If we want to Prioritise abstraction over metaphor, the concept of a System Boundary needs to be stripped of its metaphorical content. The concept of a Markov blanket delivers exactly that:
[T]]he notion of a Markov blanket allows one to define any System or structure in a way that distinguishes it from the Environment or milieu in which it resides. The Markov blanket plays the role of a statistical boundary that allows one to talk about a system per se.
The concept has been developed in statistics and machine learning, where
when one wants to infer a random variable with a set of variables, usually a subset is enough, and other variables are useless. Such a subset that contains all the useful information is called a Markov blanket.Wikipedia
When these variables represent specific states of systems which are causally connected to other states, we can transpose this into the following:
A Markov blanket is a set of states that separates the internal or intrinsic states of a [system] from extrinsic or external states.Palacios et al. (2020), 1
This means it is a set of boundary states that are causally connected to the “inside states” of a system as well as to the “outside states” it isolates them from – the states of whatever is causally ==connected to both inside and outside== (which is the topological definition of a System Boundary).
Importantly, when interactions between states are spatially dependent, as is the case for states pertaining to the physical description of biological organisms, this separation can be spatial in nature. Consequently, in this setting, a Markov blanket describes a spatial boundary.ibid.
The Markov blanket is central to the Free Energy Principle: it is the surface at which a system’s sensory and active states are defined, and across which free energy is computed.
Because The world is a hierarchy of systems, we can describe it as being structured by “Markov blankets all the way down”Friston (2019), 7 .
If we “carve up” reality at system boundaries, and these boundaries are objectively defined as Markov blankets, this carving up has an ontological character – it is about systems themselves, not just Models of them. This is a stronger claim than the one that systems are epistemologically defined “real patterns”.Dennett (1991). Cf. Causal Emergence for more on this. The ontological character allows us to objectively identify Missing Systems.
References
- Dennett (1991): “Real Patterns”
- Friston (2019): “A free energy principle for a particular physics”
- Palacios et al. (2020): “On Markov blankets and hierarchical self-organisation”
- WIkipedia: “Markov blanket”