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THE CURRENT OPTIMIZATION

April 6th, 2022

What does traditional education optimize for? Traditional education has rightly come under a lot of fire and by many metrics education, at least in the West, is falling in quality and yield.

 

For a moment, let’s leave that question hanging, like an ominous cloud over a larger discussion of optimization in general. Good entry points to start thinking about this is to wonder what you are currently optimized for? Or what  systems in your life are being optimized? It’s a very valuable question to ask: am I optimizing for the wrong thing?

 

This kind of question helps protect against the sunk-cost fallacy: when we keep at something even when we should stop and switch gears, like waiting in a grocery line that isn’t moving as fast as the one next to it simply because we’ve invested several dozen seconds standing right where we are. There’s inertia in all things, not just physical things at motion or at rest, but with emotions and patterns of thought. A thought or behavior continually invoked is likely to be invoked again, it’s the law of habit, but good questions like “am I optimizing for the wrong thing?” help break this law for the better.

 

One principle that can be used to guide our focus of optimization is that the perfect is the enemy of the good. Optimizing for a problem that may never arise is a waste of time if we don’t do the work required to actually be awarded with that problem. An decent example is with app development. Optimizing for millions of users before having millions of users might sound very smart, but if it comes at the cost of never actually releasing an MVP (minimum viable product) then all that optimization was pointless.

 

Some things do benefit from thoughts of optimizing for the far future, like: I want to have as few regrets as possible when I’m very old. This sort of optimization - while invoking the far future - has a direct impact on how we respond on a daily basis to opportunities and chances we want to take.  Strangely, it’s optimizing for a very local circumstance: will I regret doing (or not doing) this current thing? 

 

The same sort of interplay can be repackaged and used to evaluate the situation for app development: will I regret optimizing for millions of users if I never even launch this product? Well of course. Or put another way, compare that question to this one: will I regret that I didn’t optimize for millions of users when I have millions of users? Well, maybe, but that’s also a fantastic problem to have - it’s the ultimate confirmation that something of real value has actually been produced.

 

So it turns out that we can have very long range goals that help us optimize for the right thing in any given moment. But it’s important to recognize that there might be correct order. Optimizing for no regrets can lead to a life of whimsy with no solid consistent commitments, and that in turn can become the regret: I should have committed to something and stuck with it! While all the while I was trying to live life without regret! Suddenly, the question of how to optimize for minimal regret gains a troubling amount of nuance: can we regret both paths? The scary truth is that the answer is ‘yes’.  Why? Because we can’t A/B test our life. We can’t see if a life of whimsy might lead to accidental fame and fortune but horrible personal relationships? And we can’t see that a consistent and boring area of focus might lead to a warm, stable, and loving family life.

 

The task of what to optimize for becomes fractal: Optimize for the long term, the mid term, the short term, and now. Answer all of these questions simultaneously, weight the answers, and most importantly: GO!

 

This is far from an easy task, which is what makes life both tragically difficult and quite fun and surprising, because our own personal algorithm for summing that equation is constantly shifting based on new information, opportunities and ideas.

 

Traditional education attempts (rather poorly) to cast a very wide net in terms of topics to be aware of. The focus of education is nouns. These are the things you need to know about and understand. The chief underlying problem with this approach is that life isn’t really a noun, it’s a verb: we live. Which means we need to know how to do things, and everything we do or end up doing can be optimized. A master of a craft is someone who has simply optimized their performance in that craft to an exceptionally high degree. Someone who has never committed very long to anything might not be a master in anything, but they may have optimized for fast initial learning, deriving subtle mental models that allow for quick initial optimization in any field. 

 

Which one does school point more toward? Well, considering grades are always a subtraction from a perfect score, school expects mastery. But it’s not even mastery in doing anything in particular, except perhaps regurgitation. Maybe writing and math translate to active verbs, but for the most part regurgitation goes a lot farther than creative exploration of these acts. School optimizes for knowing the noun as opposed to enacting the verb. What’s fascinating is that kids just don’t optimize well for this particular end. And yet they can concentrate for hours, days on end getting good at a video game. What’s the primary difference? A video game is a verb: you optimize for being able to do a particular thing, which is far more dynamic and challenging than any given topic that is best categorized as a collection of nouns. Math in school is boring, but millions of people spend hours every day playing sudoku. Why? Math classes require regurgitation with slight variation, while sudoku is a game that we can have fun optimizing for.

 

Life is a series of complex and dynamic problems: what best helps us solve these problems? A heap of nouns, or active skills? The answer is obvious, but hopefully it’s also intuitive, and points to potential solutions to help optimize the way we educate our children and ourselves. Will your life be a static topic?  Or is it time to change because the current thing requires a new optimization.


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Podcast Ep. 1212: The Current Optimization

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