Education
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The JC’s amateur guide to systems theory™
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Education
/ˌɛdjʊˈkeɪʃᵊn/ (n.)
The process of equipping youth for the future by systematically indoctrinating them about the past.
Education as the ultimate finite game
We learn from an early age — which in itself is kind of meta — that education, as academic progress, is a time-bound linear process: methodology, not a corpus. It is the application of technique to materials in a bounded environment to yield a result. Results can be tabulated, ranked, compared, and suitable candidates for adult life triaged.
Our formal skills — adeptness at solving equations, or parsing Shakespeare — are examined, and our output reduced to a grade.
Educational institutions being the forges of youth, we acquire real world skills as a by-product — social relations, psychological resilience, tolerance of tedium and absurdity, rebellion against unreasonable authority, how get on, how to fight, how to run, self-knowledge and self-awareness — but even where they are part of the curriculum (as fine arts sports sometimes are) these are barely evaluated, and many of these skills are unintended consequences and system effects of a superstructure that is basically irrelevant to the children going through it.
To flourish in formal education is to comply: to be good at applying known techniques to provide correct answers to pre-solved problems. This is explicitly the case for sciences — no curriculum on the planet asks students to unify quantum mechanics and relativity — but also for the humanities where there in fact is not an answer. You are nonetheless expected to give examiners what they want. This proxy is the answer.
You have 45 minutes. Twenty-five marks are available. Preparing material any more deeply than can be generically examined in the time is pointless. Thus, exam and revision technique is as important — more important than substantial learning. (The wisdom that we should optimise our time and resources is a valuable by-product that we learn).
Formal education, then, as a programme of learning methods, and applying them systematically to achieve expected outcomes.
It is all rather algorithmic.
The best students are those who most wholeheartedly embrace their role as processor of algorithms. That are most alive to the idea there is no contingency, no no unknown, no risk that can withstand the diligent application of formal analysis. These students get the first class honours, the internships and the pick of the graduate recruitment.
Now, if your entire education has taught — rewarded — our brightest minds for thinking this way, should we expect them to abandon an approach that has served them so well when they leave education?
We are generating automatons, who are accustomed to excelling at this limited game, hoop.and onto it early: the earlier they did, the better they got at it, and the more fulsomely has their success being reinforced to them such that they emerge flush with certainty in their own enlightenment. It is all they have ever known common success at this limited, narrow game.
Is it any wonder that we address our professional work in the same manner by creating structures that solve known and pre constructed risks?
Imagine instead of a weekly risk steerco meeting which go through the same agenda points and looks at the same metrics and traffic lights, convening a weekly meeting where participants from all levels are asked to to highlight their five biggest concerns? Rather than aspiring to green traffic lights, actively search for red ones.