In recent decades, several theories have claimed to explain the teleological causality of organisms as a function of self-organising and self-producing processes. The most widely cited theories of this sort are variations of autopoiesis, originally introduced by Maturana and Varela. More recent modifications of autopoietic theory have focused on system organisation, closure of constraints and autonomy to account for organism teleology. This article argues that the treatment of teleology in autopoiesis and other organisation theories is inconclusive for three reasons: First, non-living self-organising processes like autocatalysis meet the defining features of autopoiesis without being teleological; second, organisational approaches, whether defined in terms of the closure of constraints, self-determination or autonomy, are unable to specify teleological normativity, that is, the individuation of an ultimate beneficiary; third, all self-organised systems produce local order by maximising the throughput of energy and/or material (obeying the maximum entropy production (MEP) principle) and thereby are specifically organised to undermine their own critical boundary conditions. Despite these inadequacies, an alternative approach called teleodynamics accounts for teleology. This theory shows how multiple self-organising processes can be collectively linked so that they counter each other’s MEP principle tendencies to become codependent. Teleodynamics embraces – not ignoring – the difficulties of self-organisation, but reinstates teleology as a radical phase transition distinguishing systems embodying an orientation towards their own beneficial ends from those that lack normative character.
Autopoietic systems are self-defining and real-world entities of a natural kind. They are subject to natural laws. It is suggested that the theory of emergence and the law of maximum entropy production relate to, and may be predictive of, the emergence, development, and evolution of autopoietic entities, including supra-human systems. \\Not to be confused with institutionalized categories such as family, corporation, nation, etc… autopoietic supra-human systems are irreducible entities of a different order from the mutually causal interactions, conversations and compliances, that produce them and are inaccessible at the level from which they emerge. \\The energy driving the emergence of supra-human systems is the human lifetime locked up in au-topoietic organization and ultimately dispersed, thus maximizing entropy production in the social domain. The possibly dire effects on the human state are considered. \\This hypothesis justifies closing the gap between the naral and social sciences under the rubric of general systems studies.
Autopoiesis was introduced into the literature by Maturana and Varela as the name for a particular system description which they claimed was necessary and sufficient to define the living and also to explain it. The term has been widely applied in the literature instead to spontaneous order production or self-organization in general, whether living or not. Zeleny and Hufford, authors of the focal paper for this volume, would like to continue this tradition. While their effort to seek the generic behavior of spontaneous order is to be commended, this particular move must be rejected. In the first place, if the concept of autopoiesis can be used in this way it immediately shows the concept’s failure to define and explain the living, making it enigmatic as to what is being generalized. In the second place, the whole concept of autopoiesis is contrived at its foundations where it is miraculously decoupled from the physical world to promulgate a solipsistic epistemology with abhorrent social consequences. An alternative ecological physical view is presented here which shows that purposive, creative behavior is a consequence of natural law itself where order is produced such that order acts back upon order to produce more order. The ecological view rejects subject-vs, -object debates (“us” vs. “reality”) as academic; all ordered states are higher-order symmetry states of the world itself. Social praxis and evolutionary competence have an amplifed meaning in such a world, one that is not yet fully determined and where small actions, intended or unintended, can produce large consequences.
Villalobos M. (2016) Nonequilibrium thermodynamic stability: The apparent teleology of living beings. In: Gershenson C., Froese T., Siqueiros J. M., Aguilar W., Izquierdo E. J. & Sayama H. (eds.) Proceedings of the Artificial Life Conference 2016. MIT Press, Cambridge MA: 702–703. https://cepa.info/7514
Among physical systems, living beings are usually thought of as the only genuinely teleological natural systems. In this paper, I argue that the alleged teleology of living beings is not a real property but only an appearance, behind which what really exists is a complex version of stability. The complexity of living beings as stable systems has to do mainly, though not exclusively, so I argue, with the fact that living beings are dissipative structures which obey the thermodynamic principle of maximum entropy production.
Wene C.-O. (2015) A cybernetic view on learning curves and energy policy. Kybernetes 44(6/7): 852–865.
Purpose: The purpose of this paper is to demonstrate that cybernetic theory explains learning curves and sets the curves as legitimate and efficient tools for a pro-active energy technology policy. Design/methodology/approach – The learning system is a non-trivial machine that is kept in non-equilibrium steady state at minimum entropy production by competitive, equilibrium markets. The system has operational closure and the learning curve expresses its eigenbehaviour. This eigenbehaviour is analysed not in calendar time but in the characteristic time of the system, i.e., its eigentime. Measured in eigentime, the minimum entropy production in the steady-state learning system is constant. The double closure mechanism described by Heinz von Förster makes it possible for the learning system to change (adapt) its eigenbehaviour without compromising its operational closure. Findings: By obeying basic laws of second order cybernetics and of non-equilibrium thermodynamics the learning system self-organises its learning to follow an optimal path described by the learning curve. The learning rates are obtained through an operator formalism and the results explain observed distributions. Application to solar cell (photo-voltaic) modules indicates that the silicon scarcity bubble 2005–2008 produced excess entropy corresponding to costs of the order of 100 billion US dollars. Research limitations/implications: Grounding technology learning and learning curves in cybernetics and non-equilibrium thermodynamics open up new possibilities to understand technology shifts through radical innovations or paradigm changes. Practical implications: Learning curves are legitimate and efficient tools for energy policy and industrial strategy. Originality/value – Grounding of technology learning and learning curves in cybernetic and thermodynamic theory provides a stable theoretical basis for applications in industry and policy.