To create good workers, education systems put a premium on compliancy and rote memorization of basic knowledge—excellent qualities in an industrial worker.
To the extent a school is like a factory, students who inquire about “the way things are” could be seen as insubordinate
Logically, as we move from an industrial society to more of an entrepreneurial one, it makes sense that we would want to trade in the factory/obedience model of schooling for more of a questioning model. But as the world changed and the workplace changed with it, the old educational model hasn’t evolved much—and for the most part hasn’t adapted to the modern economy’s need for more creative, independent-thinking ‘workers’
This is consistent with the views on averagarianism, and the separateness of thinkers and managers (Taylorism) nicely narrated by Todd Rose, and others (most recently by Dingen, in a book I am about to start).
If you can’t articulate your ethics then someone else would. Design for agency, emotional articulation and liminal leadership don’t only apply to the collective (company, team) level, but also to the self.
Driving your own bus might have been enough in the 90’s, but today’s complexion of intricate highways filled with self driving trucks needs voices of conviction. Being able to navigate, pursue and explain decisions is a key to sanity, self fulfillment and effective work.
When utilitarian efficient systems are free, the value comes from everything else: ethics, human connection, branding, context, altruism.
Again and again, this is a question of not what you do, but who you are. Coaching (as a mean to understand the decisions you make) might very well have exponential return for your company, employees and market offering (much more so than the incrementalism of another sprint).
And yet this is the job often assigned to P values: a measure of how surprising a result is, given assumptions about an experiment, including that no effect exists. Whether a P value falls above or below an arbitrary threshold demarcating ‘statistical significance’ (such as 0.05) decides whether hypotheses are accepted, papers are published and products are brought to market. But using P values as the sole arbiter of what to accept as truth can also mean that some analyses are biased, some false positives are overhyped and some genuine effects are overlooked.