Chapter Nine has five objectives:
Chapter Twelve has four objectives:
Describe in detail and give an real-life example of:Availability HeuristicRecognition HeuristicRepresentativeness Heuristic
Understanding Concepts
• Everyday concepts (e.g., “dog,”
“shoe,” “restaurant”) are very
simple categories
• Everyday concepts are
building blocks from which
all knowledge is created.
• Need knowledge in order to
function
2
How Do We Understand Concepts?
Definition Theory of Understanding Concepts:
Understanding a concept is like knowing it
definition
• Knowledge = definitions and criterion (checklist)
How do you know what a “dog” is?
• Always possible to find exceptions!
• Example: a dog that does not bark or that
lost a leg
• Simple concepts do not have all-inclusive
definitions.
3
Family Resemblance
Wittgenstein (1953) argued that many simple
everyday concepts do not have definitions
Proposed Family Resemblance to
Ideal member
understand Concepts
• Members of a category share resemblance
to each other.
Atypical member
• No “defining features” in every family
member
• But “characteristic features” across family
members (feature overlap)
Common features of the family (concepts)
depend on what subgroups you are
considering
4
Prototype Theory of Understanding Concepts
Definition Theory
• Sets boundaries for a category, often not helpful
Prototype Theory
• Different Strategy: Specify the “center” or “ideal” of a
concept not the boundaries
• Specify the Prototype—the category example that
possesses all the characteristic features—and compare
against this ideal to determine category membership
• Based upon individuals experience and prior knowledge
Graded Membership: Objects closer to a prototype are
“better” members of the category than objects further from
the prototype.
• Not a YES or NO question for concept membership
• Example: Some dogs are “doggier” than other dogs.
5
Testing the Prototype Theory: Sentence Verification Task
Testing this theory of Graded
Membership:
Sentence Verification Task
• True or False?
Robins are birds.
Penguins are birds.
• Looking at Reaction Time
• Judgments about items
that are more distant
from the prototype took
more time to make.
6
Testing the Prototype Theory: Production Task
Production task:
• Name as many fruits as you can.
• Name as many birds as you can.
• Name as many carpenter’s tools as
you can
• Furniture, Sports, Vegetables,
Vehicles, and Weapons
• Participants name the most typical
category members first. Start with
the center of the category
• The category members that are
mentioned are also those that yield
the faster response times in the
verification task.
7
Testing the Prototype Theory: Rating Task
• Rate on a 7 point scale how typical each
fruit (or bird) is
• Items that are closer to the prototype are
rated as more typical of the category.
• The more something is like its prototype
the more “privileged” it is
8
Privilege of Typicality
• Graded Membership: Some
Members are “Better” than
Others
• Better members of a concept
are more Privileged
•
•
•
•
•
•
Recognized Faster
Mentioned More Often
Judged to be more Typical
Liked Better
Judged to be more Aesthetic
Selected more Readily
9
Understanding Concepts: Exemplars-Based Reasoning
Exemplars:
• Specific remembered instances of a category
• Examples
Exemplar-Based Reasoning
• In some cases, categorization relies on knowledge about
specific category members (exemplars) rather than the
prototype.
• Is this a “Bird”?
• Think: Memory of all “birds”, (incl sparrows, robins,
ostrich, and my cousin’s pet parrot Archimedes)
• Is new “Bird” close enough Yes! It’s a bird
• Is new “Bird” not even close No! Not a bird
10
Understanding Concepts: Prototype and Exemplar Theories
Yes! Close Enough
New
Info
Standard
No! Not Even Close
Prototype Theory:
•
•
Compare to a Prototype, an Ideal, the average representing the entire category
Economical Representation (Quick Summary of a Concept)
Exemplar Theory:
•
•
•
Compare to an Exemplar, reliable example, whatever comes to mind (different exemplars may come to mind for
different situations)
Include information about variability of concept – Triggers different memories
Easier to adjust categories based on exemplars than prototypes
• Gifts for a 5 year old vs Gifts for a faculty member
11
Prototype and Exemplar Knowledge
12
Concepts as Theories
When using a prototype or exemplar, you rely on a judgment of
resemblance. This accounts for typicality effects and graded
membership.
How do you decide resemblance?
• Completely unrelated objects can share thousands of properties.
• Decisions about which features are important to resemblance still
depend on one’s beliefs about the concept.
That judgment of resemblance depends on other knowledge.
• Which attributes to pay attention to? Which attributes to ignore?
• Depend on other knowledge, such as which attributes are
important and which are not
13
Explanatory Theories
To understand a concept (exemplars and prototypes) also
involve a network of beliefs
• Linking target concept to older already held concepts
Raccoon: to understand this concept have both prototypes and
exemplars but also beliefs:
1. Biological creatures (everything that goes with it)
2. Wild animals (everything that goes with it)
Implicit “Theories” about Concepts we hold:
• Set of beliefs
• Not necessarily sophisticated (or true!)
• Provide knowledge needed to make decisions to guide
resemblance
• Help us understand new facts
14
Concepts and the Brain
Neuroscience evidence that different concepts
are represented by different areas of the brain
• fMRI scans showed different brain regions
activated when people think about living
animals versus nonliving tools
• (Chao, Weisburg, Martin, 2002)
• Another fMRI showed different brain regions
for manufactured objects (tools) and natural
objects (fruit/rocks)
• (Gerlach, Law, Parsons, 2002)
Conceptual Knowledge: Neuroscience Evidence
Anomia:
• Inability to recognize or
answer simple questions
about common objects
• Conceptual Based
• Living Things OK but
Nonliving Things lost
• Persons
• Animals
• Tools
16
Knowledge Network
Memory best represented by a vast network of
schemas of similar information (nodes)
connected to each other
Knowledge is also best represented by a vast
network of connections and associations among
all the relevant bits of information you know.
Spreading Activation: A process where
activation travels from one activated node to
another in a network via the associative links
17
Knowledge Network
Sentence Verification Task: Evidence for
knowledge representation in a network
Participants must decide (T/F) as quickly as
possible. With obviously false sentences
mixed in.
• Robins are birds.
• Robins are animals.
• Cats have hearts.
• Cats are birds.
Collins and Quillian (1969)
• Principle of Nonredunancy
• Can predict the speed of knowledge
by counting associative links
Knowledge Network
Knowledge as a Propositional Network
Propositions: the smallest unit of
knowledge that can be either true or false
Knowledge of Dogs
Propositional Network:
Model of knowledge as a network of
interconnected propositions
• Nodes are propositions
• Propositions are connected to concepts
(Dog, Chase, Cat) by association links
• Associations links have:
• A direction
• A specific role (Agent, Relation,
Object) within the proposition
20
Knowledge as a Propositional Network
Propositional Network
representing Episodic
Knowledge
21
Artificial Intelligence through Distributed Processing
Propositional Networks
• Local Representation: Each node is equivalent to one concept or idea.
Connectionist Networks:
• Distributed Representations: Each idea is represented by a pattern of
activation that’s distributed across an entire network, not a single set of
nodes.
Parallel Distributed Processing (PDP)
• One pattern of activation (an idea) can smoothly trigger the next
• The brain relies on parallel processing – Speed!
• Learning is based on adjustments of connection weights among nodes.
• Very powerful, impressive models in computers, based on learning can
generate new patterns
Connectionism: An approach in Cognitive Psychology to attempt to explain
mental phenomena using artificial neural networks
CHAPTER 12
Judgment and Reasoning
Mental Set: Heuristics
Automatic, Non-Conscious Mental
Short Cuts
Simple Strategies: “Quick and Dirty”
1.
2.
Examples:
Recognition Heuristic
Availability Heuristic
Heuristics: Judgment Under Uncertainty
Judgment: The process through which people draw conclusions from
the evidence they encounter.
Evidence (Data) is provided through Experience and Prior
Knowledge
Judgements are made on the available data. You do not have ALL the
required data to make a perfectly informed judgement. How could
you??
Make decisions based upon what is available and easily accessed to
make judgements. This is a pretty good strategy! Works very well
most of the time!
What is amazing is that people make decisions in a similar way and
make the same errors in judgement!
Thinking (Abstract, Subjective, Personal) can be studied and
predicted!
3
How Do Heuristics Work?
Heuristics: Attribute Substitution
Availability Heuristic:
What is more likely: Words starting with the letter “K”
or words with “K” in the third position?
Availability Heuristic Frequency
Do not have all the data you need to make an informed
decision you base your judgement on what is available to
you. Often NO direct access to frequency information in life
Not a bad way to go! “If examples of phenomena leap to mind
Phenomena must be commonplace. If I am struggling to
find examples Must be a rare event”
4
Heuristics: Attribute Substitution
Attribute Substitution: Strategy of relying on easily assessed information as a
proxy for unavailable needed information
Availability Heuristic:
Base Judgements of Frequency (Needed Info) on Available Info (Proxy Substitute)
5
How Do Heuristics Work?
Heuristics: Attribute Substitution
Recognition Heuristic:
Which wine are you more likely to buy?
Recognition Heuristic Value or Importance
Base Judgements of Value or Importance (Needed Info) on Recognition
(Proxy Substitute)
Brand Recognition
Sports Betting
6
How Do Heuristics Work?
Heuristics: Attribute Substitution
Representativeness Heuristic:
Which of these men are more likely to be a college professor?
Representativeness Heuristic Probability
Base Judgements of Probability (Needed Info) on Representativeness
(Proxy Substitute)
Prototype and Family Resemblance Guides Judgements
Stereotypes
Hiring Job Applicants
Choosing Romantic Partners
Representativeness Heuristic: Category Homogeneity
Out Group Homogeneity Effect:
In-group someone belongs to is remarkably
diverse but an out-group is all the same
Gambler’s Fallacy:
If a coin toss results in heads six times in a
row, what are the odds of getting tails the
seventh time?
If coin is fair than any series of tosses should
contain roughly equal numbers. If no tails have
appeared for a while then tails is due
Detecting Covariation
Covariation: X and Y
“covary” (aka correlation)
Relationship can be
negative or positive and
can vary in strength
Positive Correlation: Two
variables go in same
direction: As X increases
so does Y
Negative Correlation: Two
variables go in opposite
direction: As X increases Y
decreases
9
Illusions of Covariation
Detecting Covariation an important part of
decision making! What you need to consider
cause and effect.
People routinely detect covariation even when
there is none
Incorrect perceptions that one variable predicts
another
• Example: Many people incorrectly believe in
a causal relationship between a person’s
astrological sign and their personality.
What causes this? Confirmation Bias: tendency
to be more responsive to evidence that confirms
one’s beliefs than evidence that challenges them.
10
Illusions of Covariation: Present/present bias
• Failing to think about what we
cannot see:
• Present/present bias
• An over importance or focus on
singular “Hits” and not many
“Misses”
• “Psychic Texts” Example
• Horoscopes
• Related: Hindsight Bias
Illusions of Covariation: Confirmation Bias
• Focusing on the evidence we like best
• “Cherry-Pick” information that supports
what we already think
• “We see what we want and disregard the
rest”
• A powerful bias!
• People often choose hypothesis-confirming
survey questions
• Psychologists MUST be careful!
Illusions of Covariation: Neglecting Base-Rates
Base-rate information—information about general frequency of a category
or an occurrence
Neglecting base-rate information can lead to inaccurate estimates of
covariation.
Kahneman and Tversky (1973)
Base-rate information: 70 lawyers and 30 engineers
Diagnostic information (engineering stereotype): “likes carpentry, sailing,
math puzzles; dislikes politics”
Base-rate neglect is partly a consequence of attribute substitution.
Reliance on the representativeness heuristic
13
Illusions of Covariation: Neglecting Base-Rates
Kahneman and Tversky (1973)
Names of 100 engineers and lawyers are written on cards and
put in a container A and B.
Container A: 70 Engineers and 30 Lawyers
Container B: 30 Engineers and 70 Lawyers
What is the probability of picking an engineer from Container A
and B?
14
Illusions of Covariation: Neglecting Base-Rates
Kahneman and Tversky (1973)
Names of 100 engineers and lawyers are written on cards and put in a container
A and B.
Jack is a 45 year old man. Married and has four children He is generally
conservative, careful and ambitious. He shows no interest in politics or social
issues and spends most of his free time oh his many hobbies. His hobbies include
home carpentry, sailing, mathematical puzzles and generally building things.
What is the probability Jack in an Engineer?
Where did the base rates go??
Base-rate neglect is partly a consequence of attribute substitution.
Reliance on the representativeness heuristic
15
Dual-Process Models
Sometimes human judgment rises above heuristics,
however.
In some contexts, people seek out more accurate
base-rate information, are sensitive to sample size
and potential sources of bias, and so on.
Dual-Process Models: propose that people have
two distinct ways of thinking about evidence that
they encounter.
Type 1: fast and automatic thinking
• Reliance on heuristics
Type 2: slower, effortful thinking
• More likely to be correct
16
The Cognitive Reflection Test (CRT)
17
Logic and Reason
Errors in logical reasoning happen all the time
• Categorical Syllogisms: logical arguments
containing two premises and a conclusion
• Valid Syllogism: Two premises are true as
well as conclusion
• Invalid Syllogism: Conclusion does not
follow two previous premises
The Four-Card Task
Conditional Statements: “If X, then Y.”
The first statement (X) provides a condition under which the second statement (Y) is
guaranteed to be true.
Psychologists study conditional reasoning using the Selection Task or Four-Card Task
Participants are told each card has a letter on one side and a number on the other. The task
is to evaluate this conditional statement: “If a card has a vowel on one side, then it must
have an even number on the other side”
Which cards must be turned over to test this conditional statement?
19
The Four-Card Task
20
The Four-Card Task
“If a person is drinking beer, then the person must be over 21 years of age.”
What cards would you turn over to test this conditional statement?
Decision Making
Decision Making = Making Choices
Principle of Utility Maximization:
• Choosing the option with the greatest expected
value
• Balance of costs and benefits
Decisions not always made according to utility
maximization
Humans do not always make rational choices!
Lots of examples where decisions are not guided by the
principle of utility maximization
22
Framing of Outcomes
23
Framing of Outcomes
24
Framing of Outcomes: Risk-Seeking vs Risk-Adverse
25
Emotional Reasoning
People’s decisions are powerfully influenced by emotion!
Assessment of risk in emotional terms
Use of Somatic Markers to evaluate options
• Reliance on “gut feelings” may favor options that trigger
positive feelings
The orbitofrontal cortex is essential for the evaluation of
somatic markers.
Patients with damage to that area will make risky decisions.
Predicting Emotions
Affective Forecasting: predictions for your
own future emotions
Example: “How would you feel after breaking up
with your romantic partner, receiving a gift,
scoring well on an exam, failure to receive a
promotion?”
People can usually predict whether their reaction
would be positive or negative
But they are often inaccurate as to the duration
of the feelings. Consistently overestimating how
long these feelings will last
People also overestimate how long their
current feelings will last as well
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