The Psychology of Judgment and Decision Making

1. The Psychology of Judgment and Decision Making

2. Part 1: • Heuristics and Biases • How they affect people’s judgments and decisions • How they affect researchers • How they affect MIS

3. Definition: Heuristic and Bias “ …people rely on a limited number of heurisitc principles which reduce cimplex tasks of assessing probabilities and prediciting values to sijmpler judgmental operations. In general, these heurisitcs are quite useful, but sometimes they lead to severe and systematic errors.” (from Tversky, & Kahneman, Science, 185, p.1124-1131.) -> ‘People are systematically biased’

4. Section 1: Perception, Memory, and Context Biases

5. A Foolish Consistency is the Hobgoblin of Small Minds- Ralph Waldo Emerson

6. Previous Beliefs and Expectations Affect Perception It Looks Red

7. Later People Reconstruct MemoriesGuess 4 Numbers Not Bad Guesses! My Numbers are 1, 2, 5, and 16 I Guessed 2, 3, 6 and 15 I was Right!

8. Later Cognitive Dissonance Save The Red Elephants It WAS Red You’ll Sign My Petition, Won’t you? Joe I saw red Elephant, X

9. The Halo Effect That Elephant Has a Big Smile; I bet He’s Red

10. Contextual Clues Small Elephant Big Elephant

11. Parables of context biases and Purple Red elephants • People see what they expect to see (Mr. Red) • People reconstruct memories (“I was right”) • People try to be “consistent” (It was red) • Nearby things affect perception (relativity) • People believe good things about good people (The halo effect)

12. Escaping Context Biases • Take note of context • Know yourself • Consider the possibility of alternative outcomes

13. How to get the results you want from an experiment, capitalizing on Perception, Memory and Context (A roll play emphasizing the impact perception, memory, and context can have in a research setting)

14. Halo Effect • Their Tool • Host uses bad grammar • Host has unkempt appearance • Hosts uses poor body language (slouches) • Our Tool • Host smiles and conveys excitement about the new tool • Host is nicely dressed • Host greets people as they enter the experiment

15. Create Expectations • Their Tool • Host says “there is a chance our tool might work” • Host says “we think our tool produces marginally better search results” • Our Tool • Host expresses confidence about the performance of the new search tool. • Host says “ we are excited about how effective our tool is”

16. Control Comparatives • Their Tool • Begin with a warm-up exercise using state-of-the-art technology that is well polished. • Show the group the best of breed searching tools available. • Our Tool • Run the warm-up exercise on an old, slow computer attempting an impossible task. • Provide a poor tool to achieve the task.

17. Get Them to Commit to Your Result • Their Tool • Conduct the following pre-experiment survey: • I am a good searcher who gets good results. • I am a jerk • (Please choose only A or B) • Our Tool • Conduct the following pre-experiment survey: • I learn quickly and do well with new tools. • I am a jerk • (Please choose only A or B)

18. Give Them Cues About How They Did • Their Tool • Host frowns when he/she looks at the screen. • Host shakes head and makes low grunting noises. • Our Tool • Host smiles as he/she looks at the participants screen. • Host takes notes by noticeably checking items off a list while nodding head.

19. Give Them Time to Reconstruct Memory • Their Tool • Host ends the session by saying “Wow that took a long time….um…come back next week to fill out the survey. • Our Tool • Host ends the session by saying “we were doing so well, we lost track of time. Oh well, just come back next week to fill out the survey.”

20. Section 2: Survey Question Biases

21. Survey Questions Biases Question phrasing, what answer choices are presented and how they are presented... !!?!! ??!??

22. On September 27, 2001, President Bush put forth the UN Hostile Powers resolution forbidding UN Humanitarian Economic aid to Afghanistan. Was President Bush within his powers as the President of the US to enact such a United Nations Resolution? a. President Bush was definitely within his power. b. President Bush overstepped his authority. Will you vote in favor of a special finance package costing the average taxpayer $475 to finance Operation Enduring Freedom? a. Yes, since it is likely Congress with provide for another tax rebate when the economy turns around.b. No, $475 in taxes negates the recent tax rebate.I would need to understand more about the finance package.

23. pseudo-opinion On September 27, 2001, President Bush put forth the UN Hostile Powers resolution forbidding UN Humanitarian Economic aid to Afghanistan. Was President Bush within his powers as the President of the US to enact such a United Nations Resolution? Framing a. President Bush was definitely within his power. b. President Bush overstepped his authority. Ordering Forbid vs. not allowing Attitude/Behavior Will you vote in favor of a special finance package costing the average taxpayer $475 to finance Operation Enduring Freedom? a. Yes, since it is likely Congress with provide for another tax rebate when the economy turns around.b. No, $475 in taxes negates the recent tax rebate.I would need to understand more about the finance package. Gain/Loss Filtering

24. Research Life Cycle: Observation • Through the use of surveys, observations verify or contradict MIS research hypotheses. • If the survey is biased, the research is nullified. • Valid theories could be unnecessarily quashed. • If the survey is manipulated to reinforce the hypothesis, the research will not withstand further investigation. • This will hider the acceptance of MIS as a discipline

25. Section 3: Models of Decision Making

26. Expected Utility Theory • --A “normative” theory of behavior • --Rational decision making principles • Ordering of alternatives • Dominance • Cancellation • Transitivity • Continuity • Invariance Utility

27. The Allais Paradox-- Violation of Cancellation Principle Alternative A: $1,000,000 for sureAlternative B: A 10% chance of getting $2,500,000, an 89% chance of getting $1,000,000, and a 1% chance of getting $0 Alternative A: An 11% chance of getting $1,000,000, and an 89% chance of getting $0 Alternative B: A 10% chance of getting $2,500,000, and a 90% chance of getting $0 The paradox is that anyone choosing Alternative A in the first situation should also choose Alternative A in the second—otherwise, the Cancellation Principle is violated.

28. Intransitivity If the difference in intelligence between any two applicants is greater than 10 points, choose the more intelligent applicant. If the difference between applicants is equal to or less than 10 points, choose the applicant with more experience.

29. Value Losses Grains Prospect Theory--Improvement • replaces notion of utility with value • different value functions exist for gains and losses (Endowment Effect)

30. Prospect Theory--Improvement • People’s tendency to overweight small probabilities. • A reduction of the probability of an outcome by a constant factor has more impact when the outcome was initially certain than when it was merely probable—Certainty Effect

31. Other Alternatives to Expected Utility Theories • Satisficing • Regret Theory • Multi-attribute Choice • Non-compensatory Strategies

32. Conclusions in MIS Field • Take caution in making assumptions and principles—they are easily violated. • Design as many experiments as you can, and consider as many conditions as you can to make your principle complete.

33. Section 4: Representativeness Availability Risk Anchoring Randomness Causation Attribution

34. Heuristics And Biases • People rely on heuristic when facing complicate decision • Advantage: normally “optimal” answer; reduce time and energy • Disadvantage: lead to biases and inconsistency • Focus: the process reaching the conclusion+consequent biases

35. Representativeness Heuristic Definition: Judge probability by the degree to which A is representation of B • Example1: • P(A) > P(AB) • Don’t be misled by highly detailed scenarios • Example2:The law of small numbers • gambler’s fallacy vs. the hot hand • Remember that chance is not self correcting • Don’t expect too much alternations

36. Representativeness Heuristic (2) • Example3: • use base rate information only when it’s consistent with their intuitive theories of cause and effect • Whenever possible, pay attention to base rates • Example4: • tendency to make “nonregressive” predictions • Don’t misinterpret regression toward the mean

37. Availability Heuristic Definition: judge probability by the ease with which the instance can be brought to mind Examples: media, difficult to generate, visualize • The limits of imagination: • difficult-to-imagine • extremely negative outcome

38. Vividness Heuristic • Definition: • concrete or imaginable; emotionally interesting or exciting; close in space or time • Examples: individual testimonials • it does exist, but is limited(time, laboratory research) • how to conquer: explicitly comparing

39. Probability and Risk • Bias in heuristic • More statistics: Bayes’ theory; • Wishful thinking: “happens to me? Never!” • Compound events: Welcome to the real world! • Each of all 500 components has the rate of 99% working great, ….now you feel better? • I am the expert…..so what? • Perception of risk are strongly biased in the direction of preexisting view.

40. Probability and Risk (2) • Managing the information system • Deal with new information • Maintain accurate records • Avoid conservatism • Avoid convenience • Be objective • Be aware of wishful thinking • Break component events into simple events • Realize different perspectives • Reduce risk in system building

41. Anchoring and Adjustment • Introductory example: Average January temperature in Pocatello, Idaho • The insufficient adjustment up or down from an original starting value, or anchor. • Very Robust • Works with extreme anchors • Examples • Real estate • Software development • “Give me a preliminary estimate…”

42. Anchoring and Adjustment in Research • Possible problems • Anchoring on previous research • Anchoring on a “hunch” • Solutions • Be skeptical of previous research • Be thorough with methodology

43. Perception of Randomness • Coincidence • Odds of particular episode happening are low, but odds of some similar episode happening somewhere are high • Examples • Dr. Booker’s story of meeting Dr. Nunamaker • Which one is more random? • 0111001000111001011011 • 0010101010110101000101

44. Randomness and Research • Finding patterns in research data that don’t exist • Stick to the methodologies and statistical analysis • Coincidences happen • Take advantage of those coincidences that happen • Increase the odds of coincidences by networking

45. Correlation, Causation and Control (CCC) • Correlation: whether two variables are related. • Illusory correlations • Common sense dominated • bacon-tiger vs. bacon-egg • Invisible correlations: • Absence of expectation • meat consumption vs. colon cancer

46. CCC (2) • Causation • Correlation and Causation • Control • Self confident: I can control myself better! • Helps that harms: connections between health and a sense of control

47. CCC (3) • Take-aways • Bias in information colleting and decision making • Focus on more than confirming and positive cases • Observation vs. expectation • Distinguish between correlation and causation

48. Attribution Theory • Definition: Attribution theory is a psychological theory about how people make “causal attribution,” or explanations for the causes of actions and outcomes

49. Important Exception • Attribution theory works most of the time, but there are several important exceptions • When people disregard consensus information • Salience information has more impact • Behavior is the most salient thing in a social setting

50. Important Exception (2) • Difference in focus between actors and observers • People rely heavily on the most salient factors at the time • Other attributional biases