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Decision making, decision support & problem solving

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Presentatie van 19-02-2014 over het hoofdstuk 'Decision-making models, decision support, and problem solving' uit het boek Human Factors Fundamentals van Lehto et al. uit 2012, en de paper 'Flightdeck …

Presentatie van 19-02-2014 over het hoofdstuk 'Decision-making models, decision support, and problem solving' uit het boek Human Factors Fundamentals van Lehto et al. uit 2012, en de paper 'Flightdeck and Air Traffic Control Collaboration and Evaluation' van Sharples et al. uit 2012.

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  • 1. Decision-making models, decision support, and problem solving Mark R. Lehto, Fiona Fui-Hoon Nah, Ji Soo Yi in Human Factors Fundamentals (2012) #CognitiveEngineering @MartinSpecken
  • 2. Integrative model of decision making • • • • • • • Single DM Time pressure Multiple stages Risk attitudes Knowledge Decision tools Multiple DMs #CognitiveEngineering @MartinSpecken
  • 3. Categories of decision making (1/5) (Sometimes overlapping) 1. Group 2. Dynamic 3. Routine 4. Conflict #CognitiveEngineering @MartinSpecken
  • 4. Categories of decision making (2/5) • Debate • Bargain • Vote Group decision making #CognitiveEngineering @MartinSpecken
  • 5. Categories of decision making (3/5) • Decision 1: Take medical test • Decision 2: What to do with the result? Dynamic decision making #CognitiveEngineering @MartinSpecken
  • 6. Categories of decision making (4/5) Routine decision making #CognitiveEngineering @MartinSpecken
  • 7. Categories of decision making (5/5) Various forms of conflict must be resolved before an alternative action can be chosen. Conflict-driven decision making #CognitiveEngineering @MartinSpecken
  • 8. Decision making models (1/3) 1. Normative 2. Behavioral 3. Naturalistic #CognitiveEngineering @MartinSpecken
  • 9. Normative decision models (1/6) Classic decision theory with 4 elements: • Potential actions to choose between [A] • Events/world states [E] • Probabilities [P] from combination [A] &[E] • Consequences [C] from combination [A]&[E] #CognitiveEngineering @MartinSpecken
  • 10. Normative decision models (2/6) 1. Dominance 2. Maximizing expected value 3. Subjective expected utility theory 4. Multiattribute utility theory #CognitiveEngineering @MartinSpecken
  • 11. Normative decision models (3/6) Occurs between two alternative actions, Aiand Aj, when: Action Ai is at least as good as Aj – for all events E AND – for at least one event Ek then Ai is preferred to Aj #CognitiveEngineering Dominance @MartinSpecken
  • 12. Normative decision models (4/6) Select the alternative with the greatest expected value. • 3 kittens are stuck in trees • Decision: – Save 3 kittens is 3 times as good as saving 1 kitten. • Choises: – 100% chance to save 1 kitten Expected value = 1 * 1 = 1 – 50% chance to save all 3 kittens + 50% to save 0 kittens Expected value = ( 3 * 0,5 + 0 * 0,5 ) = 1,5 Maximizing Expected Value #CognitiveEngineering @MartinSpecken
  • 13. Normative decision models (5/6) Basic axioms (Dutch: grondstelling) of rational choise: • If A > B and B > C , then A > C • People’s preferences can conflict with the axioms. • Movement toward less restrictive standards. Subjective Expected Utility Theory #CognitiveEngineering @MartinSpecken
  • 14. Normative decision models (6/6) Consider attractiveness of • Economic benifits • Social benefits • Environmental benefits Multiattribute Utility Theory #CognitiveEngineering @MartinSpecken
  • 15. Decision making models (2/3) 1. Normative 2. Behavioral 3. Naturalistic #CognitiveEngineering @MartinSpecken
  • 16. Behavioral decision models (1/5) Normative decision models don’t always work when compared to human behavior. 1. Statistical estimation and inference 2. Preference and choise 3. Adaptive decision behavior 4. Behavior economics #CognitiveEngineering @MartinSpecken
  • 17. Behavior decision models (2/5) 1960s: People behave as ’intuïtive statisticians’. Many examples of findings in the paper. A selection: • DMs tend to ignore the reliability of the evidence. • DMs tend to seek out confirming evidence rather than disconfirming evidence. • DMs are overconfident in their predictions. Statistical estimation and inference #CognitiveEngineering @MartinSpecken
  • 18. Behavior decision models (3/5) Research: observing human preference and choise and comparing it with the SEU theory People’s preferences change when the outcomes are framed in terms of costs, as opposed to benifits. Preference and choise #CognitiveEngineering @MartinSpecken
  • 19. Behavior decision models (4/5) Individual DM uses different strategies in different situations. Adaptive decision behavior #CognitiveEngineering @MartinSpecken
  • 20. Behavior decision models (5/5) #CognitiveEngineering Behavior economics @MartinSpecken
  • 21. Decision making models (3/3) 1. Normative 2. Behavioral 3. Naturalistic #CognitiveEngineering @MartinSpecken
  • 22. Naturalistic decision models (1/5) In dynamic and realistic environment, actions by decision maker are made sequentially in time. 1. Levels of task performance 2. Recognition-primed decision making 3. Dominance structuring 4. Explanation-based decision making #CognitiveEngineering @MartinSpecken
  • 23. Naturalistic decision models (2/5) Most decisions are made on a routine basis. The levels of performance tasks are based on: • • • • Skills Rules Knowledge Judgement Levels of task performance #CognitiveEngineering @MartinSpecken
  • 24. Naturalistic decision models (3/5) 80% of firefighters make decisions based on some sort of situation recognition Recognition-primed decision making #CognitiveEngineering @MartinSpecken
  • 25. Naturalistic decision models (4/5) Nonroutine decisions involve sequence of: 1. Screen alternatives. 2. Select alternative. 3. Check dominance of selection to other alternatives. 4. No dominance? Restructure info to force dominance. Dominance structuring #CognitiveEngineering @MartinSpecken
  • 26. Naturalistic decision models (5/5) Jurors seem to organize massive amount of data in terms of stories describing cause and intent. Explanation-based decision making #CognitiveEngineering @MartinSpecken
  • 27. Group decision making (1/5) 1. Ethics and social norms 2. Group processes 3. Group performance and biasses 4. Prescriptive approaches #CognitiveEngineering @MartinSpecken
  • 28. Group decision making (2/5) Four dilemma’s of right versus right (Kidder, 1995) 1. Truth versus Loyalty 2. Individual versus Community 3. Short term versus Long term 4. Justice versus Mercy Ethics and social norms #CognitiveEngineering @MartinSpecken
  • 29. Group decision making (3/5) Tuckman (1965): 1. Forming (initial orientation) 2. Storming (conflict) 3. Norming (develop cohesion, express opinions) 4. Performing (obtain solutions) #CognitiveEngineering Group processes @MartinSpecken
  • 30. Group decision making (4/5) Strong opposition to usefull products Group performance and biasses #CognitiveEngineering @MartinSpecken
  • 31. Group decision making (5/5) Prescriptive approaches #CognitiveEngineering @MartinSpecken
  • 32. Decision support and problem solving (1/5) 1. Decision analysis 2. Individual decision support 3. Group and organizational decision support 4. Problem solving #CognitiveEngineering @MartinSpecken
  • 33. Decision support and problem solving (2/5) A = Action E = Event P = Probability C = Consequenses P1 E1 A1 E2 1 - P1 P2 A2 E1 E2 1 – P2 #CognitiveEngineering Decision analysis C11 C12 C21 C22 @MartinSpecken
  • 34. Decision support and problem solving (3/5) Individual decision support #CognitiveEngineering @MartinSpecken
  • 35. Decision support and problem solving (4/5) Negotiation Support Systems assist people in activities that are competitive of involve conflicts of interest. Group and organizational decision #CognitiveEngineering @MartinSpecken
  • 36. Decision support and problem solving (5/5) Psychologist work together with computer scientist to understand the human mind #CognitiveEngineering Problem solving @MartinSpecken
  • 37. Book Malcolm Cook et al. (2007) http://tinyurl.com/boekdecisionmaking #CognitiveEngineering @MartinSpecken
  • 38. Paper Sarah Sharples et al. (2007) (1/5) http://www.ncbi.nlm.nih.gov/pubmed/17499573 #CognitiveEngineering @MartinSpecken
  • 39. Paper Sarah Sharples et al. (2007) (2/5) Key components in airspace systems: • Air traffic controllers • Airline management • Aircraft pilots • Aircraft systems #CognitiveEngineering @MartinSpecken
  • 40. Paper Sarah Sharples et al. (2007) (3/5) Different goals: • Air traffic controllers safety of all the aircrafts in the system • Airline management expediency &efficiency (profit) • Aircraft pilots safety &expediency of aircraft (local) #CognitiveEngineering @MartinSpecken
  • 41. Paper Sarah Sharples et al. (2007) (4/5) Different available information: • Air traffic controllers more: global traffic patterns less: global weather • Airline management less: traffic patterns more: current weather #CognitiveEngineering @MartinSpecken
  • 42. Paper Sarah Sharples et al. (2007) (5/5) Increase of air traffic: How can extra aircrafts operate economically, efficiently and safe? • Freeflight some transfer of responsibility from air traffic controller to pilot for determining flight paths • Datalink provide electronic exchange of information between pilots and air traffic controllers #CognitiveEngineering @MartinSpecken
  • 43. Finally The integrative model of decision making shows how the various approaches fit together as a whole. #CognitiveEngineering @MartinSpecken