Chapter 1– Selective Perception
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Transcript Chapter 1– Selective Perception
The Psychology of Judgment
and Decision Making
Ahmed Abbasi
Jessica Bagger
Daning Hu
Xin Li
Jon Marthaler
Nicole Forsgren Meek
Matthew Pearsall
David Shimko
Tao Wang
Jerod Wilkerson
November, 10 2004
Chapter 1: Selective
Perception
Summary
Perceptions are heavily influenced by what
we expect or hope to see
Given past experiences and/or future
desires, two people who are looking at the
same thing may perceive it in very
different ways
Example
Most people do not see
that this card is actually a
black three of hearts–
they see it as a regular
three of hearts or spades.
Typical quote from an experiment subject
confronted with this card: “I can’t make the
suit out, whatever it is. I don’t know what
color it is now or whether it’s a spade or
heart. I’m not even sure now what a
spade looks like!”
Lesson
“Perceptions are heavily
influenced by what we expect
or hope to see.”
Chapter 2: Cognitive
Dissonance
Summary
Cognitive dissonance is a difference between
our motives and our actions (psychological
inconsistency)
People are usually motivated to reduce or avoid
psychological inconsistencies
It has been suggested that people only discover
their own attitudes and other internal states by
watching themselves behave
Takes two forms: predecisional and
postdecisional dissonance
Example
Famous study from Stanford University:
Undergraduates were required to do extremely tedious
tasks for an hour
They were then paid either $1 or $20 to tell a waiting
student that the tasks were very enjoyable, then asked to
evaluate how enjoyable they themselves found the task
Those that were paid $1 rated the tasks as much more
enjoyable!
The students who were only paid $1 felt the need to
rationalize their behavior. Those who were paid $20
already had their (monetary) motivation in hand and thus
felt no such need to rationalize.
Lesson
“People may reconstruct their
motives to reduce cognitive
dissonance.”
Chapter 3: Memory and
Hindsight Biases
Summary
Memory is not a storage chest where we
deposit memories for later recall
Memories are constructed at the time they
are recalled (they are not copies of past
experiences)
People fill in missing details with logical
inferences and associated memories
People are subject to hindsight bias (I
knew it all along)
Examples
Close your eyes and recall a scene in which you
experienced something pleasurable. Did you see
yourself?
When people viewed accident film clips, their estimates
of car speed varied based on how the question was
worded (How fast were the cars going when they “hit”
verses “smashed” each other?)
People who were asked about the cars “smashing” each
other also remembered seeing broken glass (but there
was no broken glass)
People recalling a recorded discussion two weeks later
omitted more than 90% of the specific points and almost
half of what they remembered was substantially incorrect
Lesson
“Don’t believe everything you
remember.”
Chapter 4: Context
Dependence
Summary
Four types of context dependence effects:
1. The Contrast Effect - Comparison of objects to other
similar objects influences our perception
2. The Primacy Effect - First impressions affect our
judgments more than later impressions
3. The Recency Effect - Our judgments can be more
affected by things we heard recently (counteracts
primacy effect)
4. The Halo Effect - Favorable impressions of one trait
result in increased impressions of other traits
Examples
Contrast: Shapes compared to similar shapes of
significantly different sizes changes our perception of the
original shape’s size (the effect diminishes as the
similarity of the shapes is reduced)
Primacy: When people were given a list of
characteristics of someone, the items early in the list
affected their judgment of the person more than the
items later in the list
Recency: When subjects were presented with court
transcripts with pro or con sides first and the other last,
their judgments reflected a recency effect when there
was a delay between hearing the two sides of the case
Halo: Flight commanders showed a correlation between
ratings of subordinates’ intelligence and physique
Lesson
“Our judgments are based
partly on the context in which
we make them (there are no
absolutes).”
Chapter 5: Plasticity
Summary
The way questions are asked affects the answer
Question wording
Question or alternative order
On unfamiliar issues, people often give pseudoopinions (opinions when they actually have no
opinion)
Can filter pseudo-opinions out by listing “no-opinion”
as a possible response, or by asking them if they
have an opinion before asking the real question
People often demonstrate inconsistencies
between their attitudes and their behaviors
Examples
In a Tide magazine survey 70% of
respondents gave an opinion on a piece of
fictitious legislation (the Metallic Metals
Act)
Darley and Batson found a significant
inconsistency between seminary students’
attitudes about being a “Good Samaritan”
and their actions (attitude didn’t affect
actions, but whether they were in a hurry
did)
Lesson
“Beliefs and behaviors are
flexible, depending on factors
unrelated to the belief.”
Chapter 6: The Effects of
Question Wording and
Framing
Summary
Question wording affects the response
Use of “forced choice” questions
Open vs. closed questions
Word choice
Social Desirability
Framing affects the response
Wording in terms of a gain vs. a loss
Decision makers frame choices and outcomes
Examples
Vietnam troop withdrawal survey was reversed
when respondents were given a middle category
Average number of reported headaches was
higher when preceded by a question asking if
respondents get them “frequently” vs.
“occasionally”
27% of respondents endorsed opposite sides–
in the same survey—of a nuclear freeze
question when both question were worded in a
socially desirable way
Lesson
“Survey results must be
interpreted very carefully (ask:
What answer did the surveyor
want?).”
Chapter 7: Expected
Utility Theory
Summary
Expected utility theory is intended to describe how
people would behave if they followed certain principles of
rational decision making.
Six principles
Order of alternatives
Dominance
Cancellation
Transitivity
Continuity
Invariance
Extensions of expected utility theory
Subjective expected utility theory (decisions can be based on
subjective probabilities)
Stochastic models (preference for soup one day and salad the
next)
Examples
St. Petersburg Paradox
Daniel Bernoulli’s utility and wealth
relationship model: by assuming that the
value of additional money declined with
the wealth, Daniel Bernoulli was able to
show that the expected utility of the St.
Petersburg game was not infinite after all
Lesson
“People often make irrational
decisions.”
Chapter 8 : Paradoxes in
Rationality
Summary
Violations of the Cancellation Principle and
the Transitivity Principle of expected utility
theory
Violations of expected utility theory don’t
mean that the way people make decisions
is unreasonable
Examples
Decision rules for recruiting
Rule 1: if the difference in intelligence between any two
applicants is greater than 10 points, choose the more intelligent
applicant
Rule 2: if the difference in experience between two applicants is
equal to or less than 10 points, choose the applicant with more
experience
Intelligence
Experience
A
120
10
B
110
20
C
100
30
Lesson
In the real world, there are many cases in which
decision makers violate the principles of
expected utility theory
The approximations subjects follow in order to
simplify the difficult task of bidding might prove
to be rather efficient, in the sense that they
reduce cognitive effort and lead to outcomes not
too different from the results of optimal
strategies
Expected utility theory does not adequately
describe how people make decisions
Chapter 9 : Descriptive
Models of Decision Making
Summary
Prospect theory
Replaces the notion of “utility” with “value”
The value function for losses is convex while the value
function for gains is concave
Recognized as extended version of classical expected
utility theory
Regret theory
Two assumptions
Many people experience the sensations called regret and rejoicing
In making decisions under uncertainty, people try to anticipate and take
account of those sensations
Reaches the same conclusion, risk aversion, as
predicted by prospect theory
Add a new variable, regret, which could explain a lot of
the paradox
Examples
Kahneman and Tversky’s
experiment, 1979
Experiment 1 design
Alternative A: a 50 percent
chance of gaining $1000
Alternative B: a sure gain of
$500
Experiment 1 result
Of the 70 respondents who
were given this problem, 84
percent chose the sure
gain.
Experiment 2 design
Alternative C: A 50 percent
chance of losing $1000
Alternative D: A sure loss of
$500
Experiment 2 result
Nearly 70 percent of those
surveyed chose the risky
alternative
Lesson
The first thousand dollar gain has more
value than the second thousand dollar
gain
If an outcome is viewed as a gain, the
decision maker will tend to be risk averse;
on the other hand, if the outcome is
viewed as a loss, the decision maker will
be risk seeking
Chapter 10 : The
Representativeness
Heuristic
Summary
Heuristics are “rules of thumb” that can be useful
time saving estimators, but often lead to biases.
Representativeness: When people judge
probabilities “by the degree to which A
resembles B” people feel that the more specific
event is more probable than the more general
event.
Biases usually occur when people ignore base
rates, which is the relative frequency with which
an event occurs.
Examples
Linda the bank teller:
Alternatives:
Linda is a bank teller
Linda is a bank teller and is active in the
feminist movement
Results: nearly 9 out of 10 respondents
chose the second alternative
Biases: Readers believe that it is more
likely that Linda is both a bank teller and
feminist than just a bank teller.
Lesson
Don’t be misled by highly detailed
scenarios.
Pay attention to base rates.
Be skeptical about the conclusions
you arrive at from the heuristic
Chapter 11: The
Availability Heuristic
Summary
The availability heuristic – a rule of thumb
in which decision makers assess the
frequency of a class or the probability of
an event by the ease with which instances
or occurrences can be brought to mind
Availability leads to biased judgments
when examples of one event are
inherently more difficult to generate than
examples of another
Examples
Tversky and Kahneman’s experiment
Experiment question: In a typical sample of text in the
English language, is it more likely that a word starts
with the letter K or that K is its third letter (not
counting words with less than three letters)?
Experiment results: of the 152 people who were
asked this question, 105 thought that words with the
letter K in the first position were more probable.
Which is more the likely cause of death in the
United States – a car accident or stomach
cancer?
Lesson
The availability heuristic is the central
probability and frequency estimator among
all heuristics.
In some cases, the availability heuristic
leads to critical biases in judgment.
One way to correct this problem is by
explicitly comparing over- and
underestimated dangers with threats that
are misperceived in the opposite direction.
Chapter 12 : Probability
and Risk
Summary
Probability and risk are everywhere
Risk is often difficult to quantify
Probability estimates are also influenced
by the “valence” of an outcome
Examples
David Rosenhan and
Samuel Messick’s
experiment, 1966
Question: Subjects
were asked to guess
on each of the 150
trials whether the card
would show a smiling
face or a frowning face
when it was turned
over.
Results ?
Experiment
One
Experiment
Two
Smiling
70
30
Frowning
30
70
68.2
57.5
guessing
Lesson
Maintain accurate records
Beware of wishful thinking
Break compound events into simple
events
Chapter 13 : Anchoring
And Adjustment
Summary
Coined by Tversky and Kahneman to explain a
phenomenon in their research in 1974.
When asked, is the percentage of African
countries in the UN higher or lower than a
certain number:
If the number was 65%, the average estimate would
be 45%
If the number was 10%, the average estimate would
be 25%
Insufficient adjustment up or down from an
original starting value
Examples
Mathematical predictions
Quick estimate of 8 x 7 x 6 x 5 x 4 x 3 x 2 x 1
The average estimate is 2250
Quick estimate of 1 x 2 x 3 x 4 x 5 x 6 x 7 x 8
The average estimate is 520
The correct answer is 40,320
Lesson
When creating a questionnaire, it is
important to avoid anchoring.
If you are to use an anchor, use both a low
and a high anchor.
Not avoiding suggested values will likely
produce judgment bias.
Chapter 14 : Randomness
Summary
Belief in Randomness
Research shows that people will see an
ambiguous series of events as being more
structured than it really is.
Unlikely events can be seen as acts of God or
miracles.
People have a hard time behaving randomly,
but it can be learned.
Examples
An example from the book was a George D
Bryson that booked into a hotel to find that the
previous tenant was also named George D
Bryson.
One may say that the chances of that happening is
one in a million.
However, is likely that two successive occupants of
some room in some hotel in some city at some point
will have the same name.
Take any of the variables away and the probabilities
drop dramatically.
Lesson
It is important to:
keep in mind that coincidences do occur.
attempt to avoid seeing patterns that do not
exist.
state probabilities in the proper context
Chapter 15: Correlation,
Causation, and Control
Summary
Most people have difficulty assessing covariance
Uneventful events – events that do not occur are
equally important in understanding relationships
between variables
Illusory Correlation – attributing correlation
between 2 unrelated variables.
Invisible Correlation – failure to see relationship
that exists between 2 variables.
Causalation – the inferential leap that correlation
= causation.
Examples
Uneventful Events
Sherlock Holmes and “The Silver Blaze” mystery
Illusory Correlation
Use of inkblot tests to detect male homosexuality
(Chapman and Chapman, 1969)
Invisible Correlation
College students could not detect relationship until
correlation values were extremely high (Jennings et. al 1982)
Causalation
Advertising almost doubles your ROI
Lesson
Very pertinent to analyzing experimental
results. Must beware of:
Assigning relationships between variables
where none exist
Failing to detect relationships
Assuming relationship means causality
Chapter 16: Attribution
Theory
Summary
Analysis of Variance Framework (Kelley 1967)
Consensus, Distinctiveness, and Consistency used
for attribution
Problems (Attribution Biases)
Consensus information (base rate) ignored.
Studies show that more available, vivid, and salient events
appear to have greater probability and causality
Fundamental Attribution Error
Bias of dispositional factors (abilities, traits) over situational
factors (temperature, time)
Other Biases
Self-serving bias – (success=me, failure = you)
Ego-centric bias – accepting greater credit for joint task
Examples
Fundamental Attribution Error
Good Samaritan?
Observers attributed helping behavior to
religiousness (dispositional) rather than
hurriedness (situational)
Power of Salience
Two Man Conversation
Six observers in 3 vantage points used visual
salience as criteria for determining whom “set the
tone” of the conversation
Lesson
Avoid attribution biases:
Pay attention to consensus data and base
rates
Look for hidden causes (such as question
framing)
Chapter 17: Social
Influences
Summary
Because people are social by nature, their
judgments and decisions are subject to
social influences
Some of these influences will not affect
underlying judgments, but will influence
decisions
Subjects can be influenced without
recognizing it
Examples
Social facilitation
Pool playing
Social loafing / Diffusion of responsibility
Tug-of-war
Bystanders
Social Comparison
GroupSystems comparison line
Groupthink
Bay of Pigs
Conformity
Asch comparison lines
Lesson
Be consciously aware of the influence that
others will have on your subject’s responses
To avoid groupthink
Group leaders encourage criticism – appoint a “devil’s
advocate”
Group leaders should not state preferences
Group members should discuss deliberations with
others and report back to the group
Invite outside experts or qualified colleagues
Chapter 18: Group
Judgments and Decisions
Summary
Individual biases also present in groups,
such as “group attribution error” and
“group-serving bias”
Strong in-group, out-group effects
Groups tendencies are often polarized
leading to “risky shift”
Group performance depends on
aggregation method
Examples
“Risky shift:” Group members perceive
events as more or less risky than
individuals after discussion depending on
group composition
Lesson
Things to remember:
Group discussion generally amplifies existing
tendencies
Groups generally perform better than the
average individual in the group
Groups generally perform worse than the best
member of the group, depending on task
Group leadership style influences
performance
Chapter 19:
Overconfidence
Summary
Overconfidence is a belief in ability or
understanding that adversely affects a
decision
People are usually overconfident
regarding their judgments, especially if
correct judgments are hard to make
Usually happens when accuracy is near
chance level
Examples
Experimental settings: When rating own
accuracy levels, psychologists, grad
students & undergrads all overstate their
accuracy level
Space Shuttle Challenger Accident
(January 28, 1986)
Attack on Pearl Harbor
(December 7, 1941)
Lesson
Consistent decision feedback can reduce
effects of overconfidence
When working with model, system, etc.,
never assume it is perfect; always look for
problems or bugs to make improvements
Although you may have uncovered what
you believe is “cause and effect,” don’t
generalize to broadly (don’t be too
confident that your results generalize)
Chapter 20: Self-fulfilling
Prophecies
Summary
Self fulfilling prophecy is a false
definition of the situation evoking new
behavior which makes the originally
false conception come true
People seek confirming evidence rather
than disconfirming evidence
Hard to get rid off
Examples
If you expect some students to be the
high achievers, the extra attention they
receive from you will help them achieve
more on average
Male subjects who thought they talked
with a physically attractive woman
judged her as more sociable, humorous,
etc.
Lesson
Be aware that your behavior may
influence your research in the direction
that you want it to (e.g., Pygmalion Effect)
Be aware that you may pay more
attention to the evidence that supports
your hypotheses (even if unconsciously)
Chapter 21: Behavioral
Traps
Summary
A situation where individuals or groups
embark on a course of action that later
becomes difficult to escape from. There
are 5 general types:
Time delay traps
Ignorance traps
Investment traps
Deterioration traps
Collective traps
Examples
Time delay – nighttime guy vs.
morning guy
Ignorance – DDT
Investment – sunk costs
Deterioration – heroin addiction
Collective traps – prisoner’s
dilemma, tragedy of the
commons
Lesson
Gather information about the costs
of entrapment
Set limits and reevaluate costs of
continuing
Do not make commitment to
continue
Do not allow irrational feelings to
escalate commitment or evaluate
outcomes