EVOLUTIONARY BIOLOGY OF SPECIES AND ORGANIZATIONS
http://www.orgs-evolution-knowledge.net
1
OASIS SEMINAR – 27 JULY 2007
Time Value of Knowledge
—time-based
frameworks for Valuing knowledgeWilliam P. Hall, PhD
Australian Centre for Science, Innovation and Society
University of [email protected]
Peter Dalmaris, PhDFutureshock Research, Sydney
Steven Else, PhDCenter for Public-Private Enterprise,
Alexandria, VA
Christopher Martin, PhDand
Wayne Philp, PhDLand Operations Division, DSTO, Edinburgh,
SA
Slide 2
Some questions
What is knowledge?What is an organisation?How is knowledge important to
organisations?How can knowledge-intensive organisations
value knowledge and knowledge-related activities?
How does this value change and depreciate with time?
We need a vocabulary for considering how cognition, knowledge and time interact!
Slide 3
Introduction
My own background– evolutionary biology, epistemology, computers,
defence industry content and knowledge management
– emergence of knowledge in complex adaptive systems
Background to this project– a day of brainstorming at DSTO Land Ops Division
• biologically based paradigm of organization– Karl Popper’s epistemology– Maturana and Varela’s autopoiesis
• need to gain & maintain strategic power in competition• bounded rationality and limits to organisation• improving knowledge intensive organisational processes
Slide 4
Paradigms and today’s presentations
Thomas Kuhn’s (1962, 1982) concepts– scientific paradigms held by communities– paradigmatic incommensurability
this presentation a product of an emerging community developing a biological theory of organizational knowledge– KM consultants/practitioners working in industry– most with PhD’s – academically unaffiliated (but looking for a home)
planning a workshop, “Theory, Ontology and Management of Organizational Knowledge”, to bring players together
the group framework combines several paradigms from the fringes of theories of knowledge and organisation
Slide 5
Epistemology paradigm
Karl Popper’s (1972) evolutionary epistemology– Knowledge is solutions or claims to solutions for
problems of life– All claims to know are fallible (knowledge is
constructed, its truth cannot be proven)– Three ontological worlds
• W1 – uninterpreted physics and dynamics of reality• W2 - cybernetics of life or the dynamics of subjective
experience; “dispositional” and “subjective” knowledge• W3 – objectively codified products of knowledge (e.g. the
logical contents of DNA molecules, books and libraries, computer memories), the “built” environment
– Knowledge grows through trial & error elimination
Pn → TT/TS → EE → Pn+1
Slide 6
Popper's “general theory of evolution”
Knowledge building cycles
Pn a problem faced by an entity
TS a tentative solution/theory.Tentative solutions are varied
EE a process of error elimination (e.g., selection, criticism)
Pn+1 changed problem faced by an entity incorporating a surviving solution
The whole process is endlessly iterated
TS1
TS2
•••••
TSm
Pn Pn+1EE
TS1
TS2
•••••
TSm
Pn Pn+1EE
TS1
TS2
•••••
TSm
P Pn+1EE
Knowledge is constructed by living systems TSs may be tacitly embodied in in the structural dispositions of the individual
entity, or TSs may be explicitly expressed in words as a hypothesis subject to
intersubjective criticism Objective expression and criticism lets our theories die in our stead Through cyclic iteration, tested solutions can approach reality
iteration
Slide 7
Organisational paradigm
Maturana and Varela (1980) Autopoiesis (cognition) is the definition of life
Criteria after Varela et al. (1974)– Bounded (demarcated from the environment)– Complex (identifiable components within boundary)– Mechanistic (driven by cybernetically regulated
dissipative processes)– Self-referential (boundaries internally determined)– Self-produced (intrinsically produces own
components)– Autonomous (self-produced components are
necessary and sufficient to produce the system).Organisations are complex living systems
(Hall 2005)
Slide 8
Bounded rationality & limits to organisation
Need for knowledge-based decisions & actionsLimited time & resources to process
information in a relentlessly changing worldBounds to individual rationality (Simon
1955, 1957)– Time– Cognitive processing power
Organisational limitations – Arrow (1974)– Greiner (1972-1998)– Else (2004)
Slide 9
Competition and survival in harsh environments
Living systems (i.e., orgs) are dissipative– grounded in non-equilibrium thermodynamics
Resources to feed dissipative processes are limited– degraded by use
Competition in a finite world– direct– competition for resources
To grow/survive living systems must maintain at least some strategic control over external environment & competitors– knowledge = solution to problems of life
Slide 10
Achieving strategic power in the world
Achieving strategic power depends critically on learning more, better and faster, and reducing decision cycle times compared to competitors. See http://www.belisarius.com.
AO
OBSERVE
(Results of Test)
OBSERVATION
PARADIGMEXTERNAL
INFORMATION
CHANGING CIRCUMSTANCE
S
UNFOLDING ENVIRONMENTAL
RESULTS OF ACTIONS
ORIENT
D
DECIDE
(Hypothesis)
O
CULTURE PARADIGM
S PROCESSES
DNA GENETIC
HERITAGE
MEMORY OF HISTORY
INPUTANALYSIS SYNTHESI
S
ACT
(Test)
GUIDANCE AND CONTROL
PARADIGM
UNFOLDING INTERACTION
WITH EXTERNAL
ENVIRONMENTJohn Boyd's OODA Loop process
Slide 11
Info transformations in the autopoietic entity
World 1
Autopoietic systemCell
Multicellular organismSocial organisation
State
Perturbations
Observations(data)
Classification
Meaning
An "attractor basin"
Related information
Memory of historySemantic processing to form knowledge
Predict, proposeIntelligence
World 2
Slide 12
Processing Paradigm(may include W3)
Another view
Decision
Medium/Environment Autopoietic system
World State 1
Perturbation Transduction
Observation MemoryClassification
Evaluation
Synthesis
AssembleResponse
Internal changes
Effect action
Effect
Time
World State 2
IterateObserved internal changes
World 1 World 2
Codified knowledge
World 3
immutable past convergent futureOODA
stochasticfuture
OODA
calendar time
temporal divergence
temporal convergence
“now” as itinexorablyprogresses
through time
t2
t3 t4
t1+i
journey thus far
the world
perceivableworld
t1chart
×proximal
future intendedfuture
××
×
perceived present
divergent futures
divergent futures
divergent futures
cognitive edge
t1+j
tgs
From the paper
immutable past
the world
t1
t1 – time of observation
t2
t2 – orientation & sensemakingt4 – effect action
temporal convergence
calendar time
“now” as itinexorablyprogresses through
time
intendedfuture
××
×
divergent
divergent
divergent futures
×stochastic
future
convergent futuretemporal d
ivergence
OODA
t4
t3 – planning & decision
t3
Anticipating and controllingthe future from now
immutable past
the world
t1
t2
temporal convergence
calendar time
intendedfuture
××
×
divergent futures
divergent futures
divergent futures
×stochastic
future
convergent futuretemporal d
ivergence
OODA
t4
t3
Perceivable world
Cognitive edge
journey thus far
chart: received and constructed world view that remains extant and authoritative for a single OODA cycle.
perceivable world: the world that the entity can observe at t1 in relationship to the chart. This is the external reality (W1) the entity can observe and understand in W2 (i.e., within its "cognitive edge"
journey thus far: the memory of history at t2 as constructed in W2. Memories tend to focus on prospective and retrospective associations with events (event-relative time) and can also be chronological in nature (calendar time)
chart
“now” as itinexorablyprogresses through
time
recent past: recent sensory data in calendar time concerning the perceivable world at t1 (i.e., observations) the entity can project forward to construct a concept of the present situation (i.e., at t3), or some future situation. Recent past is constructed in W2 based on what existed in W1 leading up to t1.
recentpast
Present: calendar time: when an action is executed.• perceived present: the entity's constructed understanding in W2 of its situation in the world at time t3;• actual present: the entity's instantaneous situation in W1 at time t4.
perceived
present
Proximal future: the entity's anticipated future situation in the world (W2) at t4 as a consequence of its actions at t1+j, where j is a time-step unit—typically on completing the next OODA cycle. This anticipation is based on observed recent past, perceived present and forecasting of the future up to t4.
OODA
t1+j
proximalfuture
Intended future: the entity's intended goal or situation in the world farther in the future (at tgs, where gs is a goal-state and tgs is the moment when that goal is realised). Intentions are not necessarily time specific but are always associated with an event or goal-state (i.e., the arrival of a set point in calendar time can also be considered to be an event).
tgs
• convergent future: the entity’s mapping of the proximal future against an intended future in which tgs can be specified. t1 and t1+j can also be mapped to tgs and then tgs+1 forecasted in the form of some subsequent goal.• divergent future: a world state where the entity’s actions in the proximal future (t1+j) failed to achieve the world state of the intended future at tgs.
Slide 16
Utility value of knowledge
Pattee (1995)– “Knowledge is potentially useful information about
something. ... By useful information or knowledge I mean information in the evolutionary sense of information for construction and control, measured or selected information, or information ultimately necessary for survival”
Utility value of knowledge (Cornejo 2003)– Direct
• direct relationship with improvements in processes and operations, usually derived from the knowledge acquired by members of the organization.
– Indirect• When the organization knows that it is benefiting from the
acquired knowledge but can’t identify the mechanism with clarity, and it therefore can’t find a reliable way to measure and value it.
Slide 17
Value and time
Knowledge value function – claim’s accuracy reflecting the true state of
existence (i.e., the degree that rational actions based on the knowledge produce predictable results)
– claim’s applicability to particular circumstances– quality and effects observed when knowledge
enacted
Time issues– relentless advance– temporal lag of constructed W2 vs actual W1– old and multiply tested knowledge vs depreciation – tacit (uncriticisable) vs explicit issues
Slide 18
OODA cycle times and strategic power
Concerns in the decision & action cycle– rationality bounded in time– decision risk– intimidation and dithering about uncertainties– Danger of stuck OODA (“analysis paralysis”)
• decisions by “running out of time” or “fiat”• paralysis blocks dependent decisions
– Knowledge that is not refreshed depreciatesMinimax
– increased observation time gives more detail for a larger perceivable world and a more accurate model of it
– striving too long to reduce uncertainty gives more time for random events and other actors to create a stochastic future diverging from the intentional future, leading to less relevant world views and less effective control information
Advantage from changing world before competitors complete their own OODA loops
Slide 19
Conclusions
Delaying decision & action without new observation and orientation depretiates the knowledge on which they depend– increasing unpredictability of results of actions– Operating inside a competitor’s (OODA) loop breaks its external
bonds with its environment and creates mismatches between the real world and its perceptions of that world.
– Initial confusion and disorder can degenerate into internal dissolution that erodes the will to resist.
Current world-knowledge doesn’t age well, but… – Some kinds of knowledge can become more valuable with time.– The most valuable knowledge may be “old” knowledge that has
survived testing in many OODA loops as cultural heritage. – Rapid decision also benefits from cultural paradigms that don't
have to be revisited often (Boyd)– At the tactical level, one needs to deal aggressively with
latency issues.
Slide 20
Any questions?
Slide 21
Cybernetics and emerging complexity
“Cybernetics" is the regulation, communication and application of control information, beginning at the biophysical level
“System” is a set of distinguishable components that dynamically interact to facilitate and cybernetically regulate the flow of information, matter or energy
“Complex system” a system whose emergent behavior cannot readily be predicted from the behaviors of its components (i.e., non-linear/chaotic)
“Levels of organisation”. Systems may be complex at hierarchically different levels of structure (Salthe 1983)
“focal level”. A selected level of analysis for observing a system in a hierarchically complex world. System may include sub-systems at lower focal levels as components and be a single component in a complex system at higher level of focus (Salthe 1983, Gould 2002)
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