How incredible is the photo above? A flock of birds that, while individual in their own right, come together to think like a single organism, which coincidentally also looks like a bird! Individual parts that seem to have no leader; they lack a hierarchy. This is the beauty of emergence and it’s everywhere in nature. Embedded deeply as a first principle, we find it across many sectors and you’ll come to understand why this bottom-up approach to complex organizations is a paradigm shift.
Emergence is the phenomenon where seemingly simple, dumb bits manage to coalesce in a way where they work in tandem with many parts. The simpler way to phrase it is: the whole is greater than the sum of its parts. These are my definitions of course and how I interpret them, so please do not attack me with any formal definitions that may undercut the central message I wish to get across: that when in large numbers, novel properties emerge from a lower order of complexity, thereby creating a concept of a sentient whole.
Artist: Georges Seurat
Like in the painting above, we can see individual components that serve a purpose. A dot here is intended to be a mustache and you can tell because of its color while a dot there could be part of their cheek. An abrupt change in the color could indicate that perhaps this is the divergence between a mustache and a cheek and so knowing what dot is next to a specific dot determines its purpose locally. You’ll find this theme often with emergence, its the locality of a bit that gives it instructions. We could take a step back and observe more of these dots and their locality to make sense of what this is; we can, in a sense, abstract a face in all of this. A man with a mustache. Embryos grow in the same manner. While they understand their overall telos (growing into a human), the cell must learn from its local cells what it must manifest. It could be an eye, or an arm; it all depends on what lies next to it. Your spatial orientation matters a lot.
Emergence, at its heart, is the phenomenon that occurs from the continual abstraction of higher orders of complexity. The higher we go up, the more intelligent this aggregation of parts seem. The concept of emergence states that the bits of data need to be plentiful in order for it to take a more unified, organismic identity. With lesser nodes, they still function individually, but as they grow in number, they communicate in a more local manner.
What do I mean by local? Many hierarchies operate in very much that: a top-down approach. A bottom-up approach would imply that there is no chain of command and that orders are not given. Instead, actions are executed because of simple rules that occur at the local level; in other words it’s what your neighbors do that influences how you respond. Like a game of telephone, except that the message doesn’t get garbled up along the way since what’s communicated is simple and binary. In nature we see fireflies do this; it’s what results in synchrony.
Credit: https://blog.colony.io/the-future-of-work-cf99211e7ac4/
Ants follow this process as well, using pheromones and the depth of the smell to determine various pieces of information they use in foraging food. They rely on the ant before them to determine what action to take and the more ants they meet, the more information they possess.
So if individual parts can be quite dumb but more sentient when in numbers, what makes that so? It's the network; the connections that are made between them. The relationships and interactions amongst the parts are what make them intelligent. Which begs the question; is it the number of permutations that equates to the whole being more sentient for one group as opposed to another?
Well, let’s expand on that in a different way. While the number of connections can make the network more viable, it is the higher the layer of abstraction that allows this network to become intelligent, or seemingly sentient. The organism is just that, the highest abstraction of the many individual components, and Ken Wilber always alluded to this by insinuating that various social groups in nature operate under hologarchies rather than hierarchies.
When it comes to mathematics, one of the biggest breakthroughs that resulted in a paradigm shift was understanding the relationship between polynomial functions and the shapes they produce. With the introduction of vectors, we add more complexity than the mind can fathom, extra dimensions that took our core Euclidean space and caused it to fold in on itself. Adding this extra dimension, in my opinion, adds another layer of abstraction. Which makes sense, once Einstein introduced a 4th spatial dimension, we had to abstract out how we though about geometry.
So, we have particular nodes that, when connected, add dimensions. We can try and abstract those out but after a certain number of dimensions, we cannot fathom what those dimensions will look like, so we use vectors. Vectors are helpful and if we apply mathematical modeling to, say a simulation of 1,000 ants and how they interact, we would have a 1,000-dimension model that might seem daunting, but with simple binary rules to follow (just as the ants do), we’ll find co-emergence taking place. How lovely!