Metaphysics in science, Part IV. When causation is complex, what is it? Real or metaphysical?

This series has dealt with what it means to be scientific but not metaphysical, whether in a sense science has not really abandoned its ages-long flirtation with ideas imposed on the world rather than the world determining our ideas.

In previous posts we dealt with metaphysical notions like 'the human genome' or 'the globin gene', which do not really imply the actual existence of Platonic ideals, and serve mainly as pragmatic guides for our understanding of the world and the practice of science.

We then addressed why, whether, and how failure of data to replicate a theory should lead us to abandon it.  If it doesn't, then the theory is in a way shown to be a Platonic ideal assumed to be true rather than the kind of empirical truth we supposedly are seeking in science.  We mentioned a couple of examples in which Darwin held to his theory, correctly believing the overall evidence overriding mistaken notions of genes, but also imposed his theory on data as in making what amounted to 'progressive' theories of evolution when he studied barnacles.

Then we asked why GWAS and related omics, that did not find the expected, and promised, high accounting for important diseases, has not led to an abandonment of the underlying theory about major-gene causation, and whether that showed that for whatever set of reasons, metaphysics was driving our material assessment of the world of genetics and evolution.  These are all real and, we think, important issues that are rarely addressed by scientists. 

However, there are other issues that are important and we'd like to comment on two of them.  They are complexity, and statistical causation.  Here, we discuss the first of these two issues. 

Complexity and emergence: what are they?
So far in this series, we've considered rather simple theories:  A gene exists.  It codes for protein or its regulation in cells.  Antibiotic resistance results from genetic variants rising in frequency if they help the organism surmount the lethal challenge.

We've seen that these don't really seem to pose any serious systematic or fundamental threat to the notion that we can express our understanding of  the world in such abstract terms.

But what about when the theory gets more complex, when, say, many different factors interact to contribute to a single net result?  The net result, like a building, is sometimes called an 'emergent' phenomenon relative to the contributing components (bricks and steel beams).  That is, enumerating the components, or even studying them even down to the level of the atom, won't tell you much at all about the building itself.  What shape will it take?  How many stories will it be?  (We could estimate that by counting the bricks and beams, yes, but that won't be very precise.)  What's it going to be used for?  Who will use it?  Will the roof leak? 

Let's apply this to disease genetics.  Let's say that diabetes is the building, and many different genes and environmental factors the bricks and mortar.  We can't easily go forward or backward from here -- we can't reliably predict diabetes from the genes, and we certainly can't predict future environments, nor can we retrodict genes or environment knowing someone has diabetes.  In this instance, what kind of truth is an emergent phenomenon, relative to a material theory of the world?  Is it metaphysical in any way that should concern us?

If the result can't be predicted from the components, then more is going on than a list of those components.  The net result may be given a name, but this becomes more metaphysical than physical in some causal senses.  It's causally not so strictly utilitarian in the way 'the globin gene' guides us to study the instances of globin genes in actual people.

If every case of diabetes is due to a different set of causal factors, working and interacting in different ways in each instance, then diabetes is a different kind of reality, a somewhat metaphysical notion that exists independent of its assumed ordinary causality.  These are not just abstract philosophical questions, but in fact underlie our decisions about how to approach causation.  When our assumptions are unstated, and we don't think about why we're asking the scientific questions we ask, and designing the studies we design, our understanding of complex traits can easily become ensnared by their complexity, and this all becomes even more problematic if we assume we're looking at a simple trait. Even iron-clad ideas about causation, or the most appropriate uses of metaphysical convenience, can lapse into metaphysical vapor.

These are things you have to think about to grasp them, perhaps.  At least,  we do! If every instance is causally different so that we cannot enumerate the causes (because, for example, we need large samples or replications to show that they are really causes), then the emergent thing verges on a metaphysical ideal:  the trait may seem real enough, in our heads, but causally elusive in the world.  It is an assumption that it is a causally unitary....what?  It is too easy to assume its reality and force that onto assuming that if we but have big enough studies, or whatnot, we will be able to treat it by the usual reductionist methods (enumerating its causal bricks), when that may not be its reality as far as the current scientific method is concerned.  That is the 'emergence' problem, and we're not very good at solving it.  Instead, we wish it away through metaphysical ideals.

One strongly problematic aspect of all of this is related to, but goes far beyond, complexity and arbitrary agreed-on working definitions.  It is how we view probabilistic 'causation', to which we turn next.