Thinking part II
judgment heuristics
reasoning
decision-making
Judgment Heuristics
• Tversky & Kahneman propose that people in many
cases might not reason optimally (e.g. follow rules of
probability or rational choice)
• Instead, judgment may be based on heuristics
• Lower cognitive load but may lead to systematic
errors and biases
• Example heuristics
– representativeness
– availability
Kahneman
Tversky
Memory for Names
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Tom Cruise
Celia Weston
Tom Hanks
Frances O’Connor
Jane Adams
Mel Gibson
Illeana Douglass
Jim Carrey
Marg Helgenberger
George Clooney
Debi Mazar
Alyson Hannigan
Russell Crowe
Harrison Ford
Bruce Willis
Lindsay Crouse
Molly Parker
Brad Pitt
Availability Heuristic
• A person is said to employ the availability heuristic
whenever he/she estimates frequency or probability by
the ease with which instances or associations could be
brought to mind
Availability Heuristic
• Are there more words in the English language that begin
with the letter V or that have V as their third letter?
• What about the letter R, K, L, and N?
(Tversky & Kahneman, 1973)
Which causes more deaths in developed countries?
1.
(a) traffic accidents
(b) stomach cancer
2.
(a) homicide
(b) suicide
(Kahneman & Tversky, 1974)
Results
• Traffic accident vs. Stomach cancer:
– Typical Guess (in 1974)
traffic accident = 4X stomach cancer
– Actual (1974 estimates)
45,000 traffic, 95,000 stomach cancer deaths in US
– Ratio of newspaper reports on each subject
137 (traffic fatality) to 1 (stomach cancer death)
• Actual Homicide vs. Suicide rates (2013):
– Murder rate 6 per 100,000
– Suicide rate 10.8 per 100,000
(Kahneman & Tversky, 1974)
(Lichtenstein et al., 1978)
Why use the availability heuristic?
• Availability is based on fundamental aspect of memory
search
• Works well under many circumstances
– Availability correlates with likelihood of events
A hospital is surveyed about the exact sequence of births of
boys and girls (from different mothers) in a particular day.
What is more likely:
a) G B G B B G
b) B B B B B B
Another example
A coin is flipped. What is a more likely sequence?
A) H T H T T H
B) H H H H H H
Representativeness Heuristic
• The sequence “H T H T T H” is seen as more
representative of or similar to a prototypical coin
sequence
Linda is 31 years old, single, outspoken, and very bright.
She majored in philosophy. As a student, she was deeply
concerned with issues of discrimination and social justice,
and also participated in anti-nuclear demonstrations.
Please choose the most likely alternative:
(a) Linda is a bank teller
(b) Linda is a bank teller and is active in the feminist
movement
Conjunction Fallacy
• Nearly 90% choose the second alternative (bank teller
and active in the feminist movement), even though it is
logically incorrect (conjunction fallacy)
bank tellers
bank tellers
who are not
feminists
feminists
feminist bank tellers
feminists
who are not
bank tellers
Kahnemann and Tversky (1982)
Representativeness heuristic
• Kahneman and Tversky (1982) explained these results
using the representativeness heuristic
– tendency of people to judge probabilities or
likelihoods according to how much one thing
resembles another
• Linda is more representative of a feminist bank teller
than just a bank teller alone, so people give the second
answer
Hot Hand Belief in Basketball
• Question:
– Does a basketball player have a
better chance of making a free
throw shot after having just
made his last two shots than he
does after having just missed
his last two shots?
• Answers by Cornell and Stanford
University Basketball fans
– Yes = 91%
– No = 9%
(Gilovich, Vallone, & Tversky, 1985)
Does the “hot hand” phenomenon exist?
• Most basketball coaches/players/fans refer to players
having a “Hot hand” or being in a “Hot zone” and show
“Streaky shooting”
• However, making a free throw shot after just making two
free throw shots is just as likely as after just missing two
shots
 people can make errors in judging probabilities of
sequential events
(Gilovich, Vallone, & Tversky, 1985)
What to make of these results?
• One interpretation of Tversky & Kahneman’s findings:
– people do not use proper probabilistic reasoning
– people use arbitrary mechanisms/ heuristics with no
apparent rationale
• However, heuristics can often be very effective
Which city has a larger population?
A) San Diego
B) San Antonio (TX)
• 66% accuracy with University of Chicago undergraduates.
However, 100% accuracy with German students.
• San Diego was recognized as American cities by 78% of
German students. San Antonio: 4%
 With lack of information, the heuristic of picking the city
that is recognized is very effective
(note: at the time of the experiment, San Diego actually was the larger city – this is no longer true)
(Goldstein & Gigerenzer, 2002)
Decision Making
• In making choices, people are sensitive to outcomes and
to degrees of risk.
• However, people are also heavily influenced by how a
decision is framed.
• When cast in terms of gains, people tend to avoid any
risk.
• When cast in terms of losses, people seek out risk,
presumably in hopes of avoiding it.
Framing effect
•
Problem 1
Suppose I give you $300, but you also have to select one of
these two options:
(72%)
(A) 1.0 chance of gaining $100
(B) .50 chance of gaining $200 and a .50 chance of gaining
(28%)
nothing
•
Problem 2
Suppose I give you $500, but you also have to select one of
these two options:
(36%)
(A) 1.0 chance of losing $100
(B) .50 chance of losing $200 and a .50 chance of losing
(64%)
nothing
(Tversky & Kahneman, 1986)
Framing effect
• Problem 1:
– Select one of two prizes
(36%) An elegant Cross pen
(64%) $6
• Problem 2:
– Select one of three prizes
(46%) An elegant Cross pen
(52%) $6
(2%) An inferior pen
(Shafir & Tversky 1995)
Example: Cheeseburgers
50%
50%
Example: Cheeseburgers
50%
30%
50%
60%
10%
Mental Accounting
(A) Imagine you are at an electronics store and about to
purchase a pair of headphones for $145 and a calculator
for $20. Your friend mentions though, that the same
calculator is on sale for $10 at a different store located
20 minutes away. Would you make the trip to the other
store?
(B) Now, imagine a different scenario. You are at an
electronics store and about to purchase a pair of
headphones for $20 and a calculator for $145. Your
friend mentions that the same calculator is on sale for
$135 at a different store located 20 minutes away. Would
you make the trip to the other store?
(Thaler, 1999)
Reasoning
• In reasoning, we try to draw implications from our beliefs.
• This is crucial for the use of knowledge and provides
a means of testing our beliefs.
• However, people often show a pattern of confirmation
bias.
• They take evidence more seriously if it confirms their
beliefs than if it challenges them.
Wason Selection Task
E
K
4
7
“If a card has a vowel on one side, then it has an even
number on the other side”
Which cards do you need to turn over to test the correctness
of the rule?
Concrete examples are much easier
• If a person is drinking beer, then the person must be
over 21. How to test whether somebody is abiding by
this rule?
Drinking
beer
Drinking
Coke
16 years
of age
Result: 74% answered correctly
22 years
of age
Confirmation bias in hypothesis testing
• 2-4-8
is a set of numbers that conforms to a rule.
• Discover the rule by querying with any set of three
numbers and I’ll give feedback whether it is a positive or
negative example.
(Wason, 1960)
Confirmation Bias
• Wason (1960): subjects test hypotheses by generating
positive rather than negative examples
• Popper (1959): confirmatory strategies provide
ambiguous information. The hypothesis may be correct
or another hypothesis may be correct  scientists
should try to falsify their theories
(However, in many cases, it might make more sense to
confirm hypotheses, and not to attempt falsification)