Presentation on theme: "EVOLUTIONARY BIOLOGY OF SPECIES AND ORGANIZATIONS 1 OASIS SEMINAR – 27 JULY 2007 Time Value of Knowledge — time-based."— Presentation transcript:
EVOLUTIONARY BIOLOGY OF SPECIES AND ORGANIZATIONS 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 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 2 TS m P n P n+1 EE TS 1 2 TS m P n P n+1 EE TS 1 2 TS m PP n+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 ( ) –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 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 BoydJohn Boyd's OODA Loop processOODA 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 t2t2 t3t3 t4t4 t 1+i journey thus far the world perceivable world t1t1 chart × proximal future intended future × × × perceived present divergent futures cognitiv e edge t 1+j t gs From the paper
immutable past the world t1t1 t 1 – time of observation t2t2 t 2 – orientation & sensemaking t 4 – effect action temporal convergence calendar time “now” as it inexorably progresses through time intended future × × × divergen t divergent futures × stochastic future convergent future temporal divergence OODA t4t4 t 3 – planning & decision t3t3 Anticipating and controlling the future from now
immutable past the world t1t1 t2t2 temporal convergence calendar time intended future × × × divergent futures × stochastic future convergent future temporal divergence OODA t4t4 t3t3 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 t 1 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 t 2 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 t 1 (i.e., observations) the entity can project forward to construct a concept of the present situation (i.e., at t 3 ), or some future situation. Recent past is constructed in W2 based on what existed in W1 leading up to t 1. 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 t 3 ; actual present: the entity's instantaneous situation in W1 at time t 4. perceive d present Proximal future: the entity's anticipated future situation in the world (W2) at t 4 as a consequence of its actions at t 1+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 t 4. OODA t 1+j proximal future Intended future: the entity's intended goal or situation in the world farther in the future (at t gs, where gs is a goal- state and t gs 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). t gs convergent future: the entity’s mapping of the proximal future against an intended future in which t gs can be specified. t 1 and t 1+j can also be mapped to t gs and then t gs+1 forecasted in the form of some subsequent goal. divergent future: a world state where the entity’s actions in the proximal future (t 1+j ) failed to achieve the world state of the intended future at t gs.
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)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)