge and see what caused the square colour change
Which colour (green or red) caused the big box to change colour

Control participants did well on both tasks presented to both hemispheres
Perceptual task was better when presented to the right hemisphere
Causal inference task was better when presented to left hemisphere