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Erschienen in:
Introduction to This Volume Kapitel lesen Erstes Kapitel lesen

2019 | OriginalPaper | Buchkapitel

7. A Software-Inspired Constructive View of Nature

verfasst von : Russ Abbott

Erschienen in: On the Cognitive, Ethical, and Scientific Dimensions of Artificial Intelligence

Verlag: Springer International Publishing

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Abstract

In their review article on “Scientific Reduction” Van Riel and Van Gulick (Scientific reduction. In: Zalta EN (ed) The Stanford encyclopedia of philosophy (Spring 2016 edition). Stanford University, Stanford, 2016) write,
Saying that x reduces to y typically implies that x is nothing more than y or nothing over and above y.
The y to which an x reduces consists most often of x’s components. But virtually nothing can be reduced if to be “nothing more than” or “nothing over and above” its components means to have no properties other than those of its components, individually or aggregated. An atom has properties other than those of its quarks and electrons. A protein, a biological cell, and a hurricane—not to mention such man-made entities as houses, mobile phones, and automobiles—all have properties over and above their components. The properties of most entities depend on both those of the entity’s components and on how those components are put together. (That would seem obvious, but perhaps it’s not.)
One of the defining characteristics of what might be referred to as the creative disciplines—computer science, engineering, the creative arts, etc.—is a focus on understanding and using the effects of putting things together. They ask what new (and in human terms interesting and useful) properties can be realized by putting things together in new ways. Using software as an example I explore software construction, and I ask what, if anything, one gains by thinking of it reductively.
Reduction as nothing-more-than-ism tends to blind one to nature’s constructive aspects. I discuss nature’s tools for creating new phenomena, including negative interactive energy, means for creating and tapping stores of usable energy, autopoiesis, and biological evolution.

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Vorheriges Kapitel Antimodularity: Pragmatic Consequences of Computational Complexity on Scientific Explanation
Nächstes Kapitel Politics and Epistemology of Big Data: A Critical Assessment
Fußnoten
1
Extracts are slightly paraphrased throughout the paper.
 
2
Brigandt and Love (2015) distinguish two primary categories of reduction: “theory reduction, the claim that a higher level theory can be logically deduced from a lower level theory, and explanatory reduction, the claim that representations of higher level features can be explained by representations of lower level features, typically by decomposing a higher level system into parts.” I focus primarily on explanatory reduction.
 
3
Gerd Van Riel seems to spell his name at different times with an upper or lower case “V.” His current affiliation, KU Leuven, (http://​www.​kuleuven.​be/​wieiswie/​en/​person/​u0019425, retrieved Sep 3, 2016) uses upper case.
 
4
Brigandt and Love also discuss methodological reduction (“biological systems are most fruitfully investigated at the lowest possible generally biochemical level)” and epistemic reduction (“knowledge about one scientific domain can be reduced to knowledge about a more fundamental level”).
 
5
This sounds uncontroversial, but the exchange of matter and energy between biological organisms and the environment raises questions. When does an oxygen or food molecule become part of an organism? When does waste matter become not part of an organism? Are organ transplants or component implants such as pacemakers, corneal replacements, tooth implants, or dental fillings part of an organism? What about disease agents and toxins? What about an organism’s biome and virome? Does a photon that conveys visual information become part of an organism—and if so when? Given these considerations it seems a much more complex issue to decide what constitutes a biological system than this innocent-sounding statement implies.
 
6
Physics being what it is, the discovery of any such phenomena would inevitably lead to “new” physics anyway.
 
7
As I’m using the terms, to implement is to create something that has certain pre-specified properties. Engineers implement systems with required functionality. To realize—as in the heart realizes a pumping capability—is for something to come into existence that happens to have some properties. Nature realizes various functionalities without having those functionalities as teleological goals. See Abbott (2016a) for an expanded discussion.
 
8
Wilson (1998) called this recomposition: to show that components can be reassembled to “capture the key properties of the entire ensembles.”
 
10
Recall our earlier discussion of implementation and realization.
 
11
Physics is still investigating the primitives. But given the primitives as currently understood, the point still holds.
 
12
Although Strassler (2015) coined the term, the phenomenon (under various names) is fundamental to physics.
 
13
See example images from Lawrence Berkeley National Lab: http://​particleadventur​e.​org/​history-universe.​html
 
14
I was unable to find a relevant philosophical analysis of the term entity. Bricker (2014), for example, discusses ontological commitment but not an analysis of the grounds that justify ontological commitment.
 
15
Such phenomena account for many of the things traditionally considered emergent. Abbott (2010) called this static emergence. It is static because the results are statically stable entities. This mechanism is not responsible for aggregations or software objects, which are not bound together by negative interaction energy.
 
16
Work is defined as force applied over distance. I don’t know whether there is a general term for energy available for doing work. Thermodynamic free energy may not cover all cases, e.g., the kinetic energy of a bowling ball rolling down an alley or energy transferred from a planet to a satellite during a gravitational slingshot maneuver. Even isolated orbiting masses radiate energy—reflecting the consumption of usable energy. See Koberlein (2016).
 
17
Topological properties such as ball joints also help.
 
18
In his elegant book, Hoffmann points out that the “wind” is random rather than directional.
 
19
The term autopoiesis has been dismissed as vacuous, trivial, overly complex, self-referential, circular, and intentionally mysterious. Maturana and Varela’s original idea (1980) was to identify a category of systems that have the capacity to repair themselves. The claim is that all living systems are autopoietic but not that autopoiesis is sufficient for life. See Razeto-Barry (2012) for a review of the history and criticism.
 
20
Abbott (2010) used the term dynamic emergence for systems that hold themselves together through self- maintenance. Abbott (2016a) argues that together static and dynamic emergence demystify emergence and render the term nearly superfluous.
 
21
This section discusses biological-style evolution, not general evolution discussed earlier. For convenience, I’ll use the term evolution for biological evolution and general evolution when referring to the broader process.
 
22
I’m using the term procreation rather than reproduction since the offspring are generally not exact copies.
 
23
I wouldn’t argue that DNA is the design of an organism or that DNA is the software an organism “runs.” That’s a greatly over-simplified picture of the role of DNA. But I think it’s fair to say that the meta-information about the form and function of organisms that DNA encodes plays a role similar to a product’s design.
 
Literatur
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———. 2016a. The end of (traditional) emergence; introducing reactive emergence. Journal of Public Policy and Complex Systems 2/2: 91–107.
———. 2016b. Autonomous causality. Submitted for publication.
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———. 2014. The minimal autopoietic unit. Origins of Life and Evolution of Biospheres 44 (4): 335–338.CrossRef
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Metadaten
Titel
A Software-Inspired Constructive View of Nature
verfasst von
Russ Abbott
Copyright-Jahr
2019
Buch
On the Cognitive, Ethical, and Scientific Dimensions of Artificial Intelligence

Print ISBN: 978-3-030-01799-6

Electronic ISBN: 978-3-030-01800-9

Copyright-Jahr: 2019

DOI
https://doi.org/10.1007/978-3-030-01800-9_7

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