About complexity and knowledge How order leads to chaos !

About complexity and knowledgeHow order leads to chaos !

Prof dr Walter BaetsEuromed Marseille, Ecole de Management

The Nyenrode Institute for Knowledge Management and Virtual Education

Flatland: Edwin Abbott, 1884

A. Square meets the third dimension

Wanderer, your footprints arethe path, and nothing more;Wanderer, there is no path,it is created as you walk.By walking,you make the path before you,and when you look behindyou see the path which after youwill not be trod again.Wanderer, there is no path,but the ripples on the waters

Antonio Machado,Chant XXIX Proverbios y cantares,Campos de Castilla, 1917

A very great musician came and stayed in our house,He made one big mistake …He was determined to teach me musicand consequently, no learning took place.Nevertheless, I did casually pick up from hima certain amount of stolen knowledge

Rabindranath Tagore

Sometimes small differences in the initialconditions generate very large differencesin the final phenomena. A slight error in the former could produce a tremendous error in the latter.Prediction becomes impossible; we haveaccidental phenomena.

Poincaré in 1903

Taylor’s view on the brain

The computer: attempt to automate human thinking

Manipulating symbols Modeling the brain

Represent the world Simulate interaction of neurons

Intelligence = problem solving Intelligence = learning

0-1 Logic and mathematics Approximations, statistics

Rationalist, reductionist Idealized, holistic

Became the way of building computersBecame the way of looking at minds

I

WE

IT

ITS

Interior-IndividualIntentional

Interior-collectiveCultural

Exterior-IndividualBehavioral

Exterior-CollectiveSocial

World of: sensation, impulses, emotion, concepts, vision

World of: magic, mythic, values

World of: atoms, molecules, neuronal organisms, neocortex

World of: societies, division of labour, groups, families, tribes, nation/state,agrarian, industrial and informational

Truthfulness

Justness Functional fit

Truth

Ken Wilber: A Brief History of Everything

Complexity Theory

Sensitivity to initial conditions (Lorenz)

Xn+1 = a * Xn * (1 - Xn)

0.294 1.4 0.3 0.7

Cobweb Diagrams (Attractors/Period Doubling)

Xn+1 = * Xn * (1 - Xn) (stepfunction)

dX / dt = X (1 - X) (continuous function)

On the diagrams one gets:• Parabolic curve• Diagonal line Xn+1 = Xn

• Line connecting iterations

Lorenz curve (Butterfly effect)

Lorenz (1964) was finally able to materialize Poincaré’s claim

Lorenz weather forecasting model

dX / dt = B ( Y - X )

dY / dt = - XZ + rX - Y

dZ / dt = XY - bZ

Ilya Prigogine

• Non-linear dynamic models (initial state, period doubling,….)

• Irriversibility of time principle

• Behaviour far away from equilibrium (entropy)

• A complex system = chaos + order

• Knowledge is built from the bottom up

Why can chaos not be avoided ?

• Social systems are always dynamic and non-linear

• Measurement can never be correct

• Management is always a discontinuous approximation of a continuous phenomenon

Francesco Varela

• Self-creation and self-organization of systems and structures (autopoièse)

• Organization as a neural network

• The embodied mind

• Enacted cognition

• Subject-object division is clearly artificial

• How do artificial networks operate (Holland)

Knowledge and learning

ENVIRONMENT

Single-loop learning

ENVIRONMENT

Single-loop learning

Environmentalresponse

Individual action

INDIVIDUAL MENTAL MODEL &

FRAMEWORKS

INDIVIDUAL MENTAL MODEL &

FRAMEWORKS

ORGANIZATIONALROUTINES &

SHARED MENTALMODELS

ORGANIZATIONALROUTINES &

SHARED MENTALMODELS

Individual double-loop learning

Organizational double-loop learning

Organizational action

OADI-cycle/Individual learning

ASSESS

DESIGN

IMPLEMENT

OBSERVE

The Hybrid Business School

EXPERIENCES

INDIVIDUAL MENTALMODEL &

TACIT KNOWLEDGE

SHARING AND COMMUNICATION

SHARED MENTAL MODEL &

KNOWLEDGEREPOSITORY

ContextualInter-Action

Contextualization

CONTEXTUAL KNOWLEDGE

Real life Databases Procedures Simulators Executive seminars Concepts Theory

Inter-Action

IT for the Hybrid Business School

CASE BASEDREASONING

SYSTEM

Structuring

Advising

ARTIFICIAL NEURALNETWORKS &OTHER A.I.

TECHNIQUES

Sharing and Communicating the

Emergent

COMMUNICATIONPLATFORM /

NEURAL NETWORKS

Consultatio

n

Rules

Learning MaterialExpertise

DATA BASES LEARNING

ENVIRONMENT SIMULATORS EXPERT

SYSTEMS COMPUTER

BASED TEACHING

VIDEO-CONFERENCING

IT for the Corporate Knowledge Approach

INDIVIDUAL MENTAL MODEL

INDIVIDUAL MENTAL MODEL

SHARED MENTALMODELS

SHARED MENTALMODELS

Innovation as learning

Internal External

Individual

Collective

EXPERIENCES

CONTEXTUAL KNOWLEDGE

Individuals with characteristics (agents)

Interaction

Emotions Facts

Emotions

Emotions

Your knowledge infrastructure

Learning platform

Provide an ICTinfrastructurethat allows full

access and sharing facilities

Content

What knowledgeto share:•explicit•implicit•learned

Ownership (search/learn principles)Remains with those that use it

Those that want to learn decide what to learnJust-in-time, just-enough

Culture

Turn XYZinto a learning

culture (viaprojects)

Rewarding

Your knowledge infrastructureYour knowledge infrastructure

Learning platform and search/learn principles

The knowledge net

Explicit knowledge (database)

Searc

h e

ngin

e

Implicit knowledge (case base)Case based reasoning systemCases stored in an adapted wayA methodology for case analysis and storageCorporate knowledge repository Notion

Learned knowledge (case base)Explicit knowledge that is enhanced via experienceUsing the same methodology for implicit knowledgeInterviews with key knowledge owners

Open learning platformCollaborative tools

Dedicated search enginesAccessibility for all

Open to connect ‘any’application

Solution for e-learning

The userwith its learning

agenda

INTERNETINTRANET

PCCD ROM

BOOKS

WWW site + other knowledge applications

A TYPICAL MANAGEMENT DIPLOMA COURSE 3O % SELF-STUDY (learning-by-doing) 2O % WORKSHOPS 50 % PROJECT WORK

SKIL

LS/

ACTIV

ITIE

S

CASES

CONCEPTS

LEARNING/DATABASE SOFTWARE

EXECUTIVECOURSES

HYPERTEXTDATABASE

For a 18-24 months period

Workshops: 200 study hours Innovative projects: 700 study hoursVirtual grouplearning: 600 study hours

Some interesting technologies

Artificial Neural NetworksGenetic AlgorithmsGenetic ProgrammingFuzzy LogicArtificial life/Agent simulationsNegotiating AgentsSemantic Search EnginesCase Based ReasoningLanguage technologiesMachine learning technologiesConversational technologies

The Hybrid Business School

Building Blocks

Ownershiplearn/search

Learning Agenda(Pers. Development)

cult

ure

plat

form

IC

T

cont

ent

Explicit knowledge

Implicit knowledge

Sear

ch

engi

ne

learner+

learningagenda

Knowledge platform

case

sSki

llsActi

vitie

s

Concepts

Pra

ctic

es

Hyp

er

linke

d

Hyp

er

linke

d

Methodology Actions Outcomes(company-specific)

Brainstorm

4 Brainstorms

Project team• Notion• MD/HRM• Line mgt• IT• Marketing/R&D

IT/Application plan

White Paper(Board approval)E-learning view

4 Action plans(Board approval)

Infrastructure(Plan)

Architecture

Some statements

Knowledge products can easily be copied (pharma example);Information even faster

Is legal protection possible in the knowledge economy? (patents) Protection on HIV drugs: ethics against law (South Africa)Mobile phones: money is not made on the hardware, but

on the servicesWhat is a company’s value added: is it learning or repetition

(can it be machine replaced ?)Information against faster learning based innovation

I

WE

IT

ITS

Interior-IndividualIntentional

Interior-collectiveCultural

Exterior-IndividualBehavioral

Exterior-CollectiveSocial

World of: sensation, impulses, emotion, concepts, vision

World of: magic, mythic, values

World of: atoms, molecules, neuronal organisms, neocortex

World of: societies, division of labour, groups, families, tribes, nation/state,agrarian, industrial and informational

Truthfulness

Justness Functional fit

Truth

Ken Wilber: A Brief History of Everything