Heuristics-biases.ppt

Heuristics and Biases
Thomas R. Stewart, Ph.D.
Center for Policy Research
Rockefeller College of Public Affairs and Policy
University at Albany
State University of New York
T.STEWART@ALBANY.EDU
Public Administration and Policy
PAD634 Judgment and Decision Making Behavior
Copyright © Thomas R. Stewart

PAD634 (heuristics-biases.ppt) 2
Why study heuristics and biases?
There are three related reasons for the focus on
systematic error and inferential biases in the study of
reasoning. First, they expose some of our
intellectual limitations and suggest ways to improve
the quality of our thinking. Second, errors and
biases often reveal the psychological processes that
govern judgment and inference. Third, mistakes and
fallacies help the mapping of human intuitions by
indicating which principles of statistics or logic are
non-intuitive or counter-intuitive. (Tversky and
Kahneman, 1982)

Popular press discovers heuristics
and biases (regularly)
Newsweek, August 17, 1987

Framing

Framing--
Newsweek’s view

Example: Framing (choice 1)
Imagine that the U.S. is preparing for the
outbreak of an unusual disease which is
expected to kill 600 people. You have a
choice between two programs:
Program A: 200 people will be saved.
Program B: either no one is saved (p=.67)
or everyone is saved (p=.33)

Example: Framing (choice 2)
Imagine that the U.S. is preparing for the
outbreak of an unusual disease which is
expected to kill 600 people. You have a
choice between two programs:
Program A: 400 people will die
Program B: either everyone dies (p=.67)
or no one dies (p=.33)

Example: Framing
Choice 1--
Program A: 200 people will be saved.
Program B: either no one is saved (p=.67)
or everyone is saved (p=.33)
Choice 2--
Program A: 400 people will die
Program B: either everyone dies (p=.67)
or no one dies (p=.33)
72% chose
Program A
78% chose
Program B

The choices are formally the same
Imagine that the U.S. is preparing for the outbreak of
an unusual disease which is expected to kill 600
people. You have a choice between two programs:
Choice 1-- Choice 2--
A: 200 people saved A: 400 people die
B: no one saved (p=.67) B: everyone dies (p=.67)
everyone saved (p=.33) no one dies (p=.33)
Expected value of all programs = 200 lives saved

Anchoring--Newsweek’s view

Anchoring
8 x 7 x 6 x 5 x 4 x 3 x 2 x 1 =
1 x 2 x 3 x 4 x 5 x 6 x 7 x 8 =
40,320
40,320
8 x 7 x 6 x 5 x 4 x 3 x 2 x 1 =
1 x 2 x 3 x 4 x 5 x 6 x 7 x 8 =
Analytically...
Judgmentally...
2,250 (median)
512 (median)

Availability--Newsweek’s view

Example of availability
Are there more words with r as the first
letter or as the third letter?
Most people say the first letter, but there
are many more words with r as the third
letter.

Conjunction fallacy
Linda is 31 years old, single, outspoken and very bright. As a
student, she was deeply concerned with issues of discrimination
and social justice, and also participated in antinuclear
demonstrations.
Which is more likely:
1. Linda is a bank teller.
or
2. Linda is a bank teller and is active in the feminist movement.
85% of 142 college undergraduates said statement 2 was more
likely than statement 1.

Conjunction fallacy
By the multiplication rule, the joint
probability (conjunction) of two events
cannot exceed the probability of either
event.

Overconfidence: Speed of light

Overconfidence:
Rest mass of electron

Wason four-card task
• Are scientists and others subject to a
“confirmation bias?”
• Slides on Wason four-card task

“Psychology of Judgment and
Decision Making”
The most popular book on judgment and decision
making covers only coherence.
Plous, S. (1993). The Psychology of Judgment and Decision Making. New York: McGraw-Hill.

Prospect theory and sunk costs

Critiques of heuristics and biases
• Gigerenzer
• Lopes
• Hogarth

Gerd Gigerenzer: People are
frequentists
Gigerenzer, G. (1991). How to make
cognitive illusions disappear: Beyond
"heuristics and biases. European
Review of Social Psychology, 2, 84-115.
Gigerenzer’s critique

Conjunction fallacy revisited
demonstrations.
Which is more likely:
1. Linda is a bank teller.
or
2. Linda is a bank teller and is active in the feminist movement.
85% of 142 college undergraduates said statement 2 was more
likely than statement 1.

Conjunction fallacy revisited
demonstrations.
There are 100 persons who fit the description above. How many of
them are
(a) bank tellers
(b) bank tellers and active in the feminist movement.
22% of 44 subjects said statement b was more likely than a.

Base rate fallacy
If a test to detect a disease whose prevalence is 1/1000
has a false positive rate of 5%, what is the chance that
a person found to have a positive result actually has the
disease, assuming you know nothing about the person’s
symptoms or signs?
– 60 students and staff at Harvard Medical school
– Almost half judged the probability to be .95
– Only 18% responded .02 (the correct answer).
(Note that true positive rate was not given.)
Bayesian belief updating

Base rate fallacy revisited
One out of 1000 Americans has disease X. A test has been
developed to detect when a person has disease X. Every time the
test is given to a person who has the disease, the test comes out
positive. But sometimes the test also comes out positive when it it
given to a person who is completely healthy. Specifically, out of
every 1000 people who are perfectly healthy, 50 of them test
positive for the disease.
Imagine that we have assembled a random sample of 1000
Americans. They were selected by lottery. Those who conducted
the lottery had no information about the health status of any of
these people. How many people who test positive for the disease
will actually have the disease? ______ out of _______

Base rate fallacy revisited
One out of 1000 Americans has disease X. A test has been developed to detect
when a person has disease X. Every time the test is given to a person who has the
disease, the test comes out positive. But sometimes the test also comes out
positive when it it given to a person who is completely healthy. Specifically, out of
every 1000 people who are perfectly healthy, 50 of them test positive for the
disease.
Imagine that we have assembled a random sample of 1000 Americans. They were
selected by lottery. Those who conducted the lottery had no information about the
health status of any of these people. How many people who test positive for the
disease will actually have the disease? ______ out of _______
The Bayesian answer of .02 (one out of 50, or 51) was
given by 76% of 50 subjects.

Lola Lopes: Results are oversold
By constructing experiments so that
normative theory makes one prediction
and heuristics another, non-
representative designs are created.
Lopes, L. L. (1991). The rhetoric of rationality. Theory & Psychology, 1, 65-82.
Lopes’ critique

Availability demonstration:
Are there more words with r as the first letter or as the
third letter?
Most people say the first letter, but there are many more
words with r as the third letter.
But, there are 20 consonants.
12 are more common in the first position.
8 are more common in the third position.
Availability gives the right answer more often than not!
Lopes’ critique

“We can conclude that people use
heuristics rather than probability theory,
but we cannot conclude that their
judgments are generally poor.” (p. 75)
Lopes’ critique

Robin Hogarth: Beyond discrete biases
I. To dismiss the literature because external
validity has not been demonstrated would be
naive.
II. The more serious criticism is the failure to
specify the conditions under which people do
or do not perform well.
III. This paper focuses on the continuous,
dynamic nature of the judgment task.
Hogarth’s critique
Hogarth, R.M. (1981). Beyond discrete biases: Functional and dysfunctional aspects of
judgmental heuristics. Psychological Bulletin, 90, 197-217.

IV. Importance of feedback
A. Judgment facilitates action which
produces feedback.
1. e.g., motor activities such as driving a car
2. social interaction
B. Discrete judgment studies often use
tasks that are degraded by the absence
of feedback and redundancy.

V. Judgmental accuracy: Analogy of aiming at a
target
1. Highlights two critical dimensions of achievement
a) Degree of commitment
b) Availability and interpretation of feedback are often more
important than predictive ability
2. Prescription - Avoid or reduce commitment and make
good use of feedback (“keep your options open”).
VI. He goes on to argue that heuristics may
work well in dynamic situations.

Bottom line
• Coherence matters, and it cannot be taken
for granted.
• Other than that, heuristics and biases
research has produced no generalizations or
theory, and probably never will.
• For improving judgment and decision making,
that doesn’t matter.
• For guiding research on judgment and
decision making, it does matter.

Improving coherence of judgment
and decision making processes
• Experts should enforce coherence:
– Decide what form of coherence matters
• Logical coherence
• Probability theory
• Other
– Learn how to do it and design an
environment to facilitate coherence

Improving coherence of judgment
and decision making processes
• Laypeople
– Training and changing their environment
may be difficult
– Present information in a way that
encourages coherence.
– For example, Gigerenzer’s work suggest
that weather forecasts should be given as
frequencies rather than probabilities.

Heuristics-biases.ppt

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