As usual, I will try to efficiently review the key points and then add some reflections on what the chapter made me think about.
System
A system is a set of components that arranged in some relation to one another, where the relations have implications for the activity of the components. A heap of something is not a system; there are pieces, and they are arranged relative to one another, but the properties of those pieces don't depend on the relations. A system entails that at least some of the components are affected by at least some of the other components.This is a key figure to keep in mind throughout this book; it's the Composition, Environment, Structure (CES) model that describes the minimum set of elements required to specify a system
The system being studied is the part in the middle. It is made of components (the various checkered shapes), and at least some of this internal degrees of freedom are connected to (stand in some relation to) some other internal degrees of freedom (the thin arrows). The gray surround is the environment of the system; these are external degrees of freedom that can affect or be affected by the system. Again, at least some of the internal components stand in some relation to at least some of the external degrees of freedom (the thick arrows). Every system defines (picks out) an environment; no system, no environment, and environments are not systems (at least when considered from the point of view of the system). This set-up also immediately implies some kind of boundary - something that makes there be an 'inside' and an 'outside' of the system. Our job as scientists of perception is to correctly specify the system we are studying. We face all kinds of problems; we might only be able to observe part of the system, and different observers (scientists) might have different views of the system. This means what properties we think the system needs to do what it does might vary, or be flat out wrong. There are two basic consequences to worry about. First, thinking that something the system does is is something that the sub-system we are observing does (e.g. thinking cognition is an achievement of the nervous system, rather than the organism-in-context). Second, analysing the system into parts and processes according to the wrong procedure (e.g. disassembling a bike with a wrench and an angle grinder both produce parts, but only the former produces ontologically sensible pieces).
Intentional
Perception and action systems are intentional, specifically they exhibit aboutness. We therefore need to have a correct understanding of what those systems are about - what are the intentional objects of perception and action, and how does the system get to be about them?Epistemic
Perception and action systems have a very particular intentionality; they know about things, specifically their environments. The challenge we face is to identify what kind of material system can implement this kind of intentionality. The two most recent hypotheses are systems that compute over discrete symbols, and network systems engaged in parallel distributed processing of graded signals in a specific dynamical process.Turvey then just plants a flag for the future and says neither of these work, and we will need to move towards complexity science for our answer.
