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Social Cognitive Processes: Heuristics and Automaticity

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Title: Social Cognitive Processes: Heuristics and Automaticity


1
Social Cognitive Processes Heuristics and
Automaticity
2
Social Information
  • schemas
  • what are schemas
  • what do they do for us
  • some problems with schemas

3
Social Information
  • two pieces to the puzzle
  • content what we think about
  • process how we think about it

4
Making Inferences
  • four phases of inference processes (Fiske, 2004)
  • 1. data collection
  • Example previous serious relationship predicts
    marital success
  • What data do we need? (Nisbett Ross, 1980)
  • married, previous relationship
  • divorced, no previous relationship
  • married, no previous relationship
  • divorced, previous relationship

5
Making Inferences
  • four phases of inference processes (Fiske, 2004)
  • 2. sampling
  • only friends and people you know or a larger
    sample?
  • pay attention to base rates

6
Making Inferences
  • four phases of inference processes (Fiske, 2004)
  • 3. coding
  • separation divorce or ongoing marriage?
  • tend to be misled by extreme values (i.e.,
    outliers)
  • e.g., a person married and divorced six times

7
Making Inferences
  • four phases of inference processes (Fiske, 2004)
  • 4. combining data
  • diagnostic (e.g., previous marriages) vs.
    non-diagnostic (e.g., hobbies, profession)
    information
  • improper weighting of information

8
Processing Social Information
  • two different social goals
  • need to be accurate
  • need to be decisive

9
Processing Social Information
  • two different social goals
  • need to be accurate
  • need to be decisive
  • heuristics simple decision rules for processing
    information and making decisions (i.e., rules of
    thumb)

10
Heuristics
  • look at your answers to the first problem
  • homicide (7.9) vs. diabetes (23.3)
  • digestive system cancer (47.7) vs. motor vehicle
    accidents (16.5)
  • strokes (60.3) vs. all accidents (35.8)
  • all cancers (211.4) vs. heart disease (276.4)
  • (rates are per 100,000 people 1996)

11
Heuristics
  • availability heuristic a judgment based on the
    ease with which they can bring something to mind
  • If I can think of it, it must be important.

12
Heuristics
  • availability heuristic
  • heart disease 3 vs. 8 risk factors
  • Who feels more at risk for heart disease?

(Rothman Schwarz, 1998)
13
Heuristics
  • look at your answers to the second problem
  • a. Linda is a bank teller.
  • b. Linda is a bank teller and active in the
    feminist movement.

14
Heuristics
  • representative heuristic a judgment based on an
    objects (i.e., person, thing) resemblance to a
    particular category
  • the more similar the object is to a category, the
    more likely it is to be a member of that category

15
Heuristics
  • representative heuristic
  • ignore the base rate information
  • but, it is often a useful heuristic

16
Heuristics
  • look at your answers to the third problem
  • Who is more upset? Mr. Crane or Mr. Tees?

17
Heuristics
  • simulation heuristic mentally changing some
    aspect of the past as a way of imagining what
    might have been
  • the easier it is to imagine how things might have
    been otherwise, the more tragic it seems

18
Heuristics
  • simulation heuristic
  • examined tapes of 41 athletes from 92 Games
  • judges rated athletes on scales from agony to
    ecstasy
  • bronze medalists happier than silver medalists

(Medvec, Madey, Gilovich, 1995)
19
Heuristics
  • simulation heuristic
  • people mentally undo action easier than inaction
    (Kahneman Miller, 1986)
  • e.g., feel worse about saying something
    inappropriate than failing to say something
    appropriate

20
Heuristics
  • look at your answer to the fourth problem
  • Program A or Program B?

21
Heuristics
  • framing effect how we process information
    depends on how the information is presented (or
    framed)
  • gains likely to be risk-averse
  • losses likely to be risk-seeking

22
Heuristics
  • anchoring-and-adjustment heuristic in estimating
    numerical values (e.g., frequencies,
    probabilities), people use a starting point and
    adjust up or down
  • e.g., murder trials first consider most or least
    severe punishment (Greenberg, Williams, OBrien,
    1986)

23
Automatic or Controlled?
  • Thinking is for doing. (Fiske, 1992)
  • social cognition is practical
  • social interaction goals influence the degree of
    automaticity or control
  • decisive or accurate?

24
Automaticity
  • preconscious automaticity mental action that
    occurs outside of ones conscious awareness
  • gold standard of automatic processes
  • subliminal priming affects liking (Murphy,
    Monahan, Zajonc, 1995)

25
Automaticity
Liking Ratings
0 1 3
Number of Exposures
(Murphy, Monahan, Zajonc, 1995)
26
Automaticity
  • postconscious automaticity the stimulus
    eliciting an effect is fully conscious, but its
    influence is not

27
Automaticity
  • postconscious automaticity
  • postconscious priming
  • What kind of person is Donald? (Higgins, Rholes,
    Jones, 1977)

28
Automaticity
  • postconscious automaticity
  • postconscious priming
  • mood effects (e.g., Forgas, 1998)
  • students in library found pictures in an envelope
  • humorous cartoons or car accidents
  • stranger approached and requested some paper
  • negative mood more likely to resist the request

29
Automaticity
  • postconscious automaticity
  • postconscious priming
  • mood effects (e.g., Forgas, 1998)
  • salience effects (e.g., Taylor Fiske, 1975)
  • Who is more important to the tone and content of
    the conversation?

30
Automaticity
(Taylor Fiske, 1975)
31
Controlled Responses
  • fully intentional control
  • to exercise intent, a person must
  • a) have options
  • b) make the hard choice (i.e., the non-dominant
    alternative)
  • c) pay attention

(Fiske, 1989)
32
Controlled Responses
  • fully intentional control
  • getting out of bed on a cold, dark morning
  • a) get up or stay put
  • b) make the choice to get up
  • c) thinking about what was has to get done

33
Dealing with Limitations
  • ways to become better thinkers
  • statistical reasoning
  • e.g., pay attention to the base rates
  • law of large numbers
  • a large sample size is better (i.e., more
    accurate)
  • be critical consumers of information

34
Summary
  • processing social information is flawed
  • two goals accuracy and decisiveness
  • heuristics are adaptive but flawed
  • most of our mental processing is automatic
  • ways of improving the process

35
Next Time
  • How do we think about other people and their
    behavior?
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