Problem 7
Eysenck, Matlin, Sternberg
Judgement: involves deciding on the likelihood of various events using incomplete information
- What matters in judgement is accuracy
Decision making: involves selecting one option from several possibilities
- We assess the quality of our decisions in terms of consequences
- Judgement often forms an important initial part of the decision-making process
- Uncertainty of decision making is more common than the certainty of deductive reasoning
HEURISTICS by Kahneman & Tversky
- Most people given judgment tasks make use of rules of thumb or heuristics
- Heuristics are strategies to make decisions simpler and faster, heuristics reduce the
difficulty of decision making
REPRESENTATIVENESS HEURISTICS: involves deciding something belongs to a given category
because it appears typical or similar to that category
- we believe that random looking outcomes are more likely than orderly outcomes
- people ignore important statistical information that they should consider
Small Sample Fallacy: people think a small sample will be representative of the population
from which it’s selected
- representativeness is so compelling that we often fail to pay attention to sample size
- in reality sample size is an important characteristic that should be considered
- a large sample is statistically more likely to reflect true proportions
Base Rate Fallacy: paying too little attention to important information about base-rate
- base-rate is how often an item occurs in the population
- we focus on representativeness instead of base-rate
- this task provides support for the dual-process approach, different parts of the brain are
activated when people use Type 1 processing, rather than slow Type 2 processing?
Conjunction fallacy: the mistaken belief that the conjunction or combination of 2 events (A
and B) is more likely than 1 event (A or B) on its own
- representativeness is so powerful that people ignore mathematical implications of the
conjunction rule
- example: Linda is a bank teller or Linda is a feminist bank teller
- People rely on representativeness because the description sounds more like a feminist
bank teller
- People interpret the statement “Linda is a bank teller” as implying she is not an active
feminist
AVAILABILITY HEURISTIC: the frequencies of events can be estimated on the basis of how easy it is
to think of relevant examples (retrieve from memory)
- This heuristic is accurate as long as availability is correlated with true, objective frequency
- Unlike representativeness heuristic (given a specific example and then decide if it’s similar
to a category), you are given a general category and then you must recall the specific
examples
, - Factors can bias availability heuristics and influence memory retrieval:
Recency: more recent events are more available
- you judge recent items to be more likely than they actually are
Familiarity: can produce a distortion in frequency estimation
- media coverage can influence viewers’ ideas
Recognition heuristic: operates when you recognize one category, but not the other, you
conclude that the recognize category has higher frequency
- leads to accurate decisions
- Example: which Italian city has a larger population Milan or Modena? Milan is recognized
more so in this case the decision to pick Milan is accurate
Illusion Correlation: availability heuristic contributes to a cognitive error called illusion
correlation
- occurs when people believe that two variables are statistically related, even though there
is no actual evidence for that relationship
- Example: we often believe that a certain group of people tend to have a certain
characteristic, even though that stereotype is not true
THE ANCHORING AND ADJUSTMENT HEURISTIC:
- We begin with a first approximation, which serves as an anchor, then we make
adjustments to that number based on additional information
- This heuristic often leads to reasonable answers just as representativeness and availability
heuristics
- However, people rely too heavily on the anchor and their adjustment are too small
- This emphasizes top-down processing – people endorse their current beliefs rather than
questioning them
Estimating confidence intervals: we not only use this heuristic for a single number but
confidence intervals
- We make errors by estimating a range that is too narrow
Alternative views to heuristic approach
Gigerenzer and colleagues argue that the heuristic approach underestimated people’s decision-
making skills, they say people make fairly realistic judgements
Ecological rationality: describes how people create a wide variety of heuristics to help
themselves make useful, adaptive decisions in real world
Default heuristic: if there is a standard option in which people do nothing, people will
choose it
- Example: you have to sign up to become an organ donor, so the majority remains a non-
donor using the default heuristic
Limitations to original heuristics-and-biases approach
- heuristics are vaguely defined
- theorizing based on this approach is limited
- it’s sometimes unfair to conclude people’s judgements are biased and error-prone
- research is detached from the realities of everyday life - emotional & motivational factors
Eysenck, Matlin, Sternberg
Judgement: involves deciding on the likelihood of various events using incomplete information
- What matters in judgement is accuracy
Decision making: involves selecting one option from several possibilities
- We assess the quality of our decisions in terms of consequences
- Judgement often forms an important initial part of the decision-making process
- Uncertainty of decision making is more common than the certainty of deductive reasoning
HEURISTICS by Kahneman & Tversky
- Most people given judgment tasks make use of rules of thumb or heuristics
- Heuristics are strategies to make decisions simpler and faster, heuristics reduce the
difficulty of decision making
REPRESENTATIVENESS HEURISTICS: involves deciding something belongs to a given category
because it appears typical or similar to that category
- we believe that random looking outcomes are more likely than orderly outcomes
- people ignore important statistical information that they should consider
Small Sample Fallacy: people think a small sample will be representative of the population
from which it’s selected
- representativeness is so compelling that we often fail to pay attention to sample size
- in reality sample size is an important characteristic that should be considered
- a large sample is statistically more likely to reflect true proportions
Base Rate Fallacy: paying too little attention to important information about base-rate
- base-rate is how often an item occurs in the population
- we focus on representativeness instead of base-rate
- this task provides support for the dual-process approach, different parts of the brain are
activated when people use Type 1 processing, rather than slow Type 2 processing?
Conjunction fallacy: the mistaken belief that the conjunction or combination of 2 events (A
and B) is more likely than 1 event (A or B) on its own
- representativeness is so powerful that people ignore mathematical implications of the
conjunction rule
- example: Linda is a bank teller or Linda is a feminist bank teller
- People rely on representativeness because the description sounds more like a feminist
bank teller
- People interpret the statement “Linda is a bank teller” as implying she is not an active
feminist
AVAILABILITY HEURISTIC: the frequencies of events can be estimated on the basis of how easy it is
to think of relevant examples (retrieve from memory)
- This heuristic is accurate as long as availability is correlated with true, objective frequency
- Unlike representativeness heuristic (given a specific example and then decide if it’s similar
to a category), you are given a general category and then you must recall the specific
examples
, - Factors can bias availability heuristics and influence memory retrieval:
Recency: more recent events are more available
- you judge recent items to be more likely than they actually are
Familiarity: can produce a distortion in frequency estimation
- media coverage can influence viewers’ ideas
Recognition heuristic: operates when you recognize one category, but not the other, you
conclude that the recognize category has higher frequency
- leads to accurate decisions
- Example: which Italian city has a larger population Milan or Modena? Milan is recognized
more so in this case the decision to pick Milan is accurate
Illusion Correlation: availability heuristic contributes to a cognitive error called illusion
correlation
- occurs when people believe that two variables are statistically related, even though there
is no actual evidence for that relationship
- Example: we often believe that a certain group of people tend to have a certain
characteristic, even though that stereotype is not true
THE ANCHORING AND ADJUSTMENT HEURISTIC:
- We begin with a first approximation, which serves as an anchor, then we make
adjustments to that number based on additional information
- This heuristic often leads to reasonable answers just as representativeness and availability
heuristics
- However, people rely too heavily on the anchor and their adjustment are too small
- This emphasizes top-down processing – people endorse their current beliefs rather than
questioning them
Estimating confidence intervals: we not only use this heuristic for a single number but
confidence intervals
- We make errors by estimating a range that is too narrow
Alternative views to heuristic approach
Gigerenzer and colleagues argue that the heuristic approach underestimated people’s decision-
making skills, they say people make fairly realistic judgements
Ecological rationality: describes how people create a wide variety of heuristics to help
themselves make useful, adaptive decisions in real world
Default heuristic: if there is a standard option in which people do nothing, people will
choose it
- Example: you have to sign up to become an organ donor, so the majority remains a non-
donor using the default heuristic
Limitations to original heuristics-and-biases approach
- heuristics are vaguely defined
- theorizing based on this approach is limited
- it’s sometimes unfair to conclude people’s judgements are biased and error-prone
- research is detached from the realities of everyday life - emotional & motivational factors
