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A Logic of Diversity II

A Logic of Diversity II. Scott E Page Complex Systems, Political Science, Economics and Institute for Social Research University of Michigan Santa Fe Institute. Enlarging The Mantra. Identity, Training, Experiential Diversity. Diverse Perspectives. Better Outcomes.

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A Logic of Diversity II

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  1. A Logic of Diversity II Scott E Page Complex Systems, Political Science, Economics and Institute for Social Research University of Michigan Santa Fe Institute Michigania 02005

  2. Enlarging The Mantra Identity, Training, Experiential Diversity Diverse Perspectives Better Outcomes Michigania 02005

  3. Monday’s Talk: Unpacking The First Box Diverse Perspectives Michigania 02005

  4. Monday’s Talk: Unpacking The First Box Perspectives Heuristics Interpretations Michigania 02005

  5. Today’s Talk: Demonstrating Causality Better Outcomes Diverse Perspectives Michigania 02005

  6. Specific Tasks Problem Solving Prediction Preference Aggregation Michigania 02005

  7. Why Construct Models? Models allow us to provide conditions for when a statement is true. The Pythagorean Theorem: ``A-squared equals B-squared plus C squared’’ only holds for right triangles. Michigania 02005

  8. Finding the Conditions ``Two heads are better than one!’’ ``Too many cooks spoil the broth’’ Which one wins? Which do we apply in a given setting. Michigania 02005

  9. Finding the Conditions ``Two heads are better than one!’’ ``Too many cooks spoil the broth’’ Condition: For an irreversible process, too many cooks spoil the broth. Michigania 02005

  10. Swarm of Bees Almost all of social science looks at averages and changes in those averages. Analogy: if you look at a swarm of bees, the path of any one bee is hard to predict and understand, but in the swarm all of those idiosyncratic behaviors cancel out and we can identify general trends. Michigania 02005

  11. The Buzz Bee hives must stay around 96 degrees in order for bees to reach maturation. Bees achieve this by genetic mechanisms that drive two behaviors: When hot: fan out or leave the hive When cool: huddle together Michigania 02005

  12. Diversity and Homeostasis Genetically homogeneous bees: All get cool (or hot) at the same time. Temperature in hive fluctuates wildly. (1930’s heating system) Genetically diverse bees: Get cool (or hot) at different temperatures. Temperature stabilizes. Michigania 02005

  13. Rethinking the Swarm The logic of cancellation does not hold because there are feedbacks between the bees. Those feedbacks imply we cannot look at averages. Groups of people solving problems, making predictions, and making choices create feedbacks in abundance. Michigania 02005

  14. Problem Solving Michigania 02005

  15. Problem Solving Perspectives Heuristics Michigania 02005

  16. The Idea 135 A,b,x 91 x,M Thermometer: Toolbox: SAT,IQ skills, heuristics Michigania 02005

  17. Perspective number of chunks size Ben & Jerry’s Ice Cream Array Michigania 02005

  18. Heuristic number of chunks size Ben & Jerry’s Ice Cream Array Michigania 02005

  19. Consultant perspective: caloric rank Michigania 02005

  20. Consultant perspective: caloric rank heuristic: look left and right Michigania 02005

  21. Performance • Average Performance Given • solution in perspective • application of heuristics • Ben and Jerry • average quality of solution = 82 • Consultant - average quality of solution = 74 Michigania 02005

  22. Perspective Diversity Ben and Jerry stuck at 83 75 80 83 73 81 Michigania 02005

  23. Perspective Diversity Ben and Jerry stuck at 83 consultant Gets to 86 75 80 83 73 81 80 86 83 74 Michigania 02005

  24. Diversity or Ability: A Test Create a bunch of artificial problem solving agents and rank these agents by their average performances on a difficult problem. All of the agents must be “smart” Michigania 02005

  25. Two Groups • Group 1: Best 20 agents • Group 2: Random 20 agents Have each group work collectively - when one agent gets stuck at a point, another agent tries to find a further improvement. Group stops when no one can find a better solution. Michigania 02005

  26. The IQ View 139 138 137 111 121 84 135 135 132 135 75 31 Alpha Group Diverse Group Michigania 02005

  27. And the winner is.. “Most of the time” the diverse group outperforms the group of the best by a substantial margin. See Lu Hong and Scott Page Proceedings of the National Academy of Sciences (2002) Michigania 02005

  28. The Toolbox View ABC ABD ACD AEG AHK FD BCD BCD ADE BCD EZ IL Alpha Group Diverse Group Michigania 02005

  29. Formal Version Theorem: Given a set of diverse problem solvers, a random collection outperforms a collection of the “best” individual problem solvers provided -the set is large -the problem is hard -the problem solvers are smart Michigania 02005

  30. Prediction . Michigania 02005

  31. Prediction . Interpretations Mental Models Michigania 02005

  32. The Madness of Crowds We tend to think of crowds of people as irrational mobs. And that can be true. When people hear the ideas and opinions of others, they often succumb to peer pressure rather than speaking their own minds. Michigania 02005

  33. Which Line is Longer? A: _____________ B : ___________ Michigania 02005

  34. The dim boy claps because the others clap. - Richard Hugo Michigania 02005

  35. The Wisdom of Crowds If people do not hear the opinions of others, or if they render their true predictions anyway crowds can be incredibly wise. Michigania 02005

  36. Suroweicki’s Examples Morton Thiokol’s stock plunge Prediction Markets Hollywood Stock Exchange Iowa Electronic Market Sports Betting Markets Who Wants to be a Millionaire 1906 West of England Fat Stock and Poultry Exhibition Michigania 02005

  37. Two Separate Phenomena • Information known by part of the crowd • Aggregative diverse predictive models Michigania 02005

  38. Revealing Known Information Which of the following books would you NOT find in the Point o’ Pines Library A. The Periwinkle Steamboat - Lancaster B. Curtains - Agatha Christie C. Unabridged Crossword Puzzle Dictionary D. I am Charlotte Simmons - Tom Wolfe Michigania 02005

  39. Information Rising Suppose that no one know the answer but that 18 people know one of the books on the list is in the library and that 18 people know two of the books on the list are in the library. This means that 64 people guess randomly. Michigania 02005

  40. Information Rising Of 64 Clueless: Correct answer gets 16 Of 18 know one: Correct answer gets 6 Of 18 know two: Correct answer gets 9 Total 31 Other answers get 23 (on average) Michigania 02005

  41. The Answer Is… Which of the following books would you NOT find in the Point o’ Pines Library B. Curtains - Agatha Christie Michigania 02005

  42. Aggregating Diverse Predictions In most of the situations described, people do not know the answer yet. We can assume that people have diverse predictive models. We’d like to understand how that aggregation occurs and what roles diversity and ability play. Michigania 02005

  43. Reality Charisma H MH ML L H Experience MH ML L G G G B G G B G G G B B B B G B B Michigania 02005

  44. Experience Interpretation 75 % Correct H Experience MH ML L G G G B B G B G G G B G G B G B B B B B G B B B Michigania 02005

  45. Charisma Interpretation H MH ML L 75% Correct G G G G G B B G G B G G B G B B B G B B B G G B B Michigania 02005

  46. Balanced Interpretation H MH ML L 75% Correct H Good to be extreme on one MH measure, bad on other ML L G B G G B G B G B G G B B B G B G G B B Michigania 02005

  47. Voting Outcome Charisma H MH ML L H MH ML L GGB GGG GBG BGB GGG GGB GBB G GBG BGG BBG BBB BBG BGB BGG BBG BBB Michigania 02005

  48. The Mathematics of Prediction Prediction: # runs scored by winning softball team MonTueWed Brad 8 10 9 Matt 10 12 8 Michigania 02005

  49. “Crowd’’ Prediction MonTueWed Brad 8 10 10 Matt 10 12 8 Crowd 9 11 9 Michigania 02005

  50. Actual Numbers MonTueWed Brad 8 10 10 Matt 10 12 8 Crowd 9 11 9 Actual 8 12 9 Michigania 02005

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