Too much time is wasted because of the assumption that methods already in existence will solve problems for which they were not designed; too many hypotheses and systems of thought in philosophy and elsewhere are based on the bizarre view that we, at this point in history, are in possession of the basic forms of understanding needed to comprehend absolutely anything. — Thomas Nagel, The View from Nowhere.

One way to think about the challenges we’re facing in our day-to-day and professional lives is to classify them based on our knowledge of our knowledge.

Put another, less mind-bending way: do we know how to solve it? And if so, do we know how we’re doing it? Can we explain everything in such exact detail so that even a machine can imitate our process, or are there blanks that have to be filled in by experience? This neatly categorizes any problem to one of four kinds.

The four kinds of problems: the known knowns, the known unknowns, the unknown knowns, and the unknown unknowns

The Known Knowns are the things we know how to solve and exactly how we’re solving them. These problems are reducible to their individual constituent parts and can be automated as factories, recipes, and algorithms. The solutions are straightforward, even if sometimes finicky and exacting. They lend themselves to mnemonical, atomic, modularized forms. They are what we hope to arrive at, so that we can give the keys to a well-oiled machine and continue with the more interesting parts of our lives.

The Known Unknowns are the things we know will forever be out of reach. These are the inherent limits, difficulties, and impossibilities of physical, mathematical, and computational reality — the Bekenstein bound, Gödel’s incompleteness theorems, and computational complexity separations are just some of the results that perpetually obstruct our way. We can only accept them and work around them.

The Unknown Knowns, or I know it when I see it, are the things we do know how to solve, but aren’t exactly sure how we’re doing so. These are problems of both high-level subjective and cultivated taste and low-level sensorimotor skills. (Hence the dangerous apple-bite economical polarization in which automation forces the comfortable center into becoming either a cog or a maverick).

There’s taste: picking the right song for the mood, the right word for a sentence, the right color for a painting. And sense: reading facial expressions, navigating in a packed crowd, deciding if a pause is a break for thought or a spa...

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