Machine Dreams

If the emergentist-materialist ontology underlying biology (and, as a matter of fact, all the factual sciences) is correct, the bios constitutes a distinct ontic level the entities in which are characterized by emergent properties. The properties of biotic systems are then not (ontologically) reducible to the properties of their components, although we may be able to partially explain and predict them from the properties of their components… The belief that one has reduced a system by exhibiting [for instance] its components, which is indeed nothing but physical and chemical, is insufficient: physics and chemistry do not account for the structure, in particular the organization, of biosystems and their emergent properties (Mahner and Bunge 1997: 197). (Robert 2004: 132)

Sarkar (1998; Gilbert and Sarkar 2000) makes a helpful distinction between two kinds of reductionism — genetic reductionism and physical reductionism. Physical reductionism sees physics as the most basic of the sciences and holds that all scientific explanations may (and should) eventually be recast in the terms of physics; genetic reductionism holds that ‘genes can explain all phenotypic features of an organism’ (Sarkar 1998: 174). These types of reductionism are not coextensive, though both champions and critics of reductionism tend to conflate these two varieties; but whereas physical reductionism is a thesis about relations between the sciences, genetic reductionism is a thesis about the role of genes in organismal development. Both varieties of reductionism may be problematic, though for different reasons. (Robert 2004, 136)

Robert, Jason Scott (2004) Embryology, Epigenesis, and Evolution: Taking Development Seriously. Cambridge Studies in Philosophy and Biology.

If one starts from the axiom-premise organisms are complex machines (which within certain limits I have no problem with) and the economy is merely a network of automata functioning like an “revealed preference” calculating machines one can rather easily develop mathematically tractable models. But these models hide the real world political and social dimensions of business and economics. Economies are more like organisms than machines. And more importantly one organism in particular, the human organism, including our ability to create other machines, systems, institutions, political and social structures, norms, and practices which allow us to modify physical, social, and even intellectual reality. Through our intelligent use of our minds and bodies we create other mechanisms, physical and social (living) relationships. These have their own levels of appropriate analysis. Social science, like biology, cannot be reduced to chemistry and physics. Neither can it be reduced to genetic algorithms or computational rules. Social science cannot be reduced to a natural science via some yet-to-be-discovered social mathematics. Human beings are not just more complex social insects. These are machine dreams or more to the point machine delusions rooted in a form of scientism.

THE GENE MYTH is not just a myth about genes. It is a story about the nature of the organism and the character of biological explanation. Inspired by our experience with machines, the story (in one of its versions) is narrated in a language of causal analysis, where some things make other things happen, and our investigation of a collection of parts, one by one, enables us to piece together a knowledge of the integrated whole. The continual elucidation of explanatory “mechanisms” has seemed to vindicate the story, supported further by promises of a better life for humans and a steady stream of stunning technical achievements in data gathering and manipulation of organisms. It is no wonder that the Human Genome Project aroused such high expectations.

But this story has now come to the end of its useful life. The loss of the gene at the head of a chain of causal mechanisms explaining the organism represents more than the loss of the master link in the chain. It exemplifies the failure of every link considered as machinelike. The seeming chaos of causal arrows now being documented under the heading of “gene regulation” repeats itself in every aspect of the cell. Researchers dutifully trying to follow arrows of causation end up chasing hares running in all directions. Is there any subdiscipline of molecular biology today where research has been reducing cellular processes to a more clearly defined set of causal relations instead of rendering them more ambiguous, more plastic and context dependent, and less mechanical? Consider a few examples. (Talbot 2013, 51) [And here the interesting part begins …]

Stephen L. Talbott (2013) The Myth of the Machine-Organism: From Genetic Mechanisms to Living Beings. In Genetic Explanations: Sense and Nonsense.

Epigenetic Algorithms

Mechanical metaphors have appealed to many philosophers who sought materialist explanations of life. The definitive work on this subject is T. S. Hall’s Ideas of Life and Matter (1969). Descartes, though a dualist, thought of animal bodies as automata that obeyed mechanical rules. Julien de la Mettrie applied stricter mechanistic principles to humans in L’Homme machine (1748). Clockwork and heat engine models were popular during the Industrial Revolution. Lamarck proposed hydraulic processes as causes of variation. In the late nineteenth century, the embryologists Wilhelm His and Wilhelm Roux theorized about developmental mechanics. However, as biochemical and then molecular biological information expanded, popular machine models were refuted, but it is not surprising that computers should have filled the gap. Algorithms that systematically provide instructions for a progressive sequence of events seem to be suitable analogues for epigenetic procedures. (Reid 2007: 263)

A common error in applying this analogy is the belief that the genetic code, or at least the total complement of an organism’s DNA contains the program for its own differential expression. In the computer age it is easy to fall into that metaphysical trap. However, in the computer age we should also know that algorithms are the creations of programmers. As Charles Babbage (1838) and Robert Chambers (1844) tried to tell us, the analogy is more relevant to creationism than evolutionism. At the risk of offending the sophisticates who have indulged me so far, I want to state the problems in the most simple terms. To me, that is a major goal of theoretical biology, rather than the conversion of life to mathematics. (Reid 2007: 263)

Reid, Robert G.B. (2007) Biological Emergences: Evolution by Natural Experiment. Vienna Series in Theoretical Biology.

More attention to the history of Science is needed, as much by scientists as by historians, and especially by biologists, and this means a deliberate attempt to understand the thoughts of the great masters of the past, to see in what circumstances or intellectual milieu their ideas were formed, where they took the wrong turning or stopped short on the right track. (R. A. Fisher, 1959)

Wilkins, Adam S. (2002) The Evolution of Developmental Pathways

Because the great controversies of the past often reach into modern science, many current arguments cannot be fully understood unless one understands their history. ERNST MAYR 1982, 1

McCloskey, Deirdre Nansen; Ziliak, Steve. The Cult of Statistical Significance (Economics, Cognition, And Society) (Kindle Locations 2036-2038). University of Michigan Press.

As the relations between development and evolution were explored in the last decades of the twentieth century, mutations in those genes that regulate development also assumed great significance. Regulatory (homeobox) genes were reported that affected whole sets of genes, and some paleontologists [and developmental geneticists, etc.] have emphasized that mutations in such regulatory genes result in large discontinuous evolutionary changes (a reshuffling of parts) and may be a macromechanism of evolution. But symbiosis–the inheritance of acquired genomes, wholes or parts–was trivialized or ignored by paleontologists. Gould himself regarded the symbiotic origin of mitochondria and chloroplasts as “entering the quirky and incidental side” of evolution. (Sapp 2003: 250-251)

Most of the great controversies and conceptual oppositions of the nineteenth century are still present at the beginning of the twenty-first century: religion and vitalism versus evolution and materialism, structuralism versus functionalism, reductionism versus holism, gradualism versus saltationism, selectionism versus nonadaptationism, the inheritance of acquired characteristics, and nurture versus nature. What has changed is not so much the nature of the ideas but the evidence supporting them and the intensity of the debates. (Sapp 2003: 267)

Jan Sapp (2003) Genesis: The Evolution of Biology

Conceptualizing Cells

We should all take seriously an assessment of biology made by the physicist David Bohm over 30 years ago (and universally ignored):

“It does seem odd … that just when physics is … moving away from mechanism, biology and psychology are moving closer to it. If the trend continues … scientists will be regarding living and intelligent beings as mechanical, while they suppose that inanimate matter is to complex and subtle to fit into the limited categories of mechanism.” [D. Bohm, “Some Remarks on the Notion of Order,” in C. H. Waddington, ed., Towards a Theoretical Biology: 2 Sketches. (Edinburgh: Edinburgh Press 1969), p. 18-40.]

The organism is not a machine! Machines are not made of parts that continually turn over and renew; the cell is. A machine is stable because its parts are strongly built and function reliably. The cell is stable for an entirely different reason: It is homeostatic. Perturbed, the cell automatically seeks to reconstitute its inherent pattern. Homeostasis and homeorhesis are basic to all living things, but not machines.

If not a machine, then what is the cell?

— Carl R. Woese (2005, 100) on Evolving Biological Organization

DECONSTRUCTING MARGINALIST MICROECONOMICS

What is the essence of homo economicus? Homo economicus is a man in search of pleasure. He is man who knows what he wants and how to get it. There are fixed limits on what homo economicus can obtain, but he is a master of getting the best that he can from within those limits. The term was first coined as a criticism. It would seem that when certain people in the nineteenth century read the famous economist and philosopher John Stuart Mill, they did not like what they found. They accused Mill of reducing the human being to nothing but a calculator of his immediate pleasures. They said that Mill had removed anything properly human from Man and replaced him instead with some sort of amoral robot [e.g., automaton]; this robot they called homo economicus (Persky 1995). (Pilkington 2016, 71)

Mill himself was quite explicit about what he was doing. He claimed that economics—which was then called ‘political economy’—was concerned only with certain specific facets of Man’s existence. It did not poach on the preserves of other moral disciplines but rather abstracted from them and reasoned as if they did not exist. Mill wrote:

[Political economy] does not treat of the whole of man’s nature as modified by the social state, nor of the whole conduct of man in society. It is concerned with him solely as a being who desires to possess wealth, and who is capable of judging of the comparative efficacy of means for obtaining that end. It predicts only such phenomena of the social state as take place in consequence of the pursuit of wealth. It makes entire abstraction of every other human passion or motive; except those which may be regarded as perpetually antagonizing principles to the desire of wealth, namely, aversion to labor, and desire of the present enjoyment of costly indulgences … Political economy considers mankind as occupied solely in acquiring and consuming wealth; and aims at showing what is the course of action into which mankind, living in a state of society, would be impelled, if that motive, except in the degree in which it is checked by the two perpetual counter-motives above adverted to, were absolute ruler of all their actions. (Mill 1844) (Pilkington 2016, 71-72)

What concerned those who criticised Mill’s homo economicus was that it highlighted some of what they considered to be the less seemly aspects of Man’s existence. This was the age of high morality, and Mill’s construction seemed to many to be against the morality of the day. This was also an age of mass wealth accumulation, and Mill’s construction probably showed up a certain truth that some were less than pleased to deal with as it ran contrary to what they considered good behavior. (Pilkington 2016, 72)

By the mid- to late twentieth century, mass consumption had become a way of life and contemporary morality was more accommodative to the homo economicus. Indeed, today he seems like a rather natural construction in an age where people constitute their lives through accumulation and consumption. He has also been given more precision. Today, following on from the work of the early marginalists, he is modelled using indifference curves and differential calculus. To a critic of the theory, it is less the morality that stands out as it is the image of Man that is put forward. Man is seen as a sort of automaton with fixed, ordered preferences [or “if-then” rules as envisioned by genetic algorithms], a vast capacity for information that would be the envy of even the most powerful of computers. Whereas yesteryear homo economicus seemed offensively amoral, today he seems offensively unrealistic. (Pilkington 2016, 72, bold added)

The fact of this matter cannot be overstated enough If we turn, for example, to the main macroeconomic model used by the European Central Bank at the time of writing, we find it populated with a plethora of homo economicus. In their key forecasting model which is supposed to represent the Eurozone economy, they write:

Each household h maximises its lifetime utility in a given period t by choosing purchases of the consumption good, Ch,t, purchases of the investment good, Ih,t. (Christoffel et. al. 2008, p. 11)

Thus they turn every household into a homo economicus and then lump these homo economicus together and spell out their exact behaviour in a series of equations. If the assumption that each household acts like a homo economicus can be shown to be nonsense, then the findings of the model will also be nonsense. This cannot be stressed enough: this assumption is at the absolute core of many ‘very serious’ theories; without it they literally cannot function. Yet if the construction can be shown to be false, and by that I mean if it can be shown not to be a reasonable approximation of the real object of study (economic agents), then the theories themselves must also be false and central banks can be shown to be wasting an awful lot of time and resources employing people to build such theories. (Pilkington 2016, 73)

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