1. On Models and Modeling

2. You may recall this scene from Monty Python’s Holy Grail…

3. “Camelot!”

5. “It’s only a model”

6. Why concern ourselves with models?

7. Models are pervasive & powerful.

8. Models guide emergency plans

9. Models guide political policy

10. Models determine teams tasks & rewards in the workplace

11. Basic passenger Safety. Mastery of unusual situations. New equipment. Models train pilots

12. Models shape learning. Everyone visualizes this key relationship as a model.

13. Models interpret cultural behavior “the pursuit of reputation… is the overriding preoccupation of human life.” Social Psychology

14. “Consumption is always social; partitioning of goods … reflects an underlying partitioning of society.” Social Psychology Models interpret cultural behavior

15. THEORY OF EMULATION the upper class is happy all the time; Social Psychology Models interpret cultural behavior

16. THEORY OF EMULATION the upper class is happy all the time; the upper middle class is happy 50% of the time; Social Psychology Models interpret cultural behavior

17. THEORY OF EMULATION the upper class is happy all the time; the upper middle class is happy 50% of the time; the lower middle class is happy 25% of the time; Social Psychology Models interpret cultural behavior

18. THEORY OF EMULATION the upper class is happy all the time; the upper middle class is happy 50% of the time; the lower middle class is happy 25% of the time; the lowest class is (relatively) unhappy all of the time. Social Psychology Models interpret cultural behavior

19. Models guide your financial choices: What will I need to be comfortable 20 years from now?

20. Models determine how your personal choices are tracked and met.

21. Models are an important intersection between technology and human values.

22. Models simplify complexity When scientific knowledge is too complicated for us to fully understand.

23. Models make justifications for past and future action. Human values are expressed as variables in the model.

24. Models make justifications for past and future action. “What if we do this? What if that happens? What does the model show?”

25. If models simplify complex information and offer justifications for action…

26. …then what questions should you ask of a model? ?

27. Our goal: To develop questions that can be applied to any model from any discipline.

28. I.Types of Models II.Definitions of Models III.Questions IV.When to Question

29. I. What are the different types of models? (we encounter all of these in childhood)

30. A model is a rough representation of reality. The purpose is just play, fun, taking on a challenge.

31. A model is an exact representation of reality. The goal is exactitude. Details & scale are important. A model can become a big project.

32. Not to scale. Conceptually easier to grasp because not to scale. A model is a convenient representation of reality.

33. A model is a normative representation of reality. Variant forms and details are omitted.

34. A model is a focused representation of reality.

35. Among all possible relationships, one is featured.

36. A model can be a meta-metaphorical representation of reality. “The Circulatory System is the main transportation and cooling system for the body.”

37. A model can be a meta-metaphorical representation of reality. “The Red Blood Cells act like billions of little UPS trucks carrying all sorts of packages that are needed by all the cells in the body….”

38. A model can be a meta-metaphorical representation of reality. “White Blood Cells are the paramedics, police and street cleaners of the circulatory system.” Analogous relationships are featured.

39. By compiling our experiences, we see 6 aspects of models: Rough – artistic, play, fun Exact – artistic, but also predictive use Normative – heuristic, applicable to all cases Convenient – conceptually easier to grasp Focused – conceptually easier to grasp Meta-Metaphorical – conceptually easier to grasp

40. We can focus on 4 of these aspects: Rough – artistic and fun Exact – artistic and predictive Normative – applicable to all cases Convenient, Focused, & Meta-metaphorical – easier to grasp

41. The Sony Aibo: fun, trainable, the everydog …& easier to manage, too!

42. I.Types of Models II.Definitions of Models III.Questions IV.When to Question

43. II. Definitions of models (What do professionals say about models?)

44. The give the elements of models, the rationale for models, and the uses of models.

45. In mathematics, model theory is the study of the representation of mathematical concepts in terms of set theory... Wikipedia Elements of models

46. …It assumes there are pre-existing mathematical objects, and asks what can be proven given the objects, the relationships amongst the objects, and a set of axioms. Wikipedia Elements of models

47. pre-existing objects relationship amongst the objects a set of axioms Elements of models

48. A method of expressing relationships when measuring the real world is impractical. mc2consulting Company Rationale for models

49. Models help us to visualize the problem, to break it down into discrete, manageable units…Like any other instrument, a model assumes a specific intention of its user. Educational Design Rationale for models

50. Measuring the real world is impractical Visualizing the problem, making it manageable Rationale for models

51. A prototype or surrogate of a complex situation. It can be a physical model, such as an architectural model of urban design, or a mathematical model of interactions of many variables... Course on Future Studies, University of Arizona Uses for models

52. It can be a stand-alone tool to evaluate different approaches using different assumptions. Course on Future Studies, University of Arizona Uses for models

53. A representation of the components of a process, system, or subject area, developed for understanding, analysis, improvement, and/or replacement of the process. Interoperability Clearinghouse Uses for models

54. to evaluate different approaches using different assumptions. for understanding, analysis, improvement, and/or replacement of the process. Uses for models

55. I.Types of Models II.Definitions of Models III.Questions IV.When to Question

56. How do we question models? TYPES: Rough – fun Exact – predictive Normative – applicable Convenient, Focused, & Meta-Metaphorical – easier to grasp

57. How do we question models? TYPES: Rough – fun Exact – predictive Normative – applicable Convenient, Focused, & Meta-Metaphorical – easier to grasp ELEMENTS pre-existing objects operations amongst the objects a set of axioms

58. How do we question models? TYPES: Rough – fun Exact – predictive Normative – applicable Convenient, Focused, & Meta-Metaphorical – easier to grasp ELEMENTS pre-existing objects operations amongst the objects a set of axioms RATIONALE real measuring is impractical to visualize & manage the problem

59. How do we question models? TYPES: Rough – fun Exact – predictive Normative – applicable Convenient, Focused, & Meta-Metaphorical – easier to grasp ELEMENTS pre-existing objects operations amongst the objects a set of axioms RATIONALE real measuring is impractical to visualize & manage the problem USES evaluate approaches using different assumptions. for understanding, analysis, improvement, and/or replacement of a process.

60. Questions: 5 are about information 1)What kind of data is being represented? 2)Of this set, is all data being shown, or is only some data being shown? Is the data exact or normative?

61. Questions: 5 are about information 3) Which data are being tracked and measured in real time, and which are generated by the model’s relationships and axioms?

62. Questions: 5 are about information 4) Which relationship is being highlighted? Is this relationship linked analogously to another model? 5) If the ultimate purpose of the model is predictive, is it possible to prove and/or falsify the data?

63. Questions: 3 are about interest 6) Who commissioned the model? 7) What was the purpose of the model? Was understanding, analysis, improvement or replacement of the current system explicitly mentioned? 8) Is the new model replacing an existing model?

64. Now we’ve developed some questions.

65. How do we apply them?

66. Information: What kind of data is being represented?

67. Information: Is the data exact or normative?

68. Information: Are the data are being tracked and measured in real time? Are the data generated by a model or by instruments?

69. Information: Is it possible to prove or falsify the predictions?

70. Information: Can these relationships be linked by analogy to another model?

71. Interest: Who commissioned the model?

72. Interest: What was the purpose of the model?

73. Interest: Is the new model replacing an existing model?

74. Do all the questions apply to all models?

75. YES.

76. But if you can only ask 2 questions…. Information Is there any data in the model which is not falsifiable? Interest Is replacement one of the stated purposes of the model?

77. I.Types of Models II.Definitions of Models III.Questions IV.When to Question

78. When Models Go Bad…

79. 5 Reasons to question the model 1) When something just looks wrong.

80. Godzilla in the bathtub

81. 5 Reasons to question the model 2) When there is only one possible choice to be made.

83. 5 Reasons to question the model 3) When data consistently cannot be explained.

84. 5 Reasons to question the model 4) When the model is not elegantly economical.

85. The Ptolemaic Universe

87. 5 Reasons to question the model 5) When the category “human” is in question.

88. 5 Reasons to question the model When a group of “former” humans are re-classified as non-human. (losing rights)

89. Cesare Lombroso’s criminal types

90. 5 Reasons to question the model When a group of non-humans are re-classified as human. (obtaining rights)

91. So long, and thanks for all the fish.

92. Great Model Shifts Happen When… 1) When something just looks wrong. 2) When there is only one possible choice. 3) When data consistently cannot be explained. 4) When the model is not elegantly economical. 5) When the category “human” is in question.

93. IMAGE CREDITS Cindy Crawford http://cutechoice.com/cgi-bin/show.pl?celebname=Cindy_Crawford&pno=8 http://cutechoice.com/cgi-bin/show.pl?celebname=Cindy_Crawford&pno=8 Limits to Growth http://www.healthtreasures.com/limits-to-growth-preface.html http://www.healthtreasures.com/limits-to-growth-preface.html Monty Python’s Holy Grail http://www.intriguing.com/mp/holygrail.asp http://www.intriguing.com/mp/holygrail.asp Katrina Track University of Wisconsin-Madison Cooperative Institute for Meteorological Satellite Studies http://cimss.ssec.wisc.edu/tropic/archive/montage/atlantic/2005/KATRINA-track.gif http://cimss.ssec.wisc.edu/tropic/archive/montage/atlantic/2005/KATRINA-track.gif World Gas Reserves, Society of Petroleum Engineers http://www.spe.org/specma/binary/images/2919957WORLDGASRESERVES.gif http://www.spe.org/specma/binary/images/2919957WORLDGASRESERVES.gif http://www.globalclassroom.org/hemo.html Myers-Briggs Personality Profiles http://www.uwsp.edu/education/lwilson/learning/graphics/kirbys1.gif http://www.uwsp.edu/education/lwilson/learning/graphics/kirbys1.gif

94. IMAGE CREDITS Pilot Training http://www.link.com/gallery/f22_fmt_high_res.html Supply and Demand http://www.sci.wsu.edu/math/Lessons/SupplyAndDemand/theory.html http://www.sci.wsu.edu/math/Lessons/SupplyAndDemand/theory.html Notes on Miller Personal notes from ES 10 Insurance Life Expectancy http://web2.minnesotamutual.com/IMAGES/EDUCATE/LIFE_EXPECTANCY.GIF My Simon http://www.mjweber.com/Confessionsmm/bots/bots.htm Popsicle Projects http://pacifi.ca/models.html http://pacifi.ca/models.html http://www.tinypineapple.com/archives/2003/10/disneyland_day_five_a_theme_park_with_a_ theme.html Car Models www.oakridgehobbies.com

95. IMAGE CREDITS Solar System Models http://www.brownmunoz.com/Universe/Universe_intro.html http://www.brownmunoz.com/Universe/Universe_intro.html Visible Woman http://www.plumcreekmarketing.com/07science/01images/fullsize/160321.jpg http://www.plumcreekmarketing.com/07science/01images/fullsize/160321.jpg USGS Water Cycle http://ga.water.usgs.gov/edu/watercycle.html http://ga.water.usgs.gov/edu/watercycle.html Circulatory System http://www.globalclassroom.org/hemo.html Aibo and Aibone http://gamma.cs.unc.edu/COMP290-58/aibo.jpg http://www.mobilityparty.com/mobility_2003/press/ Axiom http://www.jtauber.com/blog/2005

96. IMAGE CREDITS Ocean http://www.spartanburg2.k12.sc.us/OES/Ocean%20waves%20clipart.jpg http://hyperphysics.phy-astr.gsu.edu/hbase/waves/watwav2.html Replacement Model http://web.pdx.edu/~stipakb/download/PA557/ReplacementModelExample.gif Mae West http://photos1.blogger.com/img/96/3696/320/Mae%20West.jpg Godzilla http://www.freerepublic.com/focus/chat/1160331/posts Lombroso Criminal Types http://ledroitcriminel.free.fr/utilitaires/iconographie/iconographie_1/lombroso_1_jpg_view.htm http://photos1.blogger.com/img/96/3696/320/Mae%20West.jpg http://www.freerepublic.com/focus/chat/1160331/posts http://ledroitcriminel.free.fr/utilitaires/iconographie/iconographie_1/lombroso_1_jpg_view.htm Dolphins – So Long, and Thanks for All the Fish http://www.spawar.navy.mil/sandiego/technology/mammals/animals.html Ptolemaic Universe http://www.luminarium.org/encyclopedia/medievalcosmology.htm http://abyss.uoregon.edu/~js/ast121/lectures/lec02.html http://www.luminarium.org/encyclopedia/medievalcosmology.htm http://abyss.uoregon.edu/~js/ast121/lectures/lec02.html