Basic to science as well to common sense is the root notion of causality, that things and processes in the world we experience are not totally random, but ordered in specific ways that allow for rational understanding through explanations of various types. In the transition from a mythological worldview to a rational one, the notion of guilt (in Greek aitia), as in a criminal being guilty of a crime, was metaphorically used to describe nonpersonal natural processes whenever one phenomenon would necessarily follow another. As one aim of modern science is to uncover the deep structure of the world beyond our immediate experience, its explanations deal with the different determinants (or causes) of processual order. Three classical conceptions of inquiry, associated with the traditions of Plato, Aristotle, and Archimedes, have provided influential ideas about the role of causal explanations in science.
In the Platonic tradition, certain properties of nature could be derived from a priori given mathematical structures. As discovered by the Pythagorean philosophers of nature, a specific mathematical structure (relations between small whole numbers) could be the key to a part of nature (such as acoustics), so why not see whether that same structure could also describe other areas (such as astronomy)? Although the latter attempt failed, the general idea of using the power of demonstrative or formal necessity in mathematics as a descriptive tool of natural causality is still vital in many areas of science, including cosmology and high-energy physics. Also, the use of analog mathematical structures to describe phenomena has become standard.
The Aristotelian tradition did not refuse mathematical description but saw it only as a tool in a search for the real causes of things. For Aristotle, there were four kinds of causes: the material cause (hyle or causa materialis) that describes the stuff of which something is made, the formal cause (eidos or causa formalis) that describes the organization of something, the efficient cause (to kineti’kon or causa efficiens) that describes the active forces by which the phenomenon comes into being, and the final cause (to’telos or causa finalis) that describes the purpose that it serves. Thus, for a house, bricks and mortar are its material cause, the plan of the house is its formal cause, the mason building it is its efficient cause, and the purpose of sheltering a family is its final cause.
In that ancient world of Aristotle, each phenomenon generally served a purpose. Aristotle did not consider the four causes as necessarily separate aspects of nature, but more like principles of explanation that may sometimes merge, as in the sprouting acorn becoming an oak tree where the formal, efficient, and final causes work together to actualize the characteristics of an adult oak. The popular renaissance critique of the final cause as implying the paradox of a future state (a goal) influencing a present state led to a dismissal of any pluralist conception of causes. In the subsequent mechanical world picture, only efficient causes were left as explanatory. The life sciences could not live up to this reduction but continued as a descriptive natural history with an essentially Aristotelian outlook, at least until Darwin would explain the final cause of adaptations by the efficient causes of natural selection and heredity. Yet, even the Darwinian paradigm could not account for the nonlinear mechanisms of self-organization in the organism’s embryonic development. Such goal-like (teleological) properties of development and self-reproduction remained necessary yet unexplained preconditions for the mechanics of natural selection.
The Archimedean tradition was founded by disciplines more physical than mathematical, although combining the two, such as optics, astronomy, mechanics, and music theory. The mathematical relations discovered by Archimedes (ca. 287–212 BC) in his books on mechanics were not a priori, as in the Platonic tradition, but derived from experience. However, the Aristotelian pursuit after the causes of the phenomena, especially the final ones, was regarded as metaphysical and so ignored. The Archimedean tradition includes such names as Ptolemaios, Johannes Kepler, Galileo Galilei, and Isaac Newton. Kepler started out as a Platonic, aiming to explain the Copernican system (which placed the Sun at the center of the solar system, in opposition to the Ptolemaic system) by regular polyhedrons, but failed and found the right laws for planetary movements through a mathematical analysis of Tycho Brahe’s empirical observations. Galileo found his laws of falling bodies by eschewing the search for a hypothetical cause of gravitational force and instead using measures proportional to the velocity of a moving body for the effect of this force.
Although the mechanical worldview emphasizes only the role of efficient causes as principles of explanation in physics, the very idea of cause gave way for a long period to skepticism about proving any real existence of causes (the positivism of David Hume), eventually seeing the concept of cause as a feature of the observing subject (the transcendental idealism of Immanuel Kant). Yet, in physics, the laws of nature as expressed in terms of mathematics came to play the explanatory role of the causes of a system’s movement. It was assumed that any natural system could be encoded into some formalism (e.g., a set of differential equations representing the basic laws governing the system) and that the entailment structure of that formalism perfectly mirrored the (efficient) causal structure of that part of nature. This view was compatible with a micro-determinism where a system’s macroscopic properties and processes are seen as completely determined by the behavior of the system’s constituent particles, governed by deterministic laws. This view was deeply questioned by quantum physics, and by Rosen’s work on fundamental limits on dynamic models of causal systems.
The complexity of causality, especially in goaldirected systems, was presaged by cybernetic research in the 1940s, dealing with negative feedback control (in animals and artifacts such as self-guiding missiles) and the role of information processing for the regulation of dynamic systems. A paradigmatic example is the closed causal loops connecting various physiological levels of hormones in the body, essential for maintaining a constant internal environment (homeostasis)—a modern version of the ancient symbol of uroboros, the snake biting its own tail.
The emergence of nonlinear science in the late 20th century increased interest in the old idea that causal explanations may not all reduce to simple one-to-one correspondences between cause and effect. The realization that complex systems may occupy different areas in phase space characterized by qualitatively distinct attractors, eventually separated by fractal borders, has questioned micro-determinism even more than the fact that many such nonlinear systems have a high sensitivity to the initial conditions (the butterfly effect).
Another insight is that complex things often selforganize as high-level patterns via processes of local interactions between simple entities. This emergence of wholes (or collective behavior of units) may be mimicked in causal explanations. Instead of top-down reductive explanations, nonlinear science provides additional bottom-up explanations of emergent phenomena. Although these explanations are still reductive (in the methodological sense that one can show exactly what is going on from step to step in a simulation of the system), the complexity makes prediction impossible; thus, computational shortcuts to predict a future state can rarely be found.
As an emergent whole is formed bottom-up, its organization constrains its components in a top-down manner, that has been called downward causation (DC). There are three interpretations of DC: in strong DC, the emergent whole (a human mind) effectuates a change in the very laws that govern the lower-level (like free will might suspend what normally determines the action of the brain’s neurons). This interpretation is often related to vitalist and dualist conceptions of life and mind and is hard to reconcile with science. In medium DC, lower-level laws remain unaffected; yet, their boundary conditions are constrained by the emergent pattern (a mental representation), which is considered just as real as the components of the system (neuronal signaling). Here, the state of the higher level works as a factor selecting which of the many possible next states of the high level may emerge from the low level. In weak DC, the emergent higher levels are seen as regulated by stable (cyclic or chaotic) attractors for the dynamics of the lower level. The fact that a biological species consists of stable organisms is not solely a product of natural selection, but is a result of such internal, formal properties in the system’s organization—the job of natural selection being to sort out the possible stable organisms and find those most fit for the given milieu (Kauffman, 1993; Goodwin, 1994). It should be emphasized that DC is not a form of efficient causation (involving a temporal sequence from cause to effect), rather it is a modern version of the Aristotelian formal and final cause.
Nonlinear science may be said to integrate a Platonic appreciation of universality (as found in the equations governing the passage to chaos in systems of quite distinct material nature), an Aristotelian acceptance of several types of causes, and an Archimedean pragmatism regarding the deeper status of determinism and causality. The latter is reflected in the fact that although deterministic chaos characterizes a large class of systems, this does not imply that these systems (or nature) are fully deterministic. The determinism refers to the mathematical tools used rather than an ontological notion of causality.
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Emmeche, C, Stjernfelt, F. & Køppe, S. 2000. Levels, Emergence, and three versions of downward causation. In Downward Causation. Minds, Bodies and Matter, edited by P.B.Andersen, C.Emmeche, N.O.Finnemann & P.V.Christiansen, aarhus: Aarhus University Press, pp. 13–34
Fox, R.F. 1982. Biological Energy Transduction: The Uroboros, New York: Wiley
Goodwin, B. 1994. How the Leopard Changed Its Spots: The Evolution of Complexity, New York: Scribner’s
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