Complex systems |
---|
Topics |
In philosophy, systems theory, science, and art, emergence occurs when a complex entity has properties or behaviors that its parts do not have on their own, and emerge only when they interact in a wider whole.
Emergence plays a central role in theories of integrative levels and of complex systems. For instance, the phenomenon of life as studied in biology is an emergent property of chemistry and physics.
In philosophy, theories that emphasize emergent properties have been called emergentism. [1]
Philosophers often understand emergence as a claim about the etiology of a system's properties. An emergent property of a system, in this context, is one that is not a property of any component of that system, but is still a feature of the system as a whole. Nicolai Hartmann (1882–1950), one of the first modern philosophers to write on emergence, termed this a categorial novum (new category). [2]
This concept of emergence dates from at least the time of Aristotle. [3] The many scientists and philosophers [4] who have written on the concept include John Stuart Mill ( Composition of Causes , 1843) [5] and Julian Huxley [6] (1887–1975).
The philosopher G. H. Lewes coined the term "emergent" in 1875, distinguishing it from the merely "resultant":
Every resultant is either a sum or a difference of the co-operant forces; their sum, when their directions are the same – their difference, when their directions are contrary. Further, every resultant is clearly traceable in its components, because these are homogeneous and commensurable. It is otherwise with emergents, when, instead of adding measurable motion to measurable motion, or things of one kind to other individuals of their kind, there is a co-operation of things of unlike kinds. The emergent is unlike its components insofar as these are incommensurable, and it cannot be reduced to their sum or their difference. [7] [8]
Usage of the notion "emergence" may generally be subdivided into two perspectives, that of "weak emergence" and "strong emergence". One paper discussing this division is Weak Emergence, by philosopher Mark Bedau. In terms of physical systems, weak emergence is a type of emergence in which the emergent property is amenable to computer simulation or similar forms of after-the-fact analysis (for example, the formation of a traffic jam, the structure of a flock of starlings in flight or a school of fish, or the formation of galaxies). Crucial in these simulations is that the interacting members retain their independence. If not, a new entity is formed with new, emergent properties: this is called strong emergence, which it is argued cannot be simulated, analysed or reduced.[ citation needed ]
David Chalmers writes that emergence often causes confusion in philosophy and science due to a failure to demarcate strong and weak emergence, which are "quite different concepts". [9]
Some common points between the two notions are that emergence concerns new properties produced as the system grows, which is to say ones which are not shared with its components or prior states. Also, it is assumed that the properties are supervenient rather than metaphysically primitive. [10]
Weak emergence describes new properties arising in systems as a result of the interactions at a fundamental level. However, Bedau stipulates that the properties can be determined only by observing or simulating the system, and not by any process of a reductionist analysis. As a consequence the emerging properties are scale dependent: they are only observable if the system is large enough to exhibit the phenomenon. Chaotic, unpredictable behaviour can be seen as an emergent phenomenon, while at a microscopic scale the behaviour of the constituent parts can be fully deterministic.[ citation needed ]
Bedau notes that weak emergence is not a universal metaphysical solvent, as the hypothesis that consciousness is weakly emergent would not resolve the traditional philosophical questions about the physicality of consciousness. However, Bedau concludes that adopting this view would provide a precise notion that emergence is involved in consciousness, and second, the notion of weak emergence is metaphysically benign. [10]
Strong emergence describes the direct causal action of a high-level system on its components; qualities produced this way are irreducible to the system's constituent parts. [11] The whole is other than the sum of its parts. It is argued then that no simulation of the system can exist, for such a simulation would itself constitute a reduction of the system to its constituent parts. [10] Physics lacks well-established examples of strong emergence, unless it is interpreted as the impossibility in practice to explain the whole in terms of the parts. Practical impossibility may be a more useful distinction than one in principle, since it is easier to determine and quantify, and does not imply the use of mysterious forces, but simply reflects the limits of our capability. [12]
Some thinkers question the plausibility of strong emergence as contravening our usual understanding of physics. Mark A. Bedau observes:
Although strong emergence is logically possible, it is uncomfortably like magic. How does an irreducible but supervenient downward causal power arise, since by definition it cannot be due to the aggregation of the micro-level potentialities? Such causal powers would be quite unlike anything within our scientific ken. This not only indicates how they will discomfort reasonable forms of materialism. Their mysteriousness will only heighten the traditional worry that emergence entails illegitimately getting something from nothing. [10]
Strong emergence can be criticized for leading to causal overdetermination. The canonical example concerns emergent mental states (M and M∗) that supervene on physical states (P and P∗) respectively. Let M and M∗ be emergent properties. Let M∗ supervene on base property P∗. What happens when M causes M∗? Jaegwon Kim says:
In our schematic example above, we concluded that M causes M∗ by causing P∗. So M causes P∗. Now, M, as an emergent, must itself have an emergence base property, say P. Now we face a critical question: if an emergent, M, emerges from basal condition P, why cannot P displace M as a cause of any putative effect of M? Why cannot P do all the work in explaining why any alleged effect of M occurred? If causation is understood as nomological (law-based) sufficiency, P, as M's emergence base, is nomologically sufficient for it, and M, as P∗'s cause, is nomologically sufficient for P∗. It follows that P is nomologically sufficient for P∗ and hence qualifies as its cause...If M is somehow retained as a cause, we are faced with the highly implausible consequence that every case of downward causation involves overdetermination (since P remains a cause of P∗ as well). Moreover, this goes against the spirit of emergentism in any case: emergents are supposed to make distinctive and novel causal contributions. [13]
If M is the cause of M∗, then M∗ is overdetermined because M∗ can also be thought of as being determined by P. One escape-route that a strong emergentist could take would be to deny downward causation. However, this would remove the proposed reason that emergent mental states must supervene on physical states, which in turn would call physicalism into question, and thus be unpalatable for some philosophers and physicists.
Crutchfield regards the properties of complexity and organization of any system as subjective qualities determined by the observer.
Defining structure and detecting the emergence of complexity in nature are inherently subjective, though essential, scientific activities. Despite the difficulties, these problems can be analysed in terms of how model-building observers infer from measurements the computational capabilities embedded in non-linear processes. An observer's notion of what is ordered, what is random, and what is complex in its environment depends directly on its computational resources: the amount of raw measurement data, of memory, and of time available for estimation and inference. The discovery of structure in an environment depends more critically and subtly, though, on how those resources are organized. The descriptive power of the observer's chosen (or implicit) computational model class, for example, can be an overwhelming determinant in finding regularity in data. [14]
The low entropy of an ordered system can be viewed as an example of subjective emergence: the observer sees an ordered system by ignoring the underlying microstructure (i.e. movement of molecules or elementary particles) and concludes that the system has a low entropy. [15] On the other hand, chaotic, unpredictable behaviour can also be seen as subjective emergent, while at a microscopic scale the movement of the constituent parts can be fully deterministic.
In physics, emergence is used to describe a property, law, or phenomenon which occurs at macroscopic scales (in space or time) but not at microscopic scales, despite the fact that a macroscopic system can be viewed as a very large ensemble of microscopic systems. [16] [17]
An emergent behavior of a physical system is a qualitative property that can only occur in the limit that the number of microscopic constituents tends to infinity. [18]
According to Robert Laughlin, [11] for many-particle systems, nothing can be calculated exactly from the microscopic equations, and macroscopic systems are characterised by broken symmetry: the symmetry present in the microscopic equations is not present in the macroscopic system, due to phase transitions. As a result, these macroscopic systems are described in their own terminology, and have properties that do not depend on many microscopic details.
Novelist Arthur Koestler used the metaphor of Janus (a symbol of the unity underlying complements like open/shut, peace/war) to illustrate how the two perspectives (strong vs. weak or holistic vs. reductionistic) should be treated as non-exclusive, and should work together to address the issues of emergence. [19] Theoretical physicist PW Anderson states it this way:
The ability to reduce everything to simple fundamental laws does not imply the ability to start from those laws and reconstruct the universe. The constructionist hypothesis breaks down when confronted with the twin difficulties of scale and complexity. At each level of complexity entirely new properties appear. Psychology is not applied biology, nor is biology applied chemistry. We can now see that the whole becomes not merely more, but very different from the sum of its parts. [20]
Meanwhile, others have worked towards developing analytical evidence of strong emergence. Renormalization methods in theoretical physics enable physicists to study critical phenomena that are not tractable as the combination of their parts. [21] In 2009, Gu et al. presented a class of infinite physical systems that exhibits non-computable macroscopic properties. [22] [23] More precisely, if one could compute certain macroscopic properties of these systems from the microscopic description of these systems, then one would be able to solve computational problems known to be undecidable in computer science. These results concern infinite systems, finite systems being considered computable. However, macroscopic concepts which only apply in the limit of infinite systems, such as phase transitions and the renormalization group, are important for understanding and modeling real, finite physical systems. Gu et al. concluded that
Although macroscopic concepts are essential for understanding our world, much of fundamental physics has been devoted to the search for a 'theory of everything', a set of equations that perfectly describe the behavior of all fundamental particles. The view that this is the goal of science rests in part on the rationale that such a theory would allow us to derive the behavior of all macroscopic concepts, at least in principle. The evidence we have presented suggests that this view may be overly optimistic. A 'theory of everything' is one of many components necessary for complete understanding of the universe, but is not necessarily the only one. The development of macroscopic laws from first principles may involve more than just systematic logic, and could require conjectures suggested by experiments, simulations or insight. [22]
Human beings are the basic elements of social systems, which perpetually interact and create, maintain, or untangle mutual social bonds. Social bonds in social systems are perpetually changing in the sense of the ongoing reconfiguration of their structure. [24] An early argument (1904–05) for the emergence of social formations can be found in Max Weber's most famous work, The Protestant Ethic and the Spirit of Capitalism . [25] Recently, the emergence of a new social system is linked with the emergence of order from nonlinear relationships among multiple interacting units, where multiple interacting units are individual thoughts, consciousness, and actions. [26] In the case of the global economic system, under capitalism, growth, accumulation and innovation can be considered emergent processes where not only does technological processes sustain growth, but growth becomes the source of further innovations in a recursive, self-expanding spiral. In this sense, the exponential trend of the growth curve reveals the presence of a long-term positive feedback among growth, accumulation, and innovation; and the emergence of new structures and institutions connected to the multi-scale process of growth. [27] This is reflected in the work of Karl Polanyi, who traces the process by which labor and nature are converted into commodities in the passage from an economic system based on agriculture to one based on industry. [28] This shift, along with the idea of the self-regulating market, set the stage not only for another economy but also for another society. The principle of emergence is also brought forth when thinking about alternatives to the current economic system based on growth facing social and ecological limits. Both degrowth and social ecological economics have argued in favor of a co-evolutionary perspective for theorizing about transformations that overcome the dependence of human wellbeing on economic growth. [29] [30]
Economic trends and patterns which emerge are studied intensively by economists. [31] Within the field of group facilitation and organization development, there have been a number of new group processes that are designed to maximize emergence and self-organization, by offering a minimal set of effective initial conditions. Examples of these processes include SEED-SCALE, appreciative inquiry, Future Search, the world cafe or knowledge cafe, Open Space Technology, and others (Holman, 2010 [32] ). In international development, concepts of emergence have been used within a theory of social change termed SEED-SCALE to show how standard principles interact to bring forward socio-economic development fitted to cultural values, community economics, and natural environment (local solutions emerging from the larger socio-econo-biosphere). These principles can be implemented utilizing a sequence of standardized tasks that self-assemble in individually specific ways utilizing recursive evaluative criteria. [33]
Looking at emergence in the context of social and systems change, invites us to reframe our thinking on parts and wholes and their interrelation. Unlike machines, living systems at all levels of recursion - be it a sentient body, a tree, a family, an organisation, the education system, the economy, the health system, the political system etc - are continuously creating themselves. They are continually growing and changing along with their surrounding elements, and therefore are more than the sum of their parts. As Peter Senge and co-authors put forward in the book Presence: Exploring profound change in People, Organizations and Society, "as long as our thinking is governed by habit - notably industrial, "machine age" concepts such as control, predictability, standardization, and "faster is better" - we will continue to recreate institutions as they have been, despite their disharmony with the larger world, and the need for all living systems to evolve." [34] While change is predictably constant, it is unpredictable in direction and often occurs at second and nth orders of systemic relationality. [35] Understanding emergence and what creates the conditions for different forms of emergence to occur, either insidious or nourishing vitality, is essential in the search for deep transformations.
The works of Nora Bateson and her colleagues at the International Bateson Institute delves into this. Since 2012, they have been researching questions such as what makes a living system ready to change? Can unforeseen ready-ness for change be nourished? Here being ready is not thought of as being prepared, but rather as nourishing the flexibility we do not yet know will be needed. These inquiries challenge the common view that a theory of change is produced from an identified preferred goal or outcome. As explained in their paper An essay on ready-ing: Tending the prelude to change: [35] "While linear managing or controlling of the direction of change may appear desirable, tending to how the system becomes ready allows for pathways of possibility previously unimagined." This brings a new lense to the field of emergence in social and systems change as it looks to tending the pre-emergent process. Warm Data Labs are the fruit of their praxis, they are spaces for transcontextual mutual learning in which aphanipoetic phenomena unfold. [36] (Read about Aphanipoesis ). Having hosted hundreds of Warm Data processes with 1000s of participants, they have found that these spaces of shared poly-learning across contexts lead to a realm of potential change, a necessarily obscured zone of wild interaction of unseen, unsaid, unknown flexibility. [35] It is such flexibility that nourishes the ready-ing living systems require to respond to complex situations in new ways and change. In other words, this readying process preludes what will emerge. When exploring questions of social change, it is important to ask ourselves, what is submerging in the current social imaginary and perhaps, rather than focus all our resources and energy on driving direct order responses, to nourish flexibility with ourselves, and the systems we are a part of.
Another approach that engages with the concept of emergence for social change is Theory U, where "deep emergence" is the result of self-transcending knowledge after a successful journey along the U through layers of awareness. [37] This practice nourishes transformation at the inner-being level, which enables new ways of being, seeing and relating to emerge. The concept of emergence has also been employed in the field of facilitation. In Emergent Strategy, adrienne maree brown, defines emergent strategies as "ways for humans to practice complexity and grow the future through relatively simple interactions.". [38]
In linguistics, the concept of emergence has been applied in the domain of stylometry to explain the interrelation between the syntactical structures of the text and the author style (Slautina, Marusenko, 2014). [39] It has also been argued that the structure and regularity of language grammar, or at least language change, is an emergent phenomenon. [40] While each speaker merely tries to reach their own communicative goals, they use language in a particular way. If enough speakers behave in that way, language is changed. [41] In a wider sense, the norms of a language, i.e. the linguistic conventions of its speech society, can be seen as a system emerging from long-time participation in communicative problem-solving in various social circumstances. [42]
The bulk conductive response of binary (RC) electrical networks with random arrangements, known as the Universal Dielectric Response (UDR), can be seen as emergent properties of such physical systems. Such arrangements can be used as simple physical prototypes for deriving mathematical formulae for the emergent responses of complex systems. [43] Internet traffic can also exhibit some seemingly emergent properties. In the congestion control mechanism, TCP flows can become globally synchronized at bottlenecks, simultaneously increasing and then decreasing throughput in coordination. Congestion, widely regarded as a nuisance, is possibly an emergent property of the spreading of bottlenecks across a network in high traffic flows which can be considered as a phase transition. [44] Some artificially intelligent (AI) computer applications simulate emergent behavior. [45] One example is Boids, which mimics the swarming behavior of birds. [46]
In religion, emergence grounds expressions of religious naturalism and syntheism in which a sense of the sacred is perceived in the workings of entirely naturalistic processes by which more complex forms arise or evolve from simpler forms. Examples are detailed in The Sacred Emergence of Nature by Ursula Goodenough & Terrence Deacon and Beyond Reductionism: Reinventing the Sacred by Stuart Kauffman, both from 2006, as well as Syntheism – Creating God in The Internet Age by Alexander Bard & Jan Söderqvist from 2014 and Emergentism: A Religion of Complexity for the Metamodern World by Brendan Graham Dempsey (2022).[ citation needed ]
Michael J. Pearce has used emergence to describe the experience of works of art in relation to contemporary neuroscience. [47] Practicing artist Leonel Moura, in turn, attributes to his "artbots" a real, if nonetheless rudimentary, creativity based on emergent principles. [48]
Condensed matter physics is the field of physics that deals with the macroscopic and microscopic physical properties of matter, especially the solid and liquid phases, that arise from electromagnetic forces between atoms and electrons. More generally, the subject deals with condensed phases of matter: systems of many constituents with strong interactions among them. More exotic condensed phases include the superconducting phase exhibited by certain materials at extremely low cryogenic temperatures, the ferromagnetic and antiferromagnetic phases of spins on crystal lattices of atoms, the Bose–Einstein condensates found in ultracold atomic systems, and liquid crystals. Condensed matter physicists seek to understand the behavior of these phases by experiments to measure various material properties, and by applying the physical laws of quantum mechanics, electromagnetism, statistical mechanics, and other physics theories to develop mathematical models and predict the properties of extremely large groups of atoms.
Complexity characterizes the behavior of a system or model whose components interact in multiple ways and follow local rules, leading to non-linearity, randomness, collective dynamics, hierarchy, and emergence.
Quantum mechanics is a fundamental theory that describes the behavior of nature at and below the scale of atoms. It is the foundation of all quantum physics, which includes quantum chemistry, quantum field theory, quantum technology, and quantum information science.
In physics, statistical mechanics is a mathematical framework that applies statistical methods and probability theory to large assemblies of microscopic entities. Sometimes called statistical physics or statistical thermodynamics, its applications include many problems in the fields of physics, biology, chemistry, neuroscience, computer science, information theory and sociology. Its main purpose is to clarify the properties of matter in aggregate, in terms of physical laws governing atomic motion.
A complex system is a system composed of many components which may interact with each other. Examples of complex systems are Earth's global climate, organisms, the human brain, infrastructure such as power grid, transportation or communication systems, complex software and electronic systems, social and economic organizations, an ecosystem, a living cell, and, ultimately, for some authors, the entire universe.
Reductionism is any of several related philosophical ideas regarding the associations between phenomena which can be described in terms of simpler or more fundamental phenomena. It is also described as an intellectual and philosophical position that interprets a complex system as the sum of its parts.
Holism is the interdisciplinary idea that systems possess properties as wholes apart from the properties of their component parts. The aphorism "The whole is greater than the sum of its parts", typically attributed to Aristotle, is often given as a glib summary of this proposal. The concept of holism can inform the methodology for a broad array of scientific fields and lifestyle practices. When applications of holism are said to reveal properties of a whole system beyond those of its parts, these qualities are referred to as emergent properties of that system. Holism in all contexts is often placed in opposition to reductionism, a dominant notion in the philosophy of science that systems containing parts contain no unique properties beyond those parts. Proponents of holism consider the search for emergent properties within systems to be demonstrative of their perspective.
Self-organization, also called spontaneous order in the social sciences, is a process where some form of overall order arises from local interactions between parts of an initially disordered system. The process can be spontaneous when sufficient energy is available, not needing control by any external agent. It is often triggered by seemingly random fluctuations, amplified by positive feedback. The resulting organization is wholly decentralized, distributed over all the components of the system. As such, the organization is typically robust and able to survive or self-repair substantial perturbation. Chaos theory discusses self-organization in terms of islands of predictability in a sea of chaotic unpredictability.
Social simulation is a research field that applies computational methods to study issues in the social sciences. The issues explored include problems in computational law, psychology, organizational behavior, sociology, political science, economics, anthropology, geography, engineering, archaeology and linguistics.
Self-organized criticality (SOC) is a property of dynamical systems that have a critical point as an attractor. Their macroscopic behavior thus displays the spatial or temporal scale-invariance characteristic of the critical point of a phase transition, but without the need to tune control parameters to a precise value, because the system, effectively, tunes itself as it evolves towards criticality.
Emergentism is the belief in emergence, particularly as it involves consciousness and the philosophy of mind. A property of a system is said to be emergent if it is a new outcome of some other properties of the system and their interaction, while it is itself different from them. Within the philosophy of science, emergentism is analyzed both as it contrasts with and parallels reductionism. This philosophical theory suggests that higher-level properties and phenomena arise from the interactions and organization of lower-level entities yet are not reducible to these simpler components. It emphasizes the idea that the whole is more than the sum of its parts. Historically, emergentism has significantly influenced various scientific and philosophical ideas, highlighting the complexity and interconnectedness of natural systems.
In sociology, social complexity is a conceptual framework used in the analysis of society. In the sciences, contemporary definitions of complexity are found in systems theory, wherein the phenomenon being studied has many parts and many possible arrangements of the parts; simultaneously, what is complex and what is simple are relative and change in time.
Computational sociology is a branch of sociology that uses computationally intensive methods to analyze and model social phenomena. Using computer simulations, artificial intelligence, complex statistical methods, and analytic approaches like social network analysis, computational sociology develops and tests theories of complex social processes through bottom-up modeling of social interactions.
Dynamical systems theory is an area of mathematics used to describe the behavior of complex dynamical systems, usually by employing differential equations or difference equations. When differential equations are employed, the theory is called continuous dynamical systems. From a physical point of view, continuous dynamical systems is a generalization of classical mechanics, a generalization where the equations of motion are postulated directly and are not constrained to be Euler–Lagrange equations of a least action principle. When difference equations are employed, the theory is called discrete dynamical systems. When the time variable runs over a set that is discrete over some intervals and continuous over other intervals or is any arbitrary time-set such as a Cantor set, one gets dynamic equations on time scales. Some situations may also be modeled by mixed operators, such as differential-difference equations.
Generative science is an area of research that explores the natural world and its complex behaviours. It explores ways "to generate apparently unanticipated and infinite behaviour based on deterministic and finite rules and parameters reproducing or resembling the behavior of natural and social phenomena". By modelling such interactions, it can suggest that properties exist in the system that had not been noticed in the real world situation. An example field of study is how unintended consequences arise in social processes.
A complex adaptive system is a system that is complex in that it is a dynamic network of interactions, but the behavior of the ensemble may not be predictable according to the behavior of the components. It is adaptive in that the individual and collective behavior mutate and self-organize corresponding to the change-initiating micro-event or collection of events. It is a "complex macroscopic collection" of relatively "similar and partially connected micro-structures" formed in order to adapt to the changing environment and increase their survivability as a macro-structure. The Complex Adaptive Systems approach builds on replicator dynamics.
Computer simulation is a prominent method in organizational studies and strategic management. While there are many uses for computer simulation, most academics in the fields of strategic management and organizational studies have used computer simulation to understand how organizations or firms operate. More recently, however, researchers have also started to apply computer simulation to understand organizational behaviour at a more micro-level, focusing on individual and interpersonal cognition and behavior such as team working.
Universal Darwinism, also known as generalized Darwinism, universal selection theory, or Darwinian metaphysics, is a variety of approaches that extend the theory of Darwinism beyond its original domain of biological evolution on Earth. Universal Darwinism aims to formulate a generalized version of the mechanisms of variation, selection and heredity proposed by Charles Darwin, so that they can apply to explain evolution in a wide variety of other domains, including psychology, linguistics, economics, culture, medicine, computer science, and physics.
In the physical sciences, a particle is a small localized object which can be described by several physical or chemical properties, such as volume, density, or mass. They vary greatly in size or quantity, from subatomic particles like the electron, to microscopic particles like atoms and molecules, to macroscopic particles like powders and other granular materials. Particles can also be used to create scientific models of even larger objects depending on their density, such as humans moving in a crowd or celestial bodies in motion.
Artificial life is a field of study wherein researchers examine systems related to natural life, its processes, and its evolution, through the use of simulations with computer models, robotics, and biochemistry. The discipline was named by Christopher Langton, an American theoretical biologist, in 1986. In 1987, Langton organized the first conference on the field, in Los Alamos, New Mexico. There are three main kinds of alife, named for their approaches: soft, from software; hard, from hardware; and wet, from biochemistry. Artificial life researchers study traditional biology by trying to recreate aspects of biological phenomena.
The higher nexus is, in many of its structural elements, dependent on the lower, but is autonomous in its particular nature (its categorial novum). The chain of conditions of a real thing in the higher stratum contains an ample number of components from the lower strata; but they are only partial aspects of it, and therefore do not make its real possibility complete; they make it, in fact, neither necessary nor actual. The chain becomes complete only through the addition of real components of its own stratum. But these are under a categorially different kind of determination. Structurally, they belong to the higher real nexus itself, and are not found outside of it.
{{cite book}}
: CS1 maint: multiple names: translators list (link)Emergence is much discussed by both philosophers and scientists.
{{cite book}}
: |journal=
ignored (help)CS1 maint: location missing publisher (link)ISBN 0-87609-177-X
ISBN 0-226-47655-3
ISBN 0-415-42329-5
ISBN 1-443-87057-9