Transcript No Slide Title

• Write down all the sports you can think of
• Provide a definition of the word ‘cup’
• List items you would take out of your house in
case of fire
• In the movie ‘Face off’, Nicholas Cage gets John
Travolta’s face. Does he become John Travolta?
(‘Big’)
• Is the next animal a bird? (yes/no)
– Name the race of the following celebrities
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Britney Spears
Michael Jackson
Ghandi
Michael Jordan
Yo Yo Ma
Yao Ming
Course Overview
Acquisition
(perception)
ch. 3: Vision. How are
objects recognized?
-It looks easy but it’s not
ch.4: Attention.
-Filters perceptual input
Knowledge
Ch. 6-11: Memory
- to know is
to remember
Types of Knowledge
- Concepts & categories
- Visual Knowledge
- Language
ch. 5: Working Memory - Deficits & Errors
- Buffer for mental
representations
The Brain
Use
Ch. 12-14:
Reasoning
- inductive
- deductive
Problem Solving
Ch 4:Executive
Functions
Concepts & Categories
• What is a concept? Why are concepts useful?
• The structure of concepts (rules that guide how/why
things are clustered into certain categories)
– Similarity-based views
• The Classical view
• Probabilistic Views
– Prototypes
– Exemplars
– Theory-based views
• Essence
• Errors and Stereotypes
What is a concept?
• Part of semantic memory (vs. episodic memory)
• A class of items that seem to belong together
– ‘dog’, ‘balloon’, ‘terrorist’ (things)
– ‘tall’, ‘ugly’ (properties)
– ‘walk’, ‘jump’ (actions)
• A mental construct (vs. the outside world)
• Abstract knowledge
Why are concepts useful? Functions
• Coding of experience: Classification of items as
members of the same category
– Reduces cognitive demands
– Facilitates communication
– Inductive Inferences
• Natural kinds vs. artifacts
– Combines to create complex categories
• Contact lens
• Digital Camera
The structure of concepts
• How are things
clustered into
categories?
• Based on similarity
• Based on theories
Similarity-based views
• Classical view (inadequate)
• Probabilistic view
– Prototypes
– Exemplars
What does it mean to know what a ‘dog’ is?
• Classical View:
– To know what a ‘dog’ is, is to know its definition.
– Dog = mammal, four legs, barks, wags tail
– These properties are
• Singly necessary: every member must have them
• Jointly sufficient: everything that have them is a member
– Categories have sharp boundaries
• Either you are in or you are out
– Categories have a homogeneous space
• Everyone that is ‘in’ is equally good member of the category
• Classification => compare properties of instance to definition
Classical View: Problems
• Good definitions are hard to find!
• Example: A bachelor is an unmarried man
– is my kid a bachelor?
– is the pope a bachelor?
Adult
intention to get married
• Some members are more typical than others
(Categories have internal structure)
“DOG”
“DOG?”
Classical View: Problems
• Good definitions are hard to find! (games, Wittgenstein)
• Typicality effects (tea cup vs. Stanley cup)
• Solution:
– There are no defining properties, but rather
– properties characteristic of the group (typical features)
• A prototype:
– contains salient features that are true of most instances
– is an abstract representation that could:
• Be the average of several instances
• Have the most frequent features, or
• Be the ideal
• Prototype Theory (Rosch)
– specify the “center” of the category,
– leave ‘fuzzy’ boundaries
– graded category membership (tea cup vs. Stanley cup)
• Classification => comparison to prototype
Evidence Consistent with Prototype View
1. Production
Robin mentioned before Penguin
2. Sentence verification
RT [Robin is bird] << RT [Penguin is bird]
Further Evidence for Prototype View
3. Picture Identification
Sparrow identified faster than ostrich
4. Induction:
Sparrow have X -> all birds have X
but not Ostrichs have X -> all birds have X
Prototype theory
• ‘On the genesis of abstract ideas’ (Posner & Keele, 1968)
• Stimulus
– Two displays of 25 dots each (Prototypes)
– Variants on each of these two displays (10 dots are randomly
relocated)
• Training Phase:
– Learn to classify variants into two categories
– Items were variants of the prototypes
• Test phase
– Old items
– New Items
• Prototypes
• Variants
Prototype:
Only shown during test phase
Variants:
departures from the Prototype
Their average is the prototype
Some displayed at study and test, others only at test
Training Phase
Prototype (not shown)
Abstraction
Variants
Test Phase
Prototype
Old Variants
Critical comparison: ?
New Variants
Prototypes and Basic Level
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Physical Object
Living Thing
Animal
Mammal
Carnivore
Canine
Dog
Australian Shepherd
things
Superordinate
Vehicle
Furniture
Animal
Truck
Chair
Fish
Pickup Truck
Kitchen Chair
Trout
BASIC
Subordinate
Superordinate: Low similarity within category (low coherence)
Animals look different from each other
Living Thing
Animal
Fish
Plant
BASIC level:
-High similarity within category
All fish look the same
Bird
-Low similarity between categories
Trout
Salmon
Fishes look different from other animals
Subordinate: High similarity between categories (low discriminability)
Different types of fish look similar to each other
Except to Experts
• Properties of the Basic Level Categories
– Maximize within-category similarity
– Minimize between- Category similarity
– Maximum level of abstraction while
maintaining physical similarity
– Shorter name
Basic Level
• “There is generally one level of abstraction at which the most
basic category cuts can be made. ..
• …the basic level of abstraction in a taxonomy is the level at
which categories carry the most information.” Rosch et al. 1976)
• One privileged level
The Exemplar View (Instance Theory)
• Similar to Prototype View
– Representation is not a definition
• Different: Representation is not abstract
– Descriptions of specific examples
• Store in memory numerous examples of each category.
• Categorization => comparison to stored exemplars
• To categorize X is to retrieve the example most similar to X
Exemplar-based explanations of typicality
1. Production
Robin mentioned before Penguin
Robins are encountered more frequently than penguins…
thus, they are more frequently mentioned.
2. Sentence verification
RT [Robin is bird] << RT [Penguin is bird]
More examples of typical birds in memory,
so retrieval of an example similar to robin is more likely.
Exemplar-based explanations of typicality
3. Picture Identification
Sparrow is identified faster than ostrich
More instances of sparrows in memory than of ostriches,
So match will occur fastest for sparrows
4. Induction:
Sparrows have X -> All birds have X
but not Ostriches have X -> All birds have X
Same logic here…more examples of birds will be
similar to sparrow, promoting the likelihood that
people will believe a fact about sparrows is true of
the whole category.
Exemplar-based explanations of other
findings from Prototype theory
5. Prototypes are better categorized than new variants
(Posner & Keele)
Prototypes are ‘similar’ to variants studied in the
training session. Thus, prototypes are better reminders
than non-prototypical new variants
Prototype theory: Problems
1. Lack of sensitivity to within-category variability
12 inch
18 inch
8 inch
12 inch
12 inch
12 inch
The next object is 18 inch long, is it a pizza or a ruler?
Prototype theory: Problems
2. Lack information about correlated features
height
Prototype
Prototype
weight
Prototype theory: Problems
3. Goal-directed & ad hoc categories:
- “Pets, kids, money, photo albums”
-‘Things to take out of the house in case of fire’
- category judgment depends on which exemplars
come to mind. This, in turn,
- depends on context and goals.
Prototype vs. Exemplars: The role of Expertise
-Novice rely on Exemplars (okapi)
-Experts rely on
- prototypes (Posner & Keele), but also on
- specific examples
Exemplar use by Experts
• Subjects: Experts (MDs)
• Task: Visual diagnosis of common skin conditions
• Study Phase
– Incidental priming of certain exemplars
• See 30 slides, with correct diagnoses.
• Decide how typical it is
• Test Phase (2 weeks later)
– Old Items (from same categories)
best performance
– New items from same categories (diseases)
• Different to items in the study phase
• similar to items in the study case
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Conclusions
People probably often represent both prototypes & instances
Experience may favor reliance on prototypes in some cases
But: Instances continue to affect performance even after
expertise has developed
Prototype and exemplar theories depend on the notion of similarity
But Similarity depends on many factors:
- Context: New York City vs. Memphis vs. Buenos Aires
- Theories:
- Accidental Features
- Essential features
And Similarity is not sufficient for categorization
- Goal directed: things to take out in case of fire
- similar things not always go together
Is Similarity sufficient for categorization?
• An object 3 inches in diameter.
– more similar to a quarter
– more likely to be a pizza
Theory-based Approach
• Folk theories highlight which perceptual features are
important and which are accidental
• Objects are classified into concepts that best explain
their attributes.
• Essence: Underlying non-obvious features
– Dolphins and deer are both mammals, even if dissimilar ones
Psychological Essentialism
• People act as though things have essences (underlying natures)
• Change in surface features doesn’t change category membership
• Removing pigeon’s wings or feathers
• Change in essential features DO change category membership
• Changing a pigeon’s DNA structure
• Categorization ultimately based on essence
– Category membership all-or-none
• Essentialist Heuristic:
– Things that look alike tend to share deeper properties.
• Three kinds of concepts
– Natural Kinds (bird, fish, tree, gold)
– Social Kinds (occupation, race, marriage)
– Artifacts (furniture, vehicle, clothing)
Without counting, guess how many dots there are
Less than 22? More than 22?
Concepts and Misconceptions
Concepts and Misconceptions
• Arbitrary Categories
– Over-estimate vs. under-estimate
– In-group favoritism (US vs. them)
• Stereotypes (social categories)
– Blacks, Republicans, Arab Nations
– Stereotypes reduce complexity
– The reduction in complexity leads to errors
Stereotypical biases
• Extreme examples of the category are more heavily weighted
– same is true for some other categories, e.g. trees
• Within-category variability is underestimated
– “all Bush supporters are the same”
• Insensitivity to disconfirmation
– Members who challenge the stereotype are thought to be ‘special cases’
(poor examples of the category). Therefore
– they are thought not to be diagnostic of the category.
– “No women is a good soldier. A good female soldier, is less of a woman”
• Stereotypes are more stable than is warranted by evidence
– test-retest reliability: after one week .94
after 4 years .92
• Illusory correlation
– Distinctive behavior - Distinctive individuals are perceived to ‘go together’
even when they are independent (e.g., antisocial behavior - blacks)
• Misattribution (race – poverty – education- neighborhood)
• Racial stereotypes are thought as ‘essential’ categories
Race and essentialism
• Essence (natural kind)
– An underlying fundamental property
– common to all members of the category, and
– only to members of the category
• Natural kind categories (e.g., ‘dog’, ‘daisy’)
1. Do not change
2. Lead to rich inductive inferences
3. Have an essence, even in the absence of a physical appearance (wolf in
lamb skin)
• Race is a social category, but
1. Does not change (Michael Jackson)
2. Is thought to lead to rich inductive inferences
• race is perceived to be predictive of attributes and behavior
3. It’s thought (erroneously) to have an essence.
• Error: The absence of physical appearance does not negate the race (in nazi
germany, Jews were Jews even if they looked Aryan)
Essentialism in other social categories
• ‘Marriage is between a man and a woman’
Concepts & Categories
• What is a concept?
• Why are concepts useful?
• The structure of concepts
– Similarity-based views
• The Classical view
• Probabilistic Views
– Prototypes
– Exemplars
– Theory-based views
• Essence
• Errors and Stereotypes