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1
Human information processing:Chapters 4-9
Receptors Perception
Long-term memory
Response selection
Response execution
Controlled system
Working memory
Attentional resources
Decision making
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Objectives
Different types of decision making descriptions and the implications for design
Heuristics and biases affecting decisions Levels of cognitive control describe qualitatively different
types of human performance Levels of cognitive control span many theories of DM
and can identify training and cognitive support strategies Skill-based processing and affect are key elements of
decision making
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Decision making defined
Decision making defined as:• Select one choice from many• Some information available regarding choices• Time frame is relatively long (> 1 sec)• Uncertainty regarding best or acceptable choice
Builds upon basic cognitive mechanisms of: perception, working memory, attention and LTM
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Decision making types
Intuitive • Quick• Automatic
Classical Decision Theory• Optimal, rational decision
determined through use of expected values
• Description of bias and heuristics that reflect human limits
Analytical • Slow• Deliberate, controlled
Naturalistic DM• Experienced people• Complex, dynamic
environments• Based on experiences and
mental simulations
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Expected utility calculations exampleExpected value of choice “v” equals the sum of the probabilities and values
E(v)= p(i)v(i)
For the most simple case of the lottery:
Purchase ticketp(winning)=1x10-7
v(winning) =1x106
E(ticket value-ticket cost)=0.10-1.0
Save money p(bank surviving)=1-1x10-7
v(with interest) =1.02E(money saved)=1.019999
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Types of classical decision theory
Normative models• What people SHOULD do• Basis of computer aids• Basis for understanding
when people make rational decisions
• Basis for training
Descriptive models• What people ACTUALLY
do• Heuristics used/ Biases
that undermine performance
• Information processing model as a descriptive model of DM
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Elements of decision process
Obtain and combine cues (selective attention) Generate hypotheses (LTM) Hypothesis evaluation and selection (working
memory) Action selection (working memory, LTM)
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Information processing model of DM
Cues
C1C2C3C4
Uncertainty
Selective attention
Diagnosis Choice
HH
HH
HH HH
AA
AA
A
A
A
A
H H A A
Working memory
LTM
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Factors influencing heuristics and biases
Selective attention Limited capacity of working memory Time available Limited attentional resources Limited knowledge (LTM) Ability to retrieve appropriate information (inert
knowledge)
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Which penny: Precise decisions with imprecise knowledge
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Heuristics and biases: Obtaining and selecting cues
Attention to limited number of cues (landing gear light fixation)
Cue primacy (first cues get greater weight) Inattention to later cues (ignore later cues) Cue salience Inappropriate weight to unreliable cues
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Heuristics and biases: Hypothesis generation
Limited number of hypotheses generated Availability heuristic (frequent, recent) Representative heuristic (take as typical of
category) Overconfidence
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Heuristics and biases: Hypothesis evaluation and selection
Cognitive fixation (continue along path, ignoring contrary information)
Confirmation bias• Seek only evidence to confirm NOT to disconfirm• Fail to use absence of important cues
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Heuristics and biases: Action selection
Retrieve small number of actions Availability heuristic for actions Availability heuristic for possible outcome
• Subjective probability does not equal actual
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Decision making types
Classical Decision Theory• Heuristics and biases
associated information processing limits
Naturalistic DM• Levels of cognitive
performance/control for experienced people in complex, dynamic environments
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Characteristics of naturalistic decision making situations
Ill-structured problems Uncertain high-risk environments Cognitive processing as an iterative
action/feedback loop Time constraints and time stress Multiple persons involved in decision People with extreme domain expertise
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The strange case of Phineas Gage
http://www.mc.maricopa.edu/academic/cult_sci/anthro/origins/phineas.html
Left intellectual abilities intact, but greatly impaired decision making
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Elements of naturalistic decision making
Implications of levels of cognitive control• Types of information• Level of expertise• Error tendencies• Situation awareness
Implications for decision aids
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Levels of cognitive controlGoals
Feature Formation
Automated Sensory-Motor
Patterns
Recognition Association State/Task
Stored Rules for Task
PlanningDecision of
TaskIdentification
Knowledge-based Behavior
Rule-based Behavior
Skill-based Behavior
Sensory Input Signals Actions
Signs
Signs
Symbols
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Types of informationGoals
Feature Formation
Automated Sensory-Motor
Patterns
Recognition Association State/Task
Stored Rules for Task
PlanningDecision of
TaskIdentification
Knowledge-based Behavior
Rule-based Behavior
Skill-based Behavior
Sensory Input Signals Actions
Signs
Signs
Symbols
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Amount of experienceGoals
Feature Formation
Automated Sensory-Motor
Patterns
Recognition Association State/Task
Stored Rules for Task
PlanningDecision of
TaskIdentification
Knowledge-based Behavior
Rule-based Behavior
Skill-based Behavior
Sensory Input Signals Actions
Signs
Signs
Symbols
Novice
Expert
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Error tendenciesGoals
Feature Formation
Automated Sensory-Motor
Patterns
Recognition Association State/Task
Stored Rules for Task
PlanningDecision of
TaskIdentification
Knowledge-based Behavior
Rule-based Behavior
Skill-based Behavior
Sensory Input Signals Actions
Signs
Symbols
Perform task out of habitMotor control error
Misclassification of situation
Failure to consider consequence
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Situation awareness
“The perception of the elements in the environment with a volume of time and space, the comprehension of their meaning and the projection of their status in the near future”
Level 1: Perceiving statusLevel 2: Comprehending information in light of goalsLevel 3: Projecting the activity to the future
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Situation awarenessGoals
Feature Formation
Automated Sensory-Motor
Patterns
Recognition Association State/Task
Stored Rules for Task
PlanningDecision of
TaskIdentification
Knowledge-based Behavior
Rule-based Behavior
Skill-based Behavior
Sensory Input Signals Actions
Signs
Signs
Symbols
Level 1 SA
Level 2 SA Level 3 SA
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Cognitive continuum theoryGoals
Feature Formation
Automated Sensory-Motor
Patterns
Recognition Association State/Task
Stored Rules for Task
PlanningDecision of
TaskIdentification
Knowledge-based Behavior
Rule-based Behavior
Skill-based Behavior
Sensory Input Signals Actions
Signs
Signs
Symbols
Analytic
Intuitive
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Cognitive continuum theory
Factors inducing Intuition:• Large number of cues• Brief display of cues• Complex relationship between cues• Short DM time• Analog display
Factors inducing Analysis:• Few cues • Long availability of cues• High consequence• Digital display
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Recognition-primed decision making
Pattern matching used to recognize situation Recognition “primes” the selection of a plausible
solution Action selected without comparison with alternates Action evaluated through simulation using a
mental model Particularly effective in time-constrained situations 40-80% based on condition-action rules
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Recognition-primed decision makingGoals
Feature Formation
Automated Sensory-Motor
Patterns
Recognition Association State/Task
Stored Rules for Task
PlanningDecision of
TaskIdentification
Knowledge-based Behavior
Rule-based Behavior
Skill-based Behavior
Sensory Input Signals Actions
Signs
Signs
Symbols
Application of condition-action rules
Simulation-based evaluation with mental model
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Improving decision making
Redesign to support decision making and performance
Decision aids Training
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Redesign
Accentuate relevant cues Warning devices to guide attention to critical
events Restructure situation and overall system Analysis of system dynamics
33
Training
Train analytic methods, has proven marginally successful
Train better metacognition (e.g., manage time pressure), has proven marginally successful
Focus on job-relevant knowledge and procedures Train skill-based with actual cues Cognitive feedback rather than performance
feedback
34
Decision aids
Fallacy of “expert” systems • No basis for evaluation of the input• Output mistrusted• “Joint cognitive breakdowns” due to unanticipated
complexity Cognitive support
• Interactive system that improves DM by extending user’s capabilities
• Tool rather than prosthesis
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Types of cognitive supportGoals
Feature Formation
Automated Sensory-Motor
Patterns
Recognition Association State/Task
Stored Rules for Task
PlanningDecision of
TaskIdentification
Knowledge-based Behavior
Rule-based Behavior
Skill-based Behavior
Sensory Input Signals Actions
Signs
Signs
Symbols
Display and call attention to important cuesPresent reliability/value of cuesAllow operators to specify alarms according to circumstances
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Types of cognitive supportGoals
Feature Formation
Automated Sensory-Motor
Patterns
Recognition Association State/Task
Stored Rules for Task
PlanningDecision of
TaskIdentification
Knowledge-based Behavior
Rule-based Behavior
Skill-based Behavior
Sensory Input Signals Actions
Signs
Signs
Symbols
Use spatial organization to state informationPresent condition-action rules and discrepanciesIndicate variable levels that require responses (e.g., level associated with normal operations)
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Goals
Feature Formation
Automated Sensory-Motor
Patterns
Recognition Association State/Task
Stored Rules for Task
PlanningDecision of
TaskIdentification
Knowledge-based Behavior
Rule-based Behavior
Skill-based Behavior
Sensory Input Signals Actions
Signs
Signs
Symbols
Support “what if” analysisProvide an externalized mental model in the displayProvide critiques of hypotheses generated
Types of cognitive support
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Problem solvingGoals
Feature Formation
Automated Sensory-Motor
Patterns
Recognition Association State/Task
Stored Rules for Task
PlanningDecision of
TaskIdentification
Knowledge-based Behavior
Rule-based Behavior
Skill-based Behavior
Sensory Input Signals Actions
Signs
Signs
Symbols
Requires KnowledgeMental model for simulationWorking memory capacity
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Critiquing systemhttp://freney.sys.virginia.edu/~sag3c/ProblemBasedLearning.html
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Key concepts
Different types of decision making descriptions and the implications for design
Heuristics and biases affecting decisions Levels of cognitive control describe qualitatively different
types of human performance Levels of cognitive control span many theories of DM
and can identify training and cognitive support strategies Skill-based processing and affect are key elements of
decision making