Specialisation

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A human being should be able to change a diaper, plan an invasion, butcher a hog, conn a ship, design a building, write a sonnet, balance accounts, build a wall, set a bone, comfort the dying, take orders, give orders, cooperate, act alone, solve equations, analyze a new problem, pitch manure, program a computer, cook a tasty meal, fight efficiently, die gallantly. Specialization is for insects.

Robert Heinlein

Universities bear some responsibility for its extinction. Classical Greece, Renaissance Italy and Victorian England all revered and rewarded generalists, for whom today universities have little or no space or patience. Enclosed departments in discrete spaces, with their own journals and jargons, are a legacy of lamentable, out-of-date ways of organising knowledge and work.

Felipe Fernández-Armesto

Since the time of Adam Smith it has been a truism that specialisation enhances productivity.

There is, it is said, no human alive who knows every step in the manufacturing process of even a humble pin.

Segmenting that process and assigning different components to specialists not only makes it possible, but improves it's quality by goosing the expertise each agent one brings to its specialised task. Just as a decathlete cannot expect to compete with event specialists, you can be sure the same generalist responsible for mining, ore extraction, metallurgy, manufacturing, quality control, book keeping, distribution, sales and marketing will not conduct any of these tasks awfully well, and certainly not as well, or quickly, as a specialist might.

But just as there is for the Laffer curve, there is a specialisation sweet spot. We know human beings are not instruction following automatons. The special skill is is there ability to narratise, hypothesise and imagine. Humans are problem solvers, not instruction-followers.

That sweet spot falls where an individual's expertise, imagination, and problem-solving abilities can be maximally concentrated: there is enough depth to to test and stretch them, but not so much width that they are pulled past breaking point.

We should specialise, but only to a point. That point is passed when when an agent is bored.

If a task can be sufficiently articulated and regularised as to be boring, it should be carried out by an agent that scores high on accuracy, speed and the boredom threshold, but low on curiosity, creativity and imagination.

There are such agents: we call them “machines”.

Converse: if a task cannot be automated, then back up to the point where it is sufficiently challenging, and the problems concentrated enough, to be demanding and requiring of expertise.

That this may involve greater cost is not the only consideration; there are hidden meta-costs — wastes, in fact — associated with segmentation too. There is a lateral cost to segmentation. Every handoff generates waste, requires supervision, involves superstructure which would not otherwise be there.

See also

• Silo