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Mihnea Moldoveanu Desautels Professor of Integrative Thinking Rotman School of Management

Designing The Thinker of the Future: “The Pedagogy of Integrative Thinking” Session 1, Shantou University, November, 2010. Mihnea Moldoveanu Desautels Professor of Integrative Thinking Rotman School of Management University of Toronto. Outline. Why higher education ‘Works ’:

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Mihnea Moldoveanu Desautels Professor of Integrative Thinking Rotman School of Management

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  1. Designing The Thinker of the Future: “The Pedagogy of Integrative Thinking” Session 1, Shantou University, November, 2010 Mihnea Moldoveanu Desautels Professor of Integrative Thinking Rotman School of Management University of Toronto

  2. Outline • Why higher education ‘Works’: The “Selection Engine”, Network Building” and “Conversational Capital” Arguments • Why higher education ‘Does not Work’: The “Development Hole” Argument • What Could and What Should be Done? The Opportunity Set and a Solution

  3. Why Higher Education ‘Works’: The Selection Engine Argument VALUE AS FUNCTION OF SELECTION CRITERIA: General intelligence(0.37-0.4); HIGH SCHOOL (12 YRS) GRADES (g,c) Conscientiousness (0.25-0.32) COLLEGE (4 YRS) THE DEVELOPMENT OPPORTUNITY SAT (g), GRADES (g,c) WORK ASSIGNMENT (2-4 YRS) COLLEGE GRADES, REFERENCES GRADUATE SCHOOL(2 YRS) TEST SCORES (GMAT, LSAT, MCAT), REFERENCES, GRADES GRADES, REFERENCES Rat Race t

  4. The “Social Capital” Argument Network connectedness and centrality of trainee increase in a discontinuous fashion as a result of enrolment and participation in the program. Social networking skill set of participant likewise increases. CA CA S S S S S S “Pre-” Professional Network “Post-” Professional Network

  5. The “Conversational Capital” Argument knows that… know that… MBA “A” MBA “B” EBITDA CAPM Black-Scholes Real Option Competitive Advantages Group Think knows meaning of knows meaning of MBA lingo Language games played out in the classroom become lubricants of “management level” communications as they are mutual or common knowledge among trainees

  6. These “value added features” are substitutable, however, and increasingly substituted by recruiters:

  7. …who, at the same time, are asking for skill sets that are not currently being developed in higher education programs source: Deep Dive™ Project (ongoing)

  8. Analog Circuit Design SUPPORTING DISCIPLINES RF Circuit Design Logic Circuit Design EXPLICIT EXPERTISE RF Antenna Design RF system design Hardware systems design System Testing TACIT EXPERTISE Competitive Analysis Strategy negotiate motivate Network Theory Network Design INTEGRATE Market Demand Analysis communicate Programming Languages and Logics Marketing Software Design Financial Analysis Financial Reporting Operating System Design Accounting Science Finance Theory Auditing Science The Integrative Gap: Consider the Expertise Map of General Manager in Large Telecommunications Equipment Manufacturer (eg: Nokia, Cisco, Huawei, etc.) Linear Systems Theory SUPPORTING BASIC SCIENCES Boolean Logic Electromagnetic Wave Theory Statistical Analysis Game Theory Queuing Theory Psychology Logic Sociology Linguistics Stochastic System Theory Microeconomics

  9. Local Integration: How it Works ENGINEER’S VIEW MARKETER’S VIEW CLASH • Core ‘argument clinchers’ or ‘anchors’: • Provability • Optimality • Deductive logical closure • Core ‘argument clinchers’ or ‘anchors’: • Face validity (smell test) • Appropriateness to multiple constraints • Inductive logical closure “Understanding” and “real communication” require not only “suspension of disbelief” but also familiarity with alternative modes of discourse, representation and justification and cross-disciplinary discourse management.

  10. The Problems of the World: A Map “Complex” “Simple” • Well specified, multi-dimensional goals and metrics; • logically deep pathways from statement to solution • Many dependant and independent variables • Convergence tests are either clearly defined or definable as a function of resource availability and problem complexity; fulfillment is independent • Well specified, uni-dimensional goals and metrics; • logically shallow pathways from statement to solution • Few dependant and independent variables • Clearly defined convergence tests and criteria whose fulfillment is independent INTEGRATIVE THINKING: RECOGNIZE WICKED PROBLEMS AND TURN THEM INTO (LOCALLY) TRACTABLE PROBLEMS PROBLEMS THE AGE OF SCIENCE THE AGE OF DESIGN “Wicked” • Goals and objectives have multiple, potentially incommensurable and conflicting specifications • Logical sequence from statement to solution depends on specification and choice of logic • Number of variables depends on specification and can change as a function of the solution process • Solution criteria are negotiated; their fulfillment conditions are “user-dependent”

  11. TRANSFORMATIONAL “Algorithmic” Total New Jobs 1998 – 2004 N = 6.4MM “Super-algorithmic” The Market Opportunity for the High Value Decision Maker NEW JOBS, 1998-2004 (Adapted from Johnson, Manyika & Yee, 2004) TRANSACTIONAL TACIT

  12. The Problems of the World: A Unified Picture 12 Forecasting/Prediction: Given n points in a time series, what is the n+1st point? Optimization: Given objective and constraints {Ci}, find a function (structure, process, procedure, algorithm) that maximizes and obeys {Ci} Strategic Manager: What problem am I solving? Analysis: Given a data set {d}, find a model, M (causal, functional), that is most likely to have generated {d} Adaptation: Given model M (structure, procedure), that is consistent with data {dk}, find optimal update rule R(M) that preserves consistency with new and possibly unforeseeable evidence {en}

  13. Problems: A Value Map Easy (Linear or constant) Value Added Transformation 4 Tractable Hard (nonlinear) Value Added Transformation 3 Well Structured Intractable (NP hard) Value Added Transformation 2 Well Defined Ill Structured (wicked) (Search space defined but changes as a function of search process Problems Value Added Transformation 1 Ill Defined (No well defined current, desired state, search space)

  14. TWO VIEWS OF EDUCATION “INFORMATION” (KNOW-WHAT) [current state: what do I know/remember?] “KNOWING” EDUCATION “BEING, DOING” “TRANSFORMATION” (KNOW-HOW) [desired state: what problems can I solve with what I know?]

  15. WHAT IS “KNOW-HOW”? SOLVE PROBLEMS FRAME PROBLEMS KNOW-HOW “MAKE IT WORK”: IMPLEMENT SOLUTIONS COMMUNICATE AND LEGITIMIZE SOLUTIONS

  16. Tough- mindedness: Experiment with and enact new model without defensiveness. The Integrative Thinker: A Conceptualization Nimble-mindedness: Recognize radical difference and otherness of different models Big- mindedness: Behold radically different models without paralysis. Integrative thinking: “the ability to think and act responsibly and responsively in the face of multiple, incommensurable and possibly conflicting models of oneself, the world and others”

  17. Componential Analysis of Integrative Thinking ASSOCIATIVE REASONING (Correlational speed and informational breadth) EMPATHIC ACCURACY (Theory of mind) DEDUCTIVE REASONING (Logical depth) AFFECTIVE FLEXIBILITY (Adaptiveness of mood or emotion) INTEGRATIVE THINKING: “the ability to think and act responsibly and responsively in the face of multiple, incommensurable and possibly conflicting models of oneself, the world and others” PERCEPTUAL ADAPTIVITY (Adaptive focus of sensory attention) • EXECUTIVE FUNCTION • Recognition of emotional conflict • Resolution of emotional conflict • Self-command • DIVERGENT/LATERAL THINKING • Generation of options • META-COGNITIVE VERSATILITY • Adaptive modes of justification • Adaptive concepts and models 17

  18. The Integrative Brain: Can we “See” Integrative Thinking? [Etkin, Egner, Peraza, Kandel, Hirsch, Neuron, 2006]: Resolution of emotional conflict associated with rostral anterior cingulate cortex, whereas emotional conflict experience is associated with amygdala, dorso-lateral pre-frontal cortex and dorso-medial pre-frontal cortex, suggesting that an ‘integrative capability’ can be observed and potentially measured neurologically (fMRI). 18

  19. Similarly, we can localize and measure other brain functions on which integrative skills supervene... Right pre-frontal cortex  reasoning (Kroger et al, 2008) Left pre-frontal cortex  calculation (Kroger et al, 2008) Affective flexibility  amygdalar response time constant (Cunningham et al, 2008) Semantic processing  Broca/Wernicke areas Empathic Understanding/Theory of Mind  ‘mirror neurons of the visuo-motor cortex [Rizzolatti, 2004] Visual short term memory  posterior parietal cortex (Todd and Marois, 2004) 19

  20. Can we not only select, but develop integrative thinkers? Development Path: “Education”

  21. N The Integrator’s mind: mile wide, mile deep The Integrative Thinker’s Development Path Inch-deep, mile-wide mind How many things you think about Integrative thinking training path Inch-wide mile-deep mind K possible links among N variables How deeply do you think about it K N variables

  22. “Yes we can” – to quote Obama: mind/brain is plastic and adaptive to learning task. Transient changes in brain activation pattern induced by learning to juggle [Dragansky et al, Nature, 2004] Development Path: “Education”

  23. Business Education: Version 1.0 Marketing Accounting Finance Organizational Behaviour Production Release date: Harvard Business School, 1908

  24. Marketing Accounting Finance Organizational Behaviour Production Micro-Economics Micro-Economics Psychology Micro-Economics Social Psychology Cognitive Psychology Micro-Economics Operations Research Business Education: Version 2.0 Release date: 1960-1970

  25. Ontological Reductivism: Simplification and Specialization Around Complex Object ‘Organization’ ‘organization is (nothing but) a power-based hierarchy’ SIMPLIFY ‘organization is (nothing but) a failure of the market ‘organization is (nothing but) a nexus of contracts among principals and agents SCHOLARLY MIND ORGANIZATIOIN Conflict sociology SPECIALIZE Neoclassical economics Modern agency theory

  26. Ontological Reductivism: Simplification and Specialization Around the Complex Object ‘Person’ ‘nothing but a set of utilities and beliefs’ SIMPLIFY ‘nothing but a set of conditional responses’ ‘nothing but a set of neurophysiological process’ SCHOLARLY MIND PERSON (other or self) Neurobiological model of man Behaviourist model of man SPECIALIZE Economic model of man

  27. What Academics Know How to Do Build models/ theories Test models/ theories Argue for/against models Engage in “cross-disciplinary discourse across models Transferrable skill set Trainees

  28. Articulation module: Model building Validation module: Model testing and implementation Integration module: Cross-model dialogue A Solution Concept for Higher Education: Training as the Cultivation of Useful Cognitive-Behavioral Modules Transferred from Academic to Trainee High Value Decision-Maker “Not only know-what and know-who.... “But also know-how...”

  29. The Physician-Scientist Training Program: Deep-Structure Analysis of Know-How Transfer Across Know-What Domains D1 D2 Design of Intervention Elimination-Oriented Experimentation & Diagnosis Recognition of Interpretation of Disease Signs Differential Diagnosis Generation D3 D4 … DM modal declarative modal declarative LOGIC MODE OF INFERENCE inductive deductive abductive causal functional causal and functional intentional MODE OF EXPLANATION “Basic medical science generates inputs in the form of disease models, causally plausible generations, hypothetico-deductive logic of experimentation”

  30. “FACTS ABOUT TRADING BEHAVIOR’ “Financial Engineering” Prescriptive Model of Optimal Adaptive Behavior Normative Model of Choice & Belief Formation “FINANCE THEORY’ “Self-reinforcing” mechanism for belief validation and selection (RCT & RBT) + “Installed base” of self-evident categories and ontologies (i.e. “money”, ROI, NPV, WACC + “Installed base” of self-evident problem statements Why Finance Training “Works”: Ontological Unification of Theory and Praxis

  31. The Personal Capital Model: What Integrative Thinking at Rotman Does FIT: Learn to build models Economics ITP: Learn to use models from YI course to solve real business problems use in use in Finance use in use in use in use in Accounting use in use in Managing People & Organizations use in use in Operations Management use in use in Marketing use in use in Organizational Behaviour use in use in Strategy Learn models and modeling strategies

  32. STATES OF META-PREFERENCE Ambivalence Commitment STATES OF AFFECT/DESIRE Obsessive desire “need passion” Weak Preference Strong Preference STATES OF COGNITION … STATES OF META-COGNITION Indifference WEAK STRONG KNOWN To represent states of desire, se a real-number index value function (“utility”) Self-evidence OBLIVION (Don’t know x or Don’t know that I Don’t know it) i.e. x > y iff certainty x ~ y iff risk x < y iff To represent states of belief, use a probability measure satisfying: uncertainty ambiguity COMMON KNOWLEDGE (Know x, know that I know that I know that I know x…) • Normality • Additivity • Sub-additivity • Regularity UNKNOWN inexpressibility inconceivability “Model Building Module”: A Modeling Approach to Understanding Human Choice

  33. Self-Modeling Exercise: 46Yo CEO of Public Company:“I am unfairly perceived as being manipulative, which often forces me to be manipulative in order to cut through the emotional dynamics that the perception generates.” …using reasons X would accept as valid given my knowledge state How to persuade X to do Y… …using reasons X may not accept as valid given my knowledge state “X as a Mind” CO-REASON WITH X’S MIND His Problem Statement: “How to get X to do Y” MANIPULATE X’S BRAIN “X as a Brain-Neuron-Muscle Machine” …using consciously designed behavior How to cause X’s body to behave in such a way as to produce Y… …using unconsciously produced behavior

  34. “Model Testing Module”: Cognitive and Emotional Landscapes of Justificationism and Falsificationism Justificationism Baseline ‘resting’ state: ‘knowing’, i.e. holding justified true beliefs; Proximate goal: supporting a belief with a reason for holding it; Long-term goal: certainty about knowledge; Guiding principle: truth’=‘certainty. Falsificationism Baseline ‘resting’ state: ‘testing’; Proximate goal: refutation of current belief; Long-term goal: elimination of refuted beliefs; Guiding principle: ’provisional truth=failure to find a refutation’.

  35. “Justificationist” “Falsificationist” Transition High - Level Developmental Blueprint • Principle 1: Cultivate ‘unknowing-ness’ as an everyday state of being or stance; • Principle 2: Cultivate questioning as a basic mode of interaction with experts and their knowledge and expertise; • Principle 3: Cultivate refutation-oriented testing as a basic mode of interaction with one’s own beliefs; • Principle 4: Cultivate controlled experimentation as a basic cognitive and behavioral discipline; • Principle 5: Cultivate poly-valence and multi-stability as a basic emotional and cognitive skill that grounds tolerance for internal and external conflict.

  36. Cognitive-Behavioral Module: ‘Justificationism’ Infinite Regress Belief B R1: Reason for B R2: Reason for R1 R3: Reason for R2 R4: Reason for R3 …. Logical Circularity R1: Reason for B, R1 Belief B R2: Reason for R1 Recourse to Absolute Certainty R1: Reason for B Belief B

  37. Cognitive-Behavioral Module: Sophisticated Methodological Falsificationism Confirmation Confirmation Hypothesis H1 Hypothesis G1 Belief B1 Belief A1 Refutation Refutation Hypothesis H2 Hypothesis G2 Confirmation Confirmation Hypothesis H3 Hypothesis G3 Belief B2: Fortified B1 Belief A2: Fortified A1 Refutation Refutation Hypothesis H4 Hypothesis G4 Confirmation Confirmation Hypothesis H5 Hypothesis G5 Belief B3: Fortified B2 Belief A3: Fortified A2 Refutation Refutation Hypothesis H6 Hypothesis G6 Choose B1 over A1 provisionally, but keep testing…

  38. Want to “innovate” within the current institutional landscape? Try this:

  39. Layer I:The Generative Sciences Mathematics, Analytic Philosophy, Artificial Intelligence, Hermeneutics, Complexity Theory Layer II: The Basic Sciences Economics, Psychology, Sociology, Anthropology, Political Science Layer III:The Applied Sciences Accounting, Finance, Strategy, Marketing, Organizational Behavior Layer IV:Knowledge-In-Action Fields of Managerial Practice The Communicative Structure of the ‘Idea Business’ Filter 1: Fit w/methods of layer II sciences Filter 2: Fit w/acknowledged problems of layer III Sciences Filter 3: Fit w/actual problems of layer IV “sciences”

  40. In summary... • Higher education ‘works’ as a selection engine, network builder and language game promulgator • Higher education ‘does not work’ (anymore) as a skill builder • Academia can choose to invest in the transfer of valuable skills its members have, which will be important to the thinker of the future • Innovation is possible even within the ‘confines’ of current institutional arrangements

  41. Back-up slides

  42. Consider choice between L1 &L2 : At the indifference point: L1 “a” : U (a) P(s) “b” : U (b) “s is true” Solve for p: “s is fake” “c” : U (c) 1 - P(s) In practice: U(a) = 0; U(c) = - (stake); U(b) = take. So: “how probable do you think s is?” → “how much would you bet to win $x if s is true and nothing otherwise?” How to Extract Probabilities From People by Observing Their Choices

  43. Event A = { S & P fall 5% or more next Monday} You believe: P(A) = ½; P(not-A) = ¾ You will take bets: A: U(A) = $1 A: U(A) = -$3 B1 And B2 Not A → U(~A) = -$1 Not A → U(~A) = $1 “A” → I lose $50 on B1, win $75 on B2 I bet $50 on B1, $25 on B2 “A” → I lose $25 on B2, win $50 on B1 I make a sure profit of $25 by betting against you How to Extract a Positive Payoff (for Sure) from Someone Whose Beliefs Do Not Satisfy Probability Axioms

  44. Multiple Incommensurable Ontologies Multiple Incommensurable Epistemologies and Logics of Argumentation Multiple Incommensurable Moral and Ethical Approaches Current (Algorithmic) Scope of Managerial Skill Development The Educational Opportunity in Post-Modern High Capitalism The Development Opportunity ‘Believing’ ‘Knowing’ ‘Wanting’ and ‘Doing’’ Successful Integration Across Hypothesis testing and inference to the Best Explanation Interactive (strategic) Decision Making Pattern Recognition Constrained Local Optimization

  45. Multi-paradigmatic Organization Science “Paradigm Wars” (1990’s) The Percolation and Diffusion of Legitimation Crises into Business Academia and Managerial Practice, 1990-2020 AD. The Hermeneutic Circle (Kuhn, 1962; Mannheim, 1935) Under Determination of Theory by Data (Duhem, 1913) Paradoxes of Confirmation (Hempel, 1941) Ontological Relativity (Quine, 1956) Autonomy of “Knowledge Power” & Emergence of Incommensurable Logics Legitimation crisis in the classroom (largely suppressed) (2000’s) (2010’s) “TRUST ME” “TELL ME” “SHOW ME”

  46. VALUE-LINKED CHARACTERISTIC INTEGRATIVE GAIN: PARETO GAIN FROM NEW FRONTIER ( , ) GAIN IN OPERATIONAL EFFICIENCY CONSTRAINED UTILITY MAXIMIZATION VALUE-LINKED CHARACTERISTIC The Integrative Function of Management (Adapted From Porter, HBR (1996))

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