Affrodances depend on the ecology, and the ecology evolves and changes - by definition. Here are some thoughts on how that happens, in a "dialectic loop" the progresses through various discjunctures, ending up in a "Web2 Network of communities of pratice" which is pretty similar to the place it started, certainly for early H. Sapiens - i.e. the embedding/ disembedding loops back, dialectically, to the next version of what it was before, from the earliest "web" of human society and culture to the recent "web2" of the global internet society. .......

The Connectivism JAM (macro-network 'course') riased interesting questions about the nature of knowledge and where it 'resides', and came to the conclusion that its all in the network - the 'between parts', i.e. in and amongst all the nodes (human, machine, inert, etc). I was trying to map out the big picture (as one does) of where all the bits and pieces are situated, and whether, as I suspected, there are radically different KINDS of domains in which knowledge is situated, captured, networked, etc.

The big picture came out like this ....

and the commentary came out like this ...

The Genealogy of Creating and Embedding Knowledge in CANs (Complex Adaptive Networks) and VANs (Virtual Adaptive Networks).

Knowledge: in broad terms, can be defined as the capacity for effective action.
This includes a wide range of subcategories: strategic alliances; contextual knowledge; procedural knowledge; ante-formal knowledge (in social networks – online and offline, this is knowledge that has not [yet] been formalised), as well as the ability to find, access, contribute to, and use knowledge and make virtual alliances, (aka connectivist or virtual adaptive network knowledge). This also includes, by definition, the ability to access information as required.

Knowledge Embedded in Humans
Knowledge is embedded in humans in a range of forms, and at a range of levels. This includes consciousness, (cerebral); tacit, subconscious, reflex ‘knowledge’ and even instinctual ‘knowledge’ at lower brain (‘cerebellar’) level; and skeleton-muscular ‘knowledge’ at subcranial levels.

It is probably useful to restrict ‘knowledge’ to acquired capacities (so no instincts or reflexes), but capacity for effective action, (as opposed to information) depends on your facility at many levels in the body, so drawing a dividing line somewhere up the spine, or at the base of the skull is going to be difficult if not impossible. The body is a network, not an assemblage of discrete and discontinuous parts.

Those aspects of our ‘capacity’ that are based on information at cellular level are easier to deal with, as although they are acquired within the evolution of the species (phylogenetically) it still seems to be very clear that they are not acquired at an individual (ontogenetic) level. Interesting though, DNA is the most basic material semiotic – the earliest radical, dis-embedding of material (the four proteins of DNA) from their function as material to function as codes, or switches – early micro-projections of power and capacity. Genes contain knowledge in the (metaphorical) sense that basic information is embedded in them which enables effective action. And it’s not static; it changes and adapts between generations, so in a critical evolutionary sense it’s re-programmable.

Social Semiotics
We still need to deal with knowledge which is acquired at a social level. The question is, how do make the leap to networks that are connected, but not physically contiguous, and certainly not physically continuous? And the answer is: semiotics, including a range of zoo-semiotics, which we will not deal with here.

So, the next radical disjuncture, or dis-embedding is the digital coding of sounds into phonemes (the basic sound elements of speech: vowels and consonants), which are combined into the basic elements of language, monemes, like ‘ma’, to which we ascribe meaning within the social use of words. This is based on the arbitrary-and-conventional nature of this linguistic ‘double articulation’.

Semiotic Machines
To carry the metaphor of embeddedness forward– in networks, machines, and networks of machines (and we will need to shift to nodes somewhere along the line, as the machine metaphor gets a bit clunky): The basic elements of language (words) are articulated into what for this exercise can be called ‘semiotic machines’, from indicative sentences to predicative sentences to more complex propositions to syllogisms to theorems to algorithms to texts and programmes to networks of programmes and so on.

There is another radical disjuncture, which is the disjuncture of ‘formalised’ knowledge, or ‘commodified’ knowledge, or ‘meta-semiotic’ knowledge. The terms are interchangeable. The point is that formalised knowledge is generated by stripping out the subject and context from semiotics, for the specific purpose of creating ‘tradable’ semiotic machines – which are, simply, semiotic algorithms that can in principle be transferred anywhere, and used by anyone, anywhere.

Positivist science, money, bureaucratic procedures, votes and ‘representatives’ in representative democracy (which might just be a subset of bureaucratic procedures), media texts, and, in line with networks / connectivism, the internet itself: the first meta-network, these are all examples of formalised knowledge in this sense

Knowledge Embedded in Machines
This emerges alongside semiotics, and its development is inseparable from developments in semiotics. It includes:

· Crafts, highly dependent on skills and energy embedded within, and sourced within, humans;
· Industrial powered machines, where the skills / knowledge becomes disembedded and re-embedded in the machine, and the power is ‘outsourced’;
· Factories which are systems of machines; programmed, re-programmable and smart machines and networks of machines, or networks of machines, programmes and networks themselves, in a network of nodes, which starts to resonate, conceptually, with the networks of nodes in humans, although there are still substantial differences in kind.
· JIT manufacturing, retailing, and a range of e-commerce activities, such as mortgage derivatives (!) in the global networked economy.

Re-embedded in Networks
Global networks, and global micro-networks (networks like the Connectivism course which are micro in size, but macro in reach) are where the human/ inanimate network in connectivism and in ANT comes into its own. What we have now is an (extraordinary) Web 2 iteration (Virtual Adaptive Networks, or VANs) of the CoP (or Complex Adaptive Networks – CANs) that humans and other primates have inhabited in the global ecology for some time.