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Making Sense of Top-Down Causation: Universality and Functional Equivalence in Physics and Biology

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Top-Down Causation and Emergence

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Abstract

Top-down causation is often taken to be a metaphysically suspicious type of causation that is found in a few complex systems, such as in human mind-body relations. However, as Ellis and others have shown, top-down causation is ubiquitous in physics as well as in biology. Top-down causation occurs whenever specific dynamic behaviors are realized or selected among a broader set of possible lower-level states. Thus understood, the occurrence of dynamic and structural patterns in physical and biological systems presents a problem for reductionist positions. We illustrate with examples of universality (a term primarily used in physics) and functional equivalence classes (a term primarily used in engineering and biology) how higher-level behaviors can be multiple realized by distinct lower-level systems or states. Multiple realizability in both contexts entails what Ellis calls “causal slack” between levels, or what others understand as relative explanatory autonomy. To clarify these notions further, we examine procedures for upscaling in multi-scale modeling. We argue that simple averaging strategies for upscaling only work for simplistic homogenous systems (such as an ideal gas), because of the scale-dependency of characteristic behaviors in multi-scale systems. We suggest that this interpretation has implications for what Ellis calls mechanical top-down causation, as it presents a stronger challenge to reductionism than typically assumed.

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Notes

  1. 1.

    Readers interested in these types of downward causation, as well as debates on the metaphysical implications of downward causation, may find Paoletti and Orilia’s (2017) comprehensive anthology on downward causation interesting. For examples of downward causation in ecology, see also (Allen and Star 1982; Ulanowicz 1986, 1997).

  2. 2.

    The net magnetization can also be understood as a difference in densities. The densities of up-spins vs. down-spins. This difference vanishes at the critical temperature, as the high temperature randomizes the directions of the spins.

  3. 3.

    This aspect is analyzed in further detail in (Green and Jones 2016).

  4. 4.

    Investigations of the stabilizing aspects of global constraints in networks have been explored much earlier, e.g., by Stuart Kauffman’s demonstrations of how the structure of Boolean networks constrains the possible network states (Kauffman 1969, 1993).

  5. 5.

    This necessarily involves abstraction from lower-level details. In the words of Ma et al.: “Here, instead of focusing on one specific signaling system that shows adaptation, we ask a more general question: what are all network topologies that are capable of robust adaptation?” They further state that the aim to “construct a unified function-topology mapping […] may otherwise be obscured by the details of any specific pathway and organism”. (Ma et al. 2009)

  6. 6.

    It goes (almost) without saying that this notion of “hidden variables” is not quantum mechanical.

  7. 7.

    This concern was for instance raised after a talk by Ellis entitled “On the Nature of Causality in Complex Systems”, at the conference The Causal Universe, Krakow, Poland, May 17–18, 2012. Available online: https://www.youtube.com/watch?v=nEhTkF3eG8Q. In the following we further elaborate on a possible response to this question.

  8. 8.

    Other examples from physics are discussed in (Bishop 2012; Christiansen 2000; see also Ellis 2018).

  9. 9.

    Note that “microstructure” here refers to structures far above the atomic and far below the continuum.

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Green, S., Batterman, R.W. (2021). Making Sense of Top-Down Causation: Universality and Functional Equivalence in Physics and Biology. In: Voosholz, J., Gabriel, M. (eds) Top-Down Causation and Emergence. Synthese Library, vol 439. Springer, Cham. https://doi.org/10.1007/978-3-030-71899-2_2

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