2. Bounded Rationality Flashcards

1
Q

Rational decision making assumes…

A
  • transitivity
  • use of all info, obey laws of probability, Bayes’ rule
  • description invariance
  • logical thinking
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2
Q

In reality how rational are people?

A

They are boundedly rational, they use heuristics rather than fully rational choices

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3
Q

How does system 1 work?

A

Intuition- it’s fast, automatic, effortless and emotional

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4
Q

How does system 2 work?

A

Reasoning- it’s slow, controlled, rule governed, neutral and takes effort

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5
Q

Primes

A

Subconscious cues that influence judgment and behaviour. They work on system 1. System 2 is needed to override them

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6
Q

Accessibility

A

The ease at which thoughts come to mind, can depend on the context and how the information is presented

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7
Q

Base rate neglect

A

Often system 1 reacts to the descriptive emotional side of the information and ignores the base rate. System 2 is needed to appreciate the base rate

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8
Q

When do people stick to the base rates?

A

When there is no other salient info

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9
Q

Statistical vs causal info

A
  • stats- 85% of cabs are green, 15% are blue

* causal- the two companies have the same number of cars but the greens are involved in 85% of crashes

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10
Q

How are statistical and causal base rates weighted?

A

Stats are generally underweighted and causal base rates are overweighted since info about the individual is accessible and we apply this to the whole population

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11
Q

Heuristics

A

Reduce complex tasks to simpler judgmental operations. In general they are useful, but they can lead to errors.

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12
Q

What are the three heuristics?

A

Representativeness
Availability
Anchoring

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13
Q

Representativeness

A

The probability that event x belongs to set y is judged on the basis of how similar x is to the stereotype of y

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14
Q

Availability

A

A frequency of probability is estimated by the ease that instances or associations can be brought to mind

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15
Q

Anchoring

A

A quantity is estimated by starting from a convenient or salient anchor and then adjusting in the appropriate directions

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16
Q

Conjunction fallacy

A

Where people place similarity over probability. E.g. 85% of people rank “Linda is a feminist bank teller” over “Linda is a bank teller”

17
Q

How can incentives affect the conjunction fallacy?

A

People are more likely to get the “correct answer” since they slow down and use system 2

18
Q

Mistakes caused by representativeness

A
  1. Insensitivity to sample size
  2. Law of small numbers
  3. Regression to the mean
19
Q

Insensitivity to sample size

A

People assess the likelihood of a sample result by asking how similar it is to the properties of the population from which the sample is drawn

20
Q

Law of small numbers

A

The belief that small samples ought to represent the population e.g. gamblers fallacy and hot hands fallacy

21
Q

Regression to the mean

A

Outliers move back towards the mean. Previous results aren’t necessarily representative of future results

22
Q

Anchoring

A

When estimating an unknown quantity where inevitably you have to start with some estimate

23
Q

Anchoring index

A

(h-l)/(H-L)

24
Q

Insufficient adjustment

A

Where you begin an estimate but don’t finish so you adjust but insufficiently

25
Q

Anchoring as priming

A

Where an initial anchor evokes an image of something which biases your estimate . E.g Gandhi being an old man

26
Q

Availability

A

Where you assess the frequency of a class or the probability of an event by the ease with which instances or occurances can be brought to mind

27
Q

Affect heuristic

A

In making judgments, people tag the affect or positive/ negative feelings induced by the event or stimulus. Feelings are accessible, estimates much less