1 Human information processing: Chapters 4-9 ReceptorsPerception Long-term memory Response selection...

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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

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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

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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