Emergence and Growth of Knowledge and Diversity in Hierarchically Complex Living Systems

An environment conducting a flux of energy and materials between temporally or spatially separated sources and sinks may become more complexly structured due to the emergence of cyclical, dissipative transport systems. Selection favors transport systems able to stabilize themselves against environmental perturbations through feedback. Continuing selection for self-stabilization over long periods of time may eventuate in the emergence of an autopoietic assembly of subsystems (i.e., an autocatalytic set). The stabilizing ‘control information’ inherent in the instantaneous structure of the autopoietic system represents a form of knowledge that enables the stabilized system to continue an existence as a living and evolving entity. Such self-referential knowledge (defined by Karl Popper as “solutions to problems of life”) is integral to the differential survival of nascent autopoietic systems. Maturana and Varela developed the concept of autopoiesis for the autopoietic cybernetics of self-maintenance and self-production. They also equated the cybernetics of autopoiesis with cognition. Concepts of “meaning”, “memory”, “learning” and “heredity” can also be derived from this framework of Popperian autopoiesis. Hall has argued that autopoiesis has emerged at cellular, (multicellular) organismic, and economic organizational levels. Given an acceptance that different orders of autopoiesis exist, it follows that forms of regulatory knowledge (i.e., solutions to problems of life) exist at each organizational level where autopoiesis occurs. Knowledge may be “tacit”, “implicit” or “explicit”.


Posted in Autopoiesis, Complex systems, Emergence, Knowledge | Tagged , , ,

Time-Based Frameworks for Valuing Knowledge: Maintaining Strategic Knowledge

To survive and flourish in a changing and unpredictable world, organizations and people must maintain strategic power over necessary resources – often in the face of competition. Knowledge contributes to that strategic power. Without vigilance to maintain its currency and accuracy, the value of knowledge depreciates as circumstances change over time. Karl Popper’s evolutionary epistemology and Maturana and Varela’s concept of autopoiesis provide a paradigmatic framework for considering the roles and importance of time in constructing knowledge and using it to maintain strategic power. Following Popper, knowledge is constructed, used and evaluated via cyclically-iterated processes. We introduce nine time-based frames of reference based on this Popperian autopoietic paradigm to explore the relationships between time and a utility-based valuation of knowledge as it is constructed and applied. We believe this framework and associated paradigmatically consistent vocabulary provide useful tools for analyzing organizational knowledge management needs.


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Requisite Variety, Autopoiesis, and Self-organization

Ashby’s law of requisite variety states that a controller must have at least as much variety (complexity) as the controlled. Maturana and Varela proposed autopoiesis (self-production) to define living systems. Living systems also require to fulfill the law of requisite variety. A measure of autopoiesis has been proposed as the ratio between the complexity of a system and the complexity of its environment. Self-organization can be used as a concept to guide the design of systems towards higher values of autopoiesis, with the potential of making technology more “living”, i.e. adaptive and robust.


Posted in Autopoiesis, Complexity, Requisite variety, Self-organization | Tagged , , ,

Autopoiesis in Creativity and Art

The term autopoiesis, (meaning ‘self’) and ‘poiesis’ (meaning ‘creation, production’) defines a system capable of reproducing and maintaining itself. The term was introduced by the theoretical biologists, Humberto Maturana and Francisco Varela, in 1972 to define the self-maintaining chemistry of living cells. The term has subsequently also been applied to the fields of systems theory and sociology. In this paper we apply this model to characterize creativity in art practice.


Read also: Autopoiesis and Creativity

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Innovation, from cells to societies

Innovation is the breaking of an adaptive pattern through the emergence of phenotypic novelty, sometimes corresponding to a new ecological function. Phenotypes in biology include anatomical, physiological and behavioral traits, such as bird wings permitting flight. Innovations are also obviously a part of cultural and technological evolution and include behavioral norms, institutions, and tools. Importantly, there are considerable analogies between innovations in biology, culture, and technology, suggesting that the same driving processes come into play.

I mentioned the example of bird wings permitting flight. Wings are the phenotype – flight is the function. Both emerged as novelties in certain dinosaur lineages, but wings serve many other functions in modern-day bird species such as paddling in water birds, courting displays, and thermoregulation. And of course, the function of flight has been lost or reduced in some bird species. Winged flight has also emerged in other animal lineages, such as the insects, and some of the same generic structures of bird wings are found in gliding mammals and reptiles. Anatomical structures permitting the use of air for displacement has therefore emerged independently many times. So innovation may derive from a single chain of events (such as photosynthesis), or be a more inevitable occurrence arising in multiple independent lineages (gliding and active flight).


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The Passion for Learning and Knowing

Abstraction’ as micro-learning-process is rarely used to analyze practices of organizational learning. In this paper, we portray abstraction as a basic learning process that prevails even in contexts characterized by high degrees of uncertainty and heterogeneity, that is, in high reliability organizations. We discuss several flavors of abstraction and use them as heuristic devices to analyze how organizational agents apply abstractions to cope with new and unexpected situations. For this purpose, we present an empirical case dealing with work experiences of novice nurse anesthetists. Based on this case, we argue that the way abstraction is built and applied has a major influence on whether novel situations can be handled ‘mindfully’


Posted in Knowing, Learning | Tagged ,

How social cognition can inform social decision making

Social decision-making is often complex, requiring the decision-maker to make inferences of others’ mental states in addition to engaging traditional decision-making processes like valuation and reward processing. A growing body of research in neuroeconomics has examined decision-making involving social and non-social stimuli to explore activity in brain regions such as the striatum and prefrontal cortex, largely ignoring the power of the social context. Perhaps more complex processes may influence decision-making in social vs. non-social contexts. Years of social psychology and social neuroscience research have documented a multitude of processes (e.g., mental state inferences, impression formation, spontaneous trait inferences) that occur upon viewing another person. These processes rely on a network of brain regions including medial prefrontal cortex (MPFC), superior temporal sulcus (STS), temporal parietal junction, and precuneus among others. Undoubtedly, these social cognition processes affect social decision-making since mental state inferences occur spontaneously and automatically. Few studies have looked at how these social inference processes affect decision-making in a social context despite the capability of these inferences to serve as predictions that can guide future decision-making. Here we review and integrate the person perception and decision-making literatures to understand how social cognition can inform the study of social decision-making in a way that is consistent with both literatures. We identify gaps in both literatures-while behavioral economics largely ignores social processes that spontaneously occur upon viewing another person, social psychology has largely failed to talk about the implications of social cognition processes in an economic decision-making context-and examine the benefits of integrating social psychological theory with behavioral economic theory.


Posted in Social cognition, Social decision | Tagged ,

Finding and evaluating community structure in networks

We propose and study a set of algorithms for discovering community structure in networks-natural divisions of network nodes into densely connected subgroups. Our algorithms all share two definitive features: first, they involve iterative removal of edges from the network to split it into communities, the edges removed being identified using any one of a number of possible “betweenness” measures, and second, these measures are, crucially, recalculated after each removal. We also propose a measure for the strength of the community structure found by our algorithms, which gives us an objective metric for choosing the number of communities into which a network should be divided. We demonstrate that our algorithms are highly effective at discovering community structure in both computer-generated and real-world network data, and show how they can be used to shed light on the sometimes dauntingly complex structure of networked systems.


Read also: Defining and Identifying Communities in Networks

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How social networks make us smarter

By harnessing the power of our collective intelligence, can humans as a species work together to implement thoughtful solutions in an age of connectivity? In a world riddled with big problems, leading social scientist Alex ‘Sandy’ Pentland has heartening news. His research is discovering the power and pitfalls of social sharing on our decision-making. Pentland’s field, “Social Physics” is a new way of understanding human behavior based on analysis of Big Data. By leveraging huge amounts of available consumer information and tracking idea flow, research can now make better predictions about human behavior and learn how to make minor shifts to generate massive change.

Alex `Sandy’ Pentland directs MIT’s Human Dynamics Laboratory and the MIT Media Lab Entrepreneurship Program, co-leads the World Economic Forum Big Data and Personal Data initiatives, and is a founding member of the Advisory Boards for Nissan, Motorola Mobility, Telefonica, and a variety of start-up firms. In 2012 Forbes named Sandy one of the ‘seven most powerful data scientists in the world’.


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Introducing Social Media Intelligence

We introduce the latest member of the intelligence family. Joining IMINT, HUMINT, SIGINT and others is ‘SOCMINT’ – social media intelligence. In an age of ubiquitous social media it is the responsibility of the security community to admit SOCMINT into the national intelligence framework, but only when two important tests are passed. First, that it rests on solid methodological bedrock of collection, evidence, verification, understanding and application. Second, that the moral hazard it entails can be legitimately managed. This article offers a framework for how this can be done.


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