Instructor: Vincent Duffy, Ph.D. Associate Professor of IE

1. IE 486 Work Analysis & Design II Instructor: Vincent Duffy, Ph.D. Associate Professor of IE Lecture 6 – Decision Making & Uncertainty Thurs. Feb. 1, 2007

2. An introduction to human decision making • First review end of cognition (lecture 5) and relationship to decision making (lecture 6) • Re-introduce QOTD as part of lecture today • Then briefly discuss plan for tomorrow in lab

3. 6. Long term memory • Design implications • The user is unlikely to develop the same level of detail (recall) in the use of a product compared to the designer • Therefore, when possible, it is a good idea to: • Encourage frequent use of information – • Take advantage of frequency and recency • then over time, the task may become more automatic • Standardize and use memory aids • Eg. Give list of instructions for sending fax • Carefully design information to be remembered • Make it meaningful and avoid the use of technical jargon when possible

4. 7. Attention and mental resources • If we devote cognitive resources to one activity, others are likely to suffer • Eg. Study of the use of cell phones and driving suggests that accidents are 5x more likely • The rate is roughly equivalent to driving drunk • Consider multiple resources • Eg. One can not read a book and watch tv at the same time. • However, one can listen to the spoken version of the book while watching tv. • Visual and auditory processing requires separate resources.

5. 8. Conclusions • Some general design implications • Consider: issues related to • Divided attention, • controlled vs. automatic processing & • multiple resources • Make the input mode ‘dissimilar’ when possible • eg. Take advantage of different pools of resources. • Automation (or more automatic processing of information) allows better time-sharing of mental resources. • Convey Priority - Let the user know the importance of each task to better allocate (mental) resources.

6. Overview of human decision making • 1. Overview of human decision making • 2. An example: anesthesiology team in hospital • 3. What is the problem with heuristics for decision making? • 4. Naturalistic decision making • 5. Skill rule and knowledge based task performance • 6. Improving human decision making

7. IE 486 - Lecture 6 - QOTD • QOTD 1. What are ‘heuristics’? • QOTD 2. How can we model task performance considering the cognitive aspects of tasks? • QOTD 3. What are some ways to improve human decision making through human factors engineering design?

8. 1. Overview of human decision making • According to Wickens (ch.7) • Decisions are made either • intuitively - quick and relatively automatic or • analytically - slow, deliberate and controlled

9. 1. Overview of human decision making • QOTD 1. What are ‘heuristics’? • Simplifications in decision making • do not always guarantee best solution due to biases or misperceptions • eg. ‘satisficing’ (Simon, a psychologist 1957) • suggests a decision maker generates alternatives until an ‘acceptable’ (not necessarily optimal) solution is found • it is believed that many people will judge that ‘going beyond this to identify something better has ‘too little advantage to make it worth the effort’. • Why? • People have limited cognitive capacity and limited time

10. 1. Overview of human decision making • How do economists believe we make decisions? • Rational decision making - it is expected that the decision maker will find the ‘optimal’ solution • …based on our concept of what is useful (utility) and willingness to accept risk

11. 2. An example: anesthesiology team in hospital • 5 medical procedures are to be performed urgently on 5 different patients in two different buildings • there are only 3 anesthesiologists plus the ‘one in charge’ who is supposed to be ‘available’ in case of incoming unexpected ‘emergency’ • classical or ‘normative’ decision making theory suggests there are different alternatives with different likelihood of outcome …and each has an expected ‘utility’ (good/bad payoff)

12. 2. anesthesiology team in hospital • 4 possible alternatives • the ‘one in charge’ begins a procedure and no emergency occurs • or the ‘one in charge’ begins a procedure and an emergency occurs • or she doesn’t begin a procedure and an emergency comes in • or she doesn’t begin a procedure and an emergency doesn’t come in • see p. 160 for expected outcomes based on likelihood and utility/payoffs

13. 3. What is the problem with heuristics for decision making? • The decisions are subject to biases • 1. A limited number of hypotheses is generated • 2. ‘memory’ research suggests people will recall what was most ‘frequently’ or most ‘recently’ considered - most readily available. • 3. Certain cues may lead to a conclusion - then not enough is then done to eliminate other possibilities • 4. Overconfidence - people tend to believe they are right more often than they really are • 5. Cognitive fixation - people tend to ignore cues that are contrary to their original belief

14. 4. Naturalistic decision making • Decisions in ‘the field’ • these ideas are considered outside the ‘experimental’ world • It is suggested by some that this is more useful that ‘experimental studies done in labs’. • However, Wickens suggests that these are complementary to experimental evidence • For ill structured problems • under time constraints and time stress • high risk and multiple people involved

15. 5. Skill, rule and knowledge based task performance QOTD 2 Q. How can we model task performance considering the cognitive aspects of tasks? • Rasmussen suggests 3 levels of ‘cognitive’ control and that people operate at one of the levels depending on the nature of the task and their ‘experience’ • skill based - reacting to perceptual elements in an automatic, subconscious level • rule based - rely on if-then associations between cues and actions • typical of those with familiarity but not extensive experience • knowledge based- when the situation is novel and there is no rule or previous experience to draw on

16. 6. Improving human decision making QOTD 3 • Q. What are some ways to improve human decision making through human factors engineering design. • Eg. Parachutist has a chute that fails to open properly • after trying to untangle the cords, they deploy the reserve chute too late - at 200 ft. • To reduce chance of an accident • a redesign could have helped recognition of the trouble and awareness of the critical ‘time’ issue • different colors for cloth and cords could have helped diagnosis and • an altitude sensor (with auditory alarm) could have given awareness about time running out

17. 6. Improving human decision making • in complex environments can be helped by training • using computer support • to teach pattern recognition • break the process into different cognitive steps • ‘People overrely on rapid, intuitive decisions rather than perform the more difficult analyses’ (Pierce, 1996) • This suggests that decision aids can support decision making if they can help ‘counteract’ this tendency to take ‘shortcuts’ (or satisficing) tendency • especially when the decision is important, and when there is enough time to do the analysis

18. Tomorrow in lab • Review lab 1, part 1 • Turn in reports • Demonstrate quantitative aspects related to decision making & uncertainty (tutorial) • Introduce Lab 2