Topic:Boundaries of systems
This topic forms part of the systems and complexity area of study. People who are competent in the topic can apply their knowledge to understanding how to effectively identify existing system boundaries, distinguish between autopoietic and allopoietic systems, and prerequisites to be met for meaningful establishment of new systems of any type.
Expected competencies after study of this topic are:
- being able to define and identify autopoietic versus allopoietic systems
- being able to describe a hierarchical ordering of systems
- being able to describe how system boundaries can be variously described as artificial, hierarchical, and interpenetrating
- distinguishing between and describing a system's function, products, and goal/purpose
Autopoietic systems are self-producing systems that maintain their own identity and boundaries through the production of their own components. Examples of autopoietic systems include living organisms, such as cells and organisms.
By comparison allopoietic systems are systems that produce outputs which are not part of the system itself. Examples of allopoietic systems include factories, which produce goods that are not part of the factory itself.
While system boundaries are always somewhat arbitrary, autopoietic systems can define their boundaries by examining their operational closure; that is, by identifying the components and processes necessary for the system to maintain its identity and function, and treating their extent as a system boundary. By contrast, examination of the presence or absence of interfaces that encapsulate some or all aspects of systems operations can be a useful heuristic for determining system boundaries of allopoietic systems.
Autopoietic [systems have] an autonomous and self-maintaining unity ... The product of an autopoietic organization is thus not different from the organization itself. A cell produces cell-forming molecules, an organism keeps renewing its defining organs, a social group "produces" group-maintaining individuals ... In contrast, an allopoietic [system] is different from the [system] itself, it does not produce the components and processes which would realize it as a distinct unity. Thus, allopoietic systems are not perceived as "living" and are usually referred to as mechanistic or contrived systems.
[Complex] systems are open systems where the relationships amongst the components of the system are usually more important than the components themselves. Since there are also relationships with the environment, specifying clearly where a boundary could be, is not obvious. One way of dealing with the problem of boundaries is to introduce the notion of “operational closure” … an autopoietic system [is] regenerated through the interaction of its own products (components), and a boundary emerges as a result of the same constitutive processes … One should be careful, however, not to overemphasise the closure of the boundary. The boundary of a complex system is not clearly defined once it has “emerged”. Boundaries are simultaneously a function of the activity of the system itself, and a product of the strategy of description involved …—Paul Cilliers, Boundaries, Hierarchies and Networks in Complex Systems
The lesson of boundaries is hard even for systems thinkers to get. There is no single, legitimate boundary to draw around a system. We have to invent boundaries for clarity and sanity; and boundaries can produce problems when we forget that we’ve artificially created them.—Donella H Meadows, Thinking in Systems
In the formation of new boundaries, signals influence the structure of new boundaries at least as often as boundaries influence the formation of new signals … [The] hierarchy of boundaries and signals [as determined by inputs, agents, and the patterns/motifs/tags they respond to] provides an adaptive process that is much more directed, and more plausible, than random variation.—John H Holland, Signals and Boundaries: Building Blocks for Complex Adaptive Systems
[Cognitive] systems ... are assumed to be capable of reducing the information flow from the environment into the system by modeling the environment. We shall call this "informational closure" ... [noting that unpredictable] events that nevertheless do affect the system [still] give rise to an information flow into the system.—Bertschinger et al, Information and closure in systems theory
- Boundaries, Hierarchies and Networks in Complex Systems
- Signals and Boundaries: Building Blocks for Complex Adaptive Systems
- Information and closure in systems theory