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Types of Systems<\/strong><\/font><\/font><\/p>\n The very circumscribed and also very partial and incomplete take on the history of General Systems Theory I provided in my last post, leaves us in the following position with respect to the problem of classifying systems. There are three very important dichotomies which have emerged out of the history of General Systems Theory. These are: Deterministic vs. indeterministic; Predictability vs. Unpredictability; and Patterned vs. Patternless. Combining these dichotomies gives 8 logically possible types of systems:<\/font><\/font><\/p>\n <\/p>\n 1. Deterministic-Patterned-Predictable<\/strong><\/em><\/font><\/font><\/p>\n This category includes systems governed by deterministic laws, exhibiting understandable patterns, that are predictable in their details. It includes mechanical and teleological deterministic systems. Dave Snowden’s distinction between simple and complicated systems can also be applied here, though his own use of the distinction doesn’t suggest that his simple and complicated systems are deterministic-patterned-predictable, but rather only ordered and predictable. Also, his distinction between known and knowable systems is based on the idea that simple systems are \u201cknown,\u201d and complicated systems are \u201cknowable.\u201d While this may be a valid distinction, it is not a distinction about the systems themselves, but is a distinction based on our state of ignorance about deterministic, or causally ordered systems. Since the present classification is about ontology, and not about the state of our psychological beliefs about systems, or even about the epistemological classification of systems, I think the distinction between \u201cknown\u201d and \u201cknowable\u201d causally ordered systems is less important here.<\/font><\/font><\/font><\/p>\n <\/p>\n 2. Deterministic-Patterned-Unpredictable<\/strong><\/em><\/font><\/font><\/p>\n This combination of the dichotomies identifies no systems that have been discovered in nature or in human experience. It suggests that if a system is both deterministic and patterned, it will be predictable.<\/font><\/font><\/p>\n <\/p>\n 3. Deterministic-Patternless-Predictable<\/strong><\/em><\/font><\/font><\/p>\n This is another combination of the dichotomies that doesn’t exist, and suggests that if a deterministic system exhibits dynamics that have no pattern, it will be unpredictable.<\/font><\/font><\/p>\n <\/p>\n 4. Deterministic-Patternless-Unpredictable<\/strong><\/em><\/font><\/font><\/font><\/p>\n Chaotic Systems are deterministic, patternless and unpredictable in their details. In Dave Snowden’s discussion of Chaotic Systems in Cynefin, such systems are among those called \u201cunordered,\u201d and he also characterizes them as systems in which the agents are unconstrained by a higher level system. However, if agents are unconstrained by a higher level system, then there is no higher level system. So if we talk about chaotic systems at all, we must be talking about systems whose phase space dynamics are deterministic, patternless, and unpredictable in their details, since if this were not the case, the systems in question would be either chance systems, or complex systems at the component level of analysis.<\/font><\/font><\/p>\n <\/p>\n 5. \tIndeterministic-Patterned-Predictable<\/strong><\/em><\/font><\/font><\/p>\n Some Complex Adaptive Systems are indeterministic, patterned, and predictable. These are human intelligent agent-based PCAS systems whose patterns of behavior involve appreciable coercive control efforts by central authorities or by cohesive factions engaged in long-standing and inconclusive political conflicts with one another. The coercive control structures in such systems make human behavior more predictable than it is in NCASs, which lack such structures. But such predictability is not produced by deterministic relationships, but by humans <\/span><\/font>choosing<\/strong><\/em><\/font> not to resist coercive authority. And the cost of implementing such structures is severe restriction in problem solving capability and the variety of new ideas generated to meet challenges from the system’s environment. Indeed the system is more predictable because its reactions to the environment are less creative than would be the case if its agents were engaged in more autonomous problem-solving efforts.<\/span><\/font><\/font><\/font><\/font><\/p>\n <\/p>\n At the level of human organizations, we can identify three types of PCASs: the Closed Organization, the Mobilized Organization, and the Frozen Organization.<\/font><\/font><\/p>\n <\/p>\n The Closed Organization is a PCAS in which authority to recognize, formulate, solve problems, and disseminate solutions is restricted by high level management to a small elite, while the mass of employees contributes only to operational business processing. Examples include American Automobile Manufacturers of the 1950s and 1960s.<\/font><\/font><\/p>\n <\/p>\n The Mobilized Organization is one in which many employees are enlisted in problem solving and solution dissemination, but, also, in which problem solving efforts and dissemination are closely managed and directed by a small elite so that only certain methods and processes of problem solving implemented. An example of such an organization is General Electric with its centrally directed imposition of Six Sigma-based approaches to problem solving.<\/font><\/font><\/p>\n <\/p>\n The Frozen Organization is one in which hierarchical stove-piped structures have formed to deal with both operational business processing and problem solving. Within the stove pipes, the pattern is one of the closed or mobilized organization, but communication across stove pipes is prevented by organizational structures, or culture with the result that organizational problems that are broader in scope than the stove pipes cannot be solved.<\/font><\/font><\/p>\n <\/p>\n 6. Indeterministic-Patterned-Unpredictable<\/strong><\/em><\/font><\/font><\/p>\n This is the category of Natural Complex Adaptive Systems and of PCASs whose behavior is relatively unpredictable. Indeterminism exists because laws that govern the evolution of complex systems can’t be formulated. Nevertheless, these systems do exhibit a pattern of change over time. Their dynamics can be understood in retrospect, while these same dynamics are relatively unpredictable, because both environmental challenges and the complex system’s reaction to them are relatively unpredictable.<\/font><\/font><\/p>\n <\/p>\n Among PCASs, there are two system types: The Open Organization, and the Violently Conflictful system. Open organizations are characterized by widely distributed authority to seek, recognize and formulate problems, arrive at new solutions and disseminate those solutions to others. Structural barriers to self-organization are at a minimum and enabling structures for self-organization are at a maximum. Also, internal transparency in knowledge processing and trust in related interactions is high. Indeterminism exists because laws governing creativity in problem solving can’t be developed, and also because choice has a big role to play in self-organization. Complex system interaction can’t be predicted in detail, because of the role of human choice and creativity in the system. On the other hand, the system pattern can be understood in retrospect, even though detailed prediction is impossible.<\/font><\/font><\/p>\n <\/p>\n Violently Conflictful Systems are not found at the organizational level, due to policing, but they can be found at other levels of society, say in residential, neighborhood or regional settings, where there is hostility and escalating conflict between or among social groups. In these settings, individuals self-organize to support contending groups, which can have coercive communitarian structures. Violent patterns of interaction, are neither determined nor random, but complex. They can’t be predicted, because violent outbreaks involve individual choices magnified by self-organizing patterns that sometimes reflect the kinds of chaotic escalations one sees in arms races. On the other hand, patterns of interaction can be understood after the fact.<\/font><\/font><\/p>\n <\/p>\n 7. Indeterministic-Patternless-Predictable<\/strong><\/em><\/font><\/font><\/p>\n Systems of this type do not exist, and their absence suggests that systems cannot be both indeterministic and patternless and still be relatively predictable.<\/font><\/font><\/p>\n <\/p>\n 8. Indeterministic-Patternless-Unpredictable<\/strong><\/em><\/font><\/font><\/p>\n This is the realm of Chance Systems — <\/font><\/font>systems in which elementary and irreducible chance events occur. Chance Systems exist at a very small scale according to Quantum Theory, and humans can engage in games, using tools whose behavior can, more or less, approximate results that we would expect from true chance systems. However, human social behavior outside of such contexts is non-random, even though it can sometimes be modeled as reflecting randomness.<\/font><\/font><\/p>\n <\/p>\n Summary and Conclusions<\/strong><\/font><\/font><\/p>\n Even though there are 8 logically possible combinations of the three dichotomies, only 5 of the categories exist in reality, and the remaining three are probably empirically impossible. The Classical deterministic systems of Category 1, whether mechanical or teleological are no surprise, and the systems of deterministic chaos falling into Category 4, as well as the Chance Systems of Category 8 are also well-known. However, the complex systems of Categories 5 and 6 are characterized differently than in other discussions of system types.<\/font><\/font><\/p>\n <\/p>\n In particular, the <\/font><\/font>indeterministic, patterned, and predictable combination of Category 5 includes human-based PCASs involving coercive controls. These systems are relatively predictable because the structures and operation of coercive control within them, reinforced by authoritarian culture, simulate the mechanical and teleological systems of Category 1. Thus, human behavior in closed, mobilized, or frozen organizations is relatively predictable compared to other types of NCASs and PCASs.<\/span><\/font><\/font><\/p>\n <\/p>\n On the other hand, the indeterministic, patterned, and unpredictable combination of Category 6 includes both commonly observable NCASs such as Ant Hills and Beehives, and two types of human-based PCASs whose behavior is relatively unpredictable, open organizations and violently conflictful organizations. Open organizations and NCASs are less predictable because agents within these systems are free to self-organize and to engage in distributed problem solving. Finally, violently conflictful PCASs are also unpredictable, because, in the case of such systems, violent outbreaks involve individual choices magnified by self-organizing patterns that sometimes reflect the kinds of chaotic escalations one sees in arms races. The truth is, that even if we don’t like them, violently conflictful systems also involve a great deal of creativity and distributed problem solving, as humans enmeshed in such systems know very well.<\/font><\/font><\/p>\n <\/p>\n The emptiness of the Categories 2, 3, and 7 suggest three Natural laws expressed in negative form. Specifically:<\/font><\/font><\/p>\n There\tare no deterministic, patterned, and unpredictable systems;<\/font><\/font><\/p>\n<\/li>\n There \tare no deterministic, patternless, and predictable systems; and<\/font><\/font><\/p>\n<\/li>\n There \tare no indeterministic, patternless, and predictable systems.<\/font><\/font><\/p>\n<\/li>\n<\/ul>\n These propositions, arising out of the categorization, can be refuted by finding one real system of each of the three types.<\/font><\/font><\/p>\n <\/p>\n Comparison with Snowden’s Types<\/strong><\/font><\/font><\/p>\n Dave Snowden’s three \u201cphysical\u201d types: order, chaos, and complexity appear to map to types 1, 4, and both 5 and 6 above, respectively. Type 8, Chance Systems, isn’t represented in his classification. Also, I said \u201cappears\u201d above, because what Dave means by \u201corder\u201d isn’t entirely clear from his writings. But I think that some of his examples, at least, suggest that he means \u201ccausally\u201d ordered systems characterized by causal laws, the sort of order we find in deterministic systems and in classical physics. However, other examples, involving things like the legal system also suggest that he may not be talking about order characterized by causal laws at all. From my point of view this aspect of Cynefin certainly needs clarification.<\/font><\/font><\/p>\n <\/p>\n It’s also not entirely clear that his \u201cchaos\u201d and my \u201cchaos\u201d match entirely. Dave has stated that his category includes deterministic chaos, but he’s also indicated in act-km correspondence that \u201cchaotic systems\u201d may include other kinds of systems as well. He has characterized \u201cchaotic systems\u201d as those in which agents are \u201cunconstrained.\u201d This doesn’t clarify things for me however, because when agents within a system are unconstrained by a higher level system, there is no such system. Of course there’s no problem with defining a \u201cno system\u201d type from a logical point of view, But if one does that, then the idea would not include \u201cdeterministic chaos,\u201d which certainly implies (as in the famous example of the \u201cbutterfly effect\u201d) causal interdependence of the components and agents in a system, and therefore constraints on the agents, whether we can see the patterning of these constraints or not.<\/font><\/font><\/p>\n <\/p>\n In the area of \u201ccomplexity,\u201d Dave recognizes that human complex systems are different from those found in nature; but he doesn’t make the NCAS\/PCAS distinction in detail. He also doesn’t recognize that there are more and less predictable CASs, so his classification doesn’t distinguish between Types 5 and 6 above.<\/font><\/font><\/p>\n <\/p>\n Within the human realm Dave’s order category is broken down according to what he calls an \u201cepistemological\u201d criterion: whether systems are \u201cknown\u201d or \u201cknowable.\u201d I don’t make that distinction myself because my classification is intended to be ontological, that is, it’s intended to be about the systems. It’s not intended to be about what we know, or to be about \u201cus.\u201d That’s another subject.<\/font><\/font><\/p>\n <\/p>\n I feel the same way about Dave’s fifth type of system, \u201cdisorder.\u201d Dave says very little about this type of system and its real characteristics, and the impression I get is that he really means to characterize it almost from a social psychological point of view, as referring to systems that we have no consensus about relative to whether we are dealing with a \u201cknown,\u201d \u201cknowable,\u201d \u201cchaotic,\u201d or \u201ccomplex\u201d system. He’d probably respond that this is a ‘sensemaking\u201d point of view, rather than a social psychological point of view. If so, I wouldn’t argue over terms, since in neither case are disorderly systems ontological in character.<\/font><\/font><\/p>\n <\/p>\n In future blogs, I’ll take up other Cynefin topics, including an analysis of Cynefin viewed not as a framework for classifying systems, but as a sensemaking framework for analyzing and deciding about what to do in specific situations or contexts; and also an analysis of Dave’s view of safe-fail experiments.<\/font><\/font><\/p>\n","protected":false},"excerpt":{"rendered":" Types of Systems The very circumscribed and also very partial and incomplete take on the history of General Systems Theory I provided in my last post, leaves us in the following position with respect to the problem of classifying systems. There are three very important dichotomies which have emerged out of the history of General […]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[14,16,8],"tags":[96,109,89,100,3535,73,65,94,93,90,102,106,101,18,92,98,19,104,88,105,103,97,95,91,107,108],"class_list":["post-20","post","type-post","status-publish","format-standard","hentry","category-complexity","category-epistemologyontology","category-knowledge-management","tag-autopoiesis","tag-chance-systems","tag-chaos","tag-chaotic-systems","tag-complexity","tag-cynefin","tag-dave-snowden","tag-deterministic-chaos","tag-deterministic-systems","tag-disorder","tag-downward-causation","tag-edge-of-chaos","tag-emergence","tag-epistemologyontologyvalue-theory","tag-general-systems-theory","tag-indeterministic","tag-karl-popper","tag-ncas","tag-order","tag-pcas","tag-plastic-controls","tag-self-making","tag-self-organization","tag-systems-classification","tag-the-open-organization","tag-violently-conflictful-systems"],"_links":{"self":[{"href":"https:\/\/kmci.org\/alllifeisproblemsolving\/wp-json\/wp\/v2\/posts\/20","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/kmci.org\/alllifeisproblemsolving\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/kmci.org\/alllifeisproblemsolving\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/kmci.org\/alllifeisproblemsolving\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/kmci.org\/alllifeisproblemsolving\/wp-json\/wp\/v2\/comments?post=20"}],"version-history":[{"count":0,"href":"https:\/\/kmci.org\/alllifeisproblemsolving\/wp-json\/wp\/v2\/posts\/20\/revisions"}],"wp:attachment":[{"href":"https:\/\/kmci.org\/alllifeisproblemsolving\/wp-json\/wp\/v2\/media?parent=20"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/kmci.org\/alllifeisproblemsolving\/wp-json\/wp\/v2\/categories?post=20"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/kmci.org\/alllifeisproblemsolving\/wp-json\/wp\/v2\/tags?post=20"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}\n