1. 1 Human information processing: Chapters 4-9 ReceptorsPerception Long-term memory Response selection Response execution Controlled system Working memory Attentional resources Decision making

2. 2 Objectives n Different types of decision making descriptions and the implications for design n Heuristics and biases affecting decisions n Levels of cognitive control describe qualitatively different types of human performance n Levels of cognitive control span many theories of DM and can identify training and cognitive support strategies n Skill-based processing and affect are key elements of decision making

3. 3 Decision making defined n 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 n Builds upon basic cognitive mechanisms of: perception, working memory, attention and LTM

4. 4 Decision making types n Intuitive Quick Automatic n Classical Decision Theory Optimal, rational decision determined through use of expected values Description of bias and heuristics that reflect human limits n Analytical Slow Deliberate, controlled n Naturalistic DM Experienced people Complex, dynamic environments Based on experiences and mental simulations

5. 5 Expected utility calculations example Expected 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 ticket p(winning)=1x10 -7 v(winning) =1x10 6 E(ticket value-ticket cost)=0.10-1.0 Save money p(bank surviving)=1-1x10 -7 v(with interest) =1.02 E(money saved)=1.019999

6. 6 Types of classical decision theory n Normative models What people SHOULD do Basis of computer aids Basis for understanding when people make rational decisions Basis for training n Descriptive models What people ACTUALLY do Heuristics used/ Biases that undermine performance Information processing model as a descriptive model of DM

7. 7 Elements of decision process n Obtain and combine cues (selective attention) n Generate hypotheses (LTM) n Hypothesis evaluation and selection (working memory) n Action selection (working memory, LTM)

8. 8 Information processing model of DM Cues C1 C2 C3 C4 Uncertainty Selective attention Diagnosis Choice H H H H H HH H A A A A A A A A H H A A Working memory LTM

9. 9 Factors influencing heuristics and biases n Selective attention n Limited capacity of working memory n Time available n Limited attentional resources n Limited knowledge (LTM) n Ability to retrieve appropriate information (inert knowledge)

10. 10 Which penny: Precise decisions with imprecise knowledge

11. 11 Heuristics and biases: Obtaining and selecting cues n Attention to limited number of cues (landing gear light fixation) n Cue primacy (first cues get greater weight) n Inattention to later cues (ignore later cues) n Cue salience n Inappropriate weight to unreliable cues

12. 12 Heuristics and biases: Hypothesis generation n Limited number of hypotheses generated n Availability heuristic (frequent, recent) n Representative heuristic (take as typical of category) n Overconfidence

13. 13 Heuristics and biases: Hypothesis evaluation and selection n Cognitive fixation (continue along path, ignoring contrary information) n Confirmation bias Seek only evidence to confirm NOT to disconfirm Fail to use absence of important cues

14. 14 Heuristics and biases: Action selection n Retrieve small number of actions n Availability heuristic for actions n Availability heuristic for possible outcome Subjective probability does not equal actual

15. 15 Decision making types n Classical Decision Theory Heuristics and biases associated information processing limits n Naturalistic DM Levels of cognitive performance/control for experienced people in complex, dynamic environments

16. 16 Characteristics of naturalistic decision making situations n Ill-structured problems n Uncertain high-risk environments n Cognitive processing as an iterative action/feedback loop n Time constraints and time stress n Multiple persons involved in decision n People with extreme domain expertise

17. 17 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

18. 18 Elements of naturalistic decision making n Implications of levels of cognitive control Types of information Level of expertise Error tendencies Situation awareness n Implications for decision aids

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20. 20 Levels of cognitive control Goals Feature Formation Automated Sensory-Motor Patterns Recognition Association State/Task Stored Rules for Task Planning Decision of Task Identification Knowledge-based Behavior Rule-based Behavior Skill-based Behavior Sensory Input Signals Actions Signs Symbols

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22. 22 Types of information Goals Feature Formation Automated Sensory-Motor Patterns Recognition Association State/Task Stored Rules for Task Planning Decision of Task Identification Knowledge-based Behavior Rule-based Behavior Skill-based Behavior Sensory Input Signals Actions Signs Symbols

23. 23 Amount of experience Goals Feature Formation Automated Sensory-Motor Patterns Recognition Association State/Task Stored Rules for Task Planning Decision of Task Identification Knowledge-based Behavior Rule-based Behavior Skill-based Behavior Sensory Input Signals Actions Signs Symbols Novice Expert

24. 24 Error tendencies Goals Feature Formation Automated Sensory-Motor Patterns Recognition Association State/Task Stored Rules for Task Planning Decision of Task Identification Knowledge-based Behavior Rule-based Behavior Skill-based Behavior Sensory Input Signals Actions Signs Symbols Perform task out of habit Motor control error Misclassification of situation Failure to consider consequence

25. 25 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 status Level 2: Comprehending information in light of goals Level 3: Projecting the activity to the future

26. 26 Situation awareness Goals Feature Formation Automated Sensory-Motor Patterns Recognition Association State/Task Stored Rules for Task Planning Decision of Task Identification Knowledge-based Behavior Rule-based Behavior Skill-based Behavior Sensory Input Signals Actions Signs Symbols Level 1 SA Level 2 SA Level 3 SA

27. 27 Cognitive continuum theory Goals Feature Formation Automated Sensory-Motor Patterns Recognition Association State/Task Stored Rules for Task Planning Decision of Task Identification Knowledge-based Behavior Rule-based Behavior Skill-based Behavior Sensory Input Signals Actions Signs Symbols Analytic Intuitive

28. 28 Cognitive continuum theory n Factors inducing Intuition: Large number of cues Brief display of cues Complex relationship between cues Short DM time Analog display n Factors inducing Analysis: Few cues Long availability of cues High consequence Digital display

29. 29 Recognition-primed decision making n Pattern matching used to recognize situation n Recognition “primes” the selection of a plausible solution n Action selected without comparison with alternates n Action evaluated through simulation using a mental model n Particularly effective in time-constrained situations n 40-80% based on condition-action rules

30. 30 Recognition-primed decision making Goals Feature Formation Automated Sensory-Motor Patterns Recognition Association State/Task Stored Rules for Task Planning Decision of Task Identification Knowledge-based Behavior Rule-based Behavior Skill-based Behavior Sensory Input Signals Actions Signs Symbols Application of condition-action rules Simulation-based evaluation with mental model

31. 31 Improving decision making n Redesign to support decision making and performance n Decision aids n Training

32. 32 Redesign n Accentuate relevant cues n Warning devices to guide attention to critical events n Restructure situation and overall system n Analysis of system dynamics

33. 33 Training n Train analytic methods, has proven marginally successful n Train better metacognition (e.g., manage time pressure), has proven marginally successful n Focus on job-relevant knowledge and procedures n Train skill-based with actual cues n Cognitive feedback rather than performance feedback

34. 34 Decision aids n Fallacy of “expert” systems No basis for evaluation of the input Output mistrusted “Joint cognitive breakdowns” due to unanticipated complexity n Cognitive support Interactive system that improves DM by extending user’s capabilities Tool rather than prosthesis

35. 35 Types of cognitive support Goals Feature Formation Automated Sensory-Motor Patterns Recognition Association State/Task Stored Rules for Task Planning Decision of Task Identification Knowledge-based Behavior Rule-based Behavior Skill-based Behavior Sensory Input Signals Actions Signs Symbols Display and call attention to important cues Present reliability/value of cues Allow operators to specify alarms according to circumstances

36. 36 Types of cognitive support Goals Feature Formation Automated Sensory-Motor Patterns Recognition Association State/Task Stored Rules for Task Planning Decision of Task Identification Knowledge-based Behavior Rule-based Behavior Skill-based Behavior Sensory Input Signals Actions Signs Symbols Use spatial organization to state information Present condition-action rules and discrepancies Indicate variable levels that require responses (e.g., level associated with normal operations)

37. 37 Goals Feature Formation Automated Sensory-Motor Patterns Recognition Association State/Task Stored Rules for Task Planning Decision of Task Identification Knowledge-based Behavior Rule-based Behavior Skill-based Behavior Sensory Input Signals Actions Signs Symbols Support “what if” analysis Provide an externalized mental model in the display Provide critiques of hypotheses generated Types of cognitive support

38. 38 Problem solving Goals Feature Formation Automated Sensory-Motor Patterns Recognition Association State/Task Stored Rules for Task Planning Decision of Task Identification Knowledge-based Behavior Rule-based Behavior Skill-based Behavior Sensory Input Signals Actions Signs Symbols Requires Knowledge Mental model for simulation Working memory capacity

39. 39 Critiquing system http://freney.sys.virginia.edu/~sag3c/ProblemBasedLearning.html

40. 40 Key concepts n Different types of decision making descriptions and the implications for design n Heuristics and biases affecting decisions n Levels of cognitive control describe qualitatively different types of human performance n Levels of cognitive control span many theories of DM and can identify training and cognitive support strategies n Skill-based processing and affect are key elements of decision making