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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 knowledge
William P. Hall, PhD
Australian Centre for Science, Innovation and Society
University of Melbourne
whall@unimelb.edu.au
Peter Dalmaris, PhD
Futureshock Research, Sydney
Steven Else, PhD
Center for Public-Private Enterprise, Alexandria, VA
Christopher Martin, PhD
and
Wayne Philp, PhD
Land 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
P
n
TT/TS EE P→ → →
n+1
Slide 6
Popper's “general theory of evolution”
Knowledge building cycles
P
n
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)
P
n+1
changed problem faced by an entity
incorporating a surviving solution
The whole process is endlessly iterated
TS 1
TS 2
•
•
•
•
•
TS m
PnPn +1
EE
TS 1
TS 2
•
•
•
•
•
TS m
PnPn +1
EE
TS 1
TS 2
•
•
•
•
•
TS m
P Pn +1
EE
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 & actions
Limited time & resources to process information in a relentlessly
changing world
Bounds 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.
A
O
OBSERVE
(Results of Test)
OBSERVATION
PARADIGM
EXTERNAL
INFORMATION
CHANGING
CIRCUMSTANCES
UNFOLDING
ENVIRONMENTAL
RESULTS OF ACTIONS
ORIENT
D
DECIDE
(Hypothesis)
O
CULTURE
PARADIGMS
PROCESSES
DNA
GENETIC
HERITAGE
MEMORY OF HISTORY
INPUT ANALYSIS
SYNTHESIS
ACT
(Test)
GUIDANCE AND CONTROL
PARADIGM
UNFOLDING
INTERACTION
WITH EXTERNAL
ENVIRONMENT
John Boyd's OODA Loop process
Slide 11
Info transformations in the autopoietic entity
World 1
Autopoietic system
Cell
Multicellular organism
Social organisation
State
Perturbations
Observations
(data)
Classification
Meaning
An "attractor basin"
Related
information
Memory of history
Semantic processing
to form knowledge
Predict, propose Intelligence
World 2
Slide 12
Processing Paradigm
(may include W3)
Another view
Decision
Medium/
Environment Autopoietic system
World State 1
Perturbation Transduction
Observation Memory
Classification
Evaluation
Synthesis
Assemble
Response
Internal changes
Effect action
Effect
Time
World State 2
Iterate Observed internal changes
World 1 World 2
Codified knowledge
World 3
immutable past convergent future
OODA
stochastic
future
OODA
calendar time
temporal divergence
temporal convergence
“now” as it
inexorably
progresses
through time
t2
t3t4
t1+i
journey thus far
the world
perceivable
world
t1
chart
×
proximal
future intended
future
×
×
×
perceived
present
divergent
futures
divergent
futures
divergent
futures
cognitiv
e edge
t1+j
tgs
From the paper
immutable past
the world
t1
t1 – time of observation
t2
t2 – orientation & sensemaking
t4 – effect action
temporal convergence
calendar time
“now” as it
inexorably
progresses
through time
intended
future
×
×
×
divergent
divergent
divergent
futures
×
stochastic
future
convergent future
temporal divergence
OODA
t4
t3 – planning & decision
t3
Anticipating and controlling
the future from now
immutable past
the world
t1
t2
temporal convergence
calendar time
intended
future
×
×
×
divergent
futures
divergent
futures
divergent
futures
×
stochastic
future
convergent future
temporal divergence
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 it
inexorably
progresses
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.
recent
past
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
proximal
future
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 depreciates
Minimax
–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)