bohm2 said:
I'm a bit confused about semiosis. Does semiosis bring any new facts to bear or is it just a different way of looking at the known "facts" of neuroscience, biology, cognition, etc.?
In my view, you have to look at it as a whole framework of logic.
So people are generally taught to think about the world in a way that is non-systematic. If asked the question of why things happen, they will start to analyse using an interlocking set of assumptions that we generally call reductionism. The elements of this include atomism, mechanicalism, monism, locality, determinism. Cause is equated with material construction - parts stuck together make wholes. So explanation begins with the smallest, simplest, action or component.
This is a powerful and familiar way to look at the world. It really works. But - systems thinkers claim - it is not the whole of things. It is a too-simple view that gains efficiency at the expense of leaving out the full story. And this is what create problems with explanations - scientific, philosophical or otherwise - when you get towards the limit of things. When what you are seeking to explain is the whole.
So the systems approach seeks the expanded view. Like Aristotle argued, you need to at least include formal and final cause as part of the package of causes. You need to deal with development and process.
Systems science thus has a more complex model of causality. Principally, it sees cause as hierarchical. There is both the local and global (as a fundamental fact). So scale matters. Cause is divided into bottom-up construction and top-down constraint.
The other fundamental assumption is that reality is dynamic. Everything must arise as a process of development. So change is also real (not merely rearrangement).
We could call this the organic view, in contrast to the mechanical. But the point is that it is another way of modelling reality. And it both includes reductionism and contradicts it.
So it has a place for bottom-up construction, but then also says that the parts or atoms or degrees of freedom doing the construction are not fundamental. Instead, they in turn are being shaped into crisp being by a system's downward acting constraints. The parts are emergent rather than existent.
In this way, you can have the same material facts (the existence of atoms) but a different explanation of those facts (one says the fundamentally small just is...somehow, the other says smallness is ultimately created as the counterpart to largeness).
I haven't even mentioned semiosis yet. But semiosis was really the particular view of systems taken by CS Peirce, who emphasised certain aspects of systems logic (and neglected some others). His writings have become only recently fashionable and so the tag 'semiosis' has become a bit of a bandwagon among the current generation of scientists who are dabbling in the systems view.
The key thing that I mean to draw attention to by talking about semiosis and the epistemic cut is a yet a further dimension to the whole systems view. I just said the two principle elements of systems thinking are hierarchical causality and a developmental ontology. Well this is enough for simple complexity, but not complex complexity (as we know it from life and mind).
You also have the possibility of global constraints being locally constructed. Systems with some kind of memory can store information and make active choices. So as well as dynamicism we also have computationalism, as well as semantics we also have syntax. There are coding mechanisms like genes and words, neurons and membranes, that can be used to control the world of rate-tied dynamics.
Now, science already knows this of course. We build computers and use them all the time. We invent mathematical syntax. We long ago discovered genes and realized the difference speech made to human consciousness.
But regular science, based on a reductionist model of causality, cannot ground these facts in a common framework of logic. Lacking a systems view of complex complexity, all sorts of philosophical problems arise about how to define life and mind. Not to mention all the other regulars in philosophy forums, like the problem of freewill, the nature of maths, etc.
So semiosis is systems science as it gets to its most intricate. It provides a different framework for the same facts. But does it predict different facts?
Potentially it should. But it would first need to be made more mathematical - hierarchy theory is semi-mathematical at the moment. And also, many of the facts we have discovered are as a result of scientists using systems thinking intuitively (and presenting the results in terms of reductionist models). So we can say it has already worked in that sense.
But an example of applied systems thinking is Friston's Bayesian brain, which I've mentioned. There explicitly is a systems model of brain function. And it claims to account better for a whole range of facts than previous models. It proposes an actual probability process that can be measured experimentally.