This is, it seems to me, a general principle: you get bored with something not when you have exhausted its repertoire of behaviour, but when you have mapped out the limits of the space that contains its behaviour.
The Danger of Reductionism and the Fear of Simplification
Results without causes are much more impressive (Sherlock Holmes, The Stockbroker’s Clerk).
The practice of analysing complex phenomena by breaking them down into their individual parts risks the interpretation that these phenomena are ‘nothing but’ the sum of those parts. This reductionist interpretation is often signalled by the use of words such as ‘just’, ‘only’, ‘merely’, or ‘simply’. Grammatically, these words function as mood adjuncts of intensity, specifically within the category of counterexpectancy and limiting. Their meaning is essentially: “contrary to expectations, the phenomenon is limited to x”.
When these terms are applied to construals of humanity, they evoke a fear that, despite any theoretical or emotional assertions, humans are limited to their anatomical, chemical, or atomic components. As argued earlier, the constituency model (which breaks down systems into parts) is limited by its static nature and is insufficient for understanding dynamic systems—systems that emerge through interaction and cannot be fully understood merely by looking at their parts.
The covert assumption driving this misinterpretation is the false belief that lower levels of organisation (e.g., biological or chemical components) are somehow more “real” or “true” than higher levels of organisation (such as psychological or social phenomena). This view is held both by proponents and opponents of reductionist thinking. However, lower-level models are not more “real”. Like all models, they are semiotic representations, distinct from the phenomena they aim to describe.
Lower-level models are more self-consistent and reliable simply because they describe simpler systems, which are easier to represent and require less time to evolve in the history of modelling.
This fear of simplification is closely tied to the concern that any model of a phenomenon reduces it to that explanation. This confusion between the phenomenon itself and the model of it leads to the erroneous belief that reducing ignorance is equivalent to reducing value. In this framework, the positive value of a model is often seen as linked to the mystery it maintains.