Lecture 12 - Judgements, Decision and Reasoning Flashcards

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1
Q

what is a heuristic?

A

simple procedure used to find adequate but often imperfect answers to difficult questions

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2
Q

who is KT?

A

Daniel Kahneman and Amos Tversky

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3
Q

what is bounded rationality?

A

theory that humans reason and choose rationally, but only within the constraints imposed by their limited search and computational capacities

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4
Q

what is satisficing?

A

using experience to construct an expectation of how good a solution we might reasonable achieve and halting search as soon as a solution is reached that meets the expectation

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5
Q

what did paul meehl find

A

that clinical prediction performs very poorly relative to statistical prediction and that it overweights case characteristics and underweights base rates

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6
Q

what are the characteristics of system 1?

A

intuitive, fast, nonconscious, automatic

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7
Q

what are the characteristics of system 2?

A

reflective, slow, conscious, controlled

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8
Q

how do system 1 and 2 interact?

A
  • system 2 kicks in when system 1 is unable to solve/interpret/understand stimuli
  • system 1 feeds system 2 and 2 normally takes this on apart from when there is something obscure not taken on by 1
  • NB, 2 is not actually that slow as it is responsible for control, eg control of not saying something we shouldn’t
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9
Q

how can we improve system’s 2 intervention?

A
  • provide rewards to motivate checking of intuitive impressions
  • reduce cog load
  • increase metacog difficulty (although this one is sceptical)
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10
Q

what is the proposed mechanism of system 1?

A

question substitution:
as seeking answer to complex question is hard, system 1 overwrites the question to make it an easier question it thinks is related, substituting an easy to compute feature for a hard to compute feature

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11
Q

what are the 3 general purpose heuristics?

A
  • representativeness
  • availability
  • affect
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12
Q

what is the representativeness Heuristic?

give example

A

probability judgements are substituted with assessments of resemblance… the likelihood that X is Y is substituted with the “degree to which X looks like Y”
Eg, how likely is it that tom is a computer science student is substituted with how much does time resemble a comp science student?

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13
Q

what is the core of the conjunction fallacy?

A

that people substitute a question about probability with similarity

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14
Q

what are the biases related to representativeness heuristic?

A
  • conjunction fallacy (bank teller/fem example)
  • insensitivity to sample size (kids in hospital)
  • misperceptions of randomness (ipod shuffle example)
  • belief in the law of small numbers (mistaken confidence in adequacy of small samples representative of pop)
  • hot hand fallacy
  • base rate neglect (engineer v lawyer guessing)
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15
Q

what is the availability heuristic?

A

factors which come to mind easily are assigned more weight in the formulation of judgments. we judge the likelihood/frequency of an event by the ease with which instances come to mind

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16
Q

example of availability heuristic?

A

hollywood v train drives divorce rates? we think hollywood have higher divorce rates as we are exposed to that information more often

17
Q

what are the biases related to availability heuristic?

A
  • effectiveness of search set (eg, scrabble, “ing” v “n” words)
  • egocentric bias (husband v wife rating their contribution to various activities in relationship - not self serving)
  • outcome (decision with positive outcome is rated as superior)
18
Q

what does schwarz suggest determines our availability? which study proposed this?

A

our subjective experience of the ease of recall
asking participants to either come up with 6 or 12 examples of assertiveness… those who had to get 12 struggled and stopped at 6, thus thinking they were not assertive, whereas those who were asked to come up with 6 assertive examples then viewed themselves as quite assertive

19
Q

what is the affect heuristic?

give eg

A

judgements are made in accordance with the intensity of the emotion felt
eg, how large are the benefits of nuclear power? and you substitute in a response as to how you feel about nuclear power

20
Q

what are the biases related to affect heuristic?

A
  • negative risk/benefit correlation (benefit/risk of nuclear power leads to inferring the other (risk/benefit) of it)
  • insensitivity to numbers (saving % of 150 lives was more supported than saving 150 lives)
21
Q

what is a so called heuristic?

A

anchoring heuristic

22
Q

what is the anchoring “heuristic”?

A

when estimating quantities, people start with an intuitive reference point (anchor) and make adjustments to it

23
Q

what is an example of the anchoring heuristic

A

1x2x3 etc gets smaller estimate than 3x2x1 etc

24
Q

what were the 3 critiques of KT’s work

A
  1. KT’s biases lack external validity
  2. have been vaguely theorised/specified and there has been a lack of formal modelling
  3. overstates the problems caused by computational limits of our brains
25
Q

what are some examples of the critique: 1. KT’s biases lack external validity

A

minor changes in wording/context could sometimes debias people, eg

  1. eliciting frequencies rather than probabilities
  2. emphasising the role of random sampling
26
Q

what is an example of the critique: KT’s work overstates the problems caused by computational limits of our brains

A

complex methods won’t necessarily outperform simple one

the fast and frugal methods can be better

27
Q

what is an example of a fast and frugal method?

A

recognition heuristic

28
Q

what is the recognition heuristic

give eg

A

theory that you may actually be correct if you recognise one object and not the other which leads you to determine it has the higher value

eg: which city has more inhabitants question
- those who recognises only one were more often correct

29
Q

what heuristic might come into play if “both cities” are recognised?

A

“Take the best”

30
Q

what is the “Take the best” heuristic?

A

look up cues in order of their validity, stop search when ev for one object (city featured in film) but not the other is found