Understanding Regularities 1: Some examples

One problem with the regularities framework is that, like other frameworks, it is an interlocking set of conceptual intuitions and hypotheses that do not lead to an easy definition. It is almost OK to say that regularities are not definable but we know one when we see one. I don’t quite agree with that conclusion, but let us first see if we can agree about some phenomena being regularities, so that we can at least say that we know one when we see one. Here are a few examples of what I would call regularities:

  1. The size of an animal predicts the pitch of it’s voice. Mice squeak and lions roar and not vice versa
  2. Clouds are puffy while water is runny.
  3. More controversially, the size of an animal predicts how smart it is. A bacterium can never be as smart as a dophin.

These three examples are all related to each other though not in any obvious way. The underlying mechanisms for mice squeaking, clouds puffing and dolphins thinking are all different. Even the evolutionary histories are different. However, at a thermodynamic level, we can see that all of them have to do with how energy and information flow through the respective systems. Physicists talk about “universality” i.e., that the macroscopic properties of a system can often be independent of it’s microscopic origins. The regularity approach takes this one step further, that the regularities of a system are not only independent of the underlying mechanism or causal features, they are the real thing. Especially when it comes to biological processes we can hypothesize that it is regularities and their graspability that is being selected for in natural selection, not the underlying mechanism. I see this as a biologically grounded version of the hardware/software distinction well known in AI and cognitive science. Just as an earlier generation of theorists argued that the same software can be instantiated in different hardware, we can argue that the same regularity can be instantiated via different mechanisms while remaining the same.


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10 Responses to “Understanding Regularities 1: Some examples”

  1. Sartaj Says:

    When you say that it is regularities and their graspability that is being selected for in natural selection, what exactly do you mean? And how different is it from the biologists’ notion of natural selection operating upon features of behaviour and morphology?

  2. Rajesh Kasturirangan Says:

    It certainly includes features of behavior and morphology but would also included informational features such as depth perception, without necessarily selecting for a particular way of doing depth perception. The hypothesis is about the unit of selection, which I am saying could be the regularity itself, not underlying mechanisms.

  3. Sartaj Says:

    Just because it’s all so new, i’m trying to get a fix on the terminology.
    So depth perception is an informational feature, retrieved, say, by using using the differential projection onto the two retinas in bifocal animals, which works because the relation between the angles that objects subtend and their distance is a regularity. It is the underlying regularities that allow one to access the informational feature.
    Thus depth perception would be selected for, but i cannot think of how it can be stated in terms of a regularity being selected.

  4. Rajesh Kasturirangan Says:

    Note that you can get the same regularity, for distant objects any way, using two single eyed snapshots. A univocal animal can also recover the same regularity. It is the regularity that provides reliable info, not uni- or bi-focality.

  5. Sartaj Says:

    Let me try and put my question better.
    Depth perception is the feature being selected for. It is not a regularity. It can be achieved using one or more algorithms that operate on one or more regularities that exist in the world. Is that correct?
    How then is a regularity being selected for?

  6. Rajesh Kasturirangan Says:

    Hmmm. We need a slightly more precise language. Depth perception is the function being selected for. However it is the regularity connecting angles and distance that makes that function selectable. While this is not correct, think of Aristotles four causes. Regularities, roughly, are the formal cause. Function is the efficient cause. I am claiming that selection may operate on the efficient cause but that in turn requires the other causes, and in particular, the formal, regularities driven cause.

  7. Sartaj Says:

    Yes, that i would agree with. n we do need to have a more precise terminology.

  8. Narayanan Srinivasan Says:

    Just reading the first regularity example on pitch, human females have a higher pitch than males but presumably have a smaller size!!!

  9. Narayanan Srinivasan Says:

    On a separate note, for every (claimed) regularity, people may (will?) come up with an exception leading to the opposite claim. For an interesting take on this, please see the book Arguing and Thinking by the social psychologist Mike Billig.

  10. Rajesh Kasturirangan Says:

    It’s not an order of magnitude difference though, unlike mice and lions. I don’t think this analytic scheme works when the differences are that small.

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