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There are easy questions and there are hard questions, and it isn’t always obvious which are which. Quite the contrary: we routinely confuse the one for the other, and that confusion is the source of all kinds of error and misery.
The questions we have to ask and answer when building super-computers and the internet and rockets to the moon, those are the easy questions. They’re easy because they deal with relatively simple systems. However complex these marvels of engineering seem, they are the product of simple rules — often a great many simple rules — rigorously applied in well-controlled settings. They may seem hard because most of us don’t understand them, because they require for their implementation specialized learning and sophisticated mathematical skills. But the answers to these questions are calculable and verifiable: the scientists and mathematicians and engineers who derive and apply those answers can be confident that their numbers are correct and that their rockets (computers, robots, bridges, etc.) will work as expected.
On the other hand, the truly hard questions offer no such systematic and precise solutions. That’s because they involve factors that are hard to measure, effects that are difficult to predict, and complex feed-back systems that sometimes produce large changes in results in response to small changes in variables. Reliably predicting the weather for more than a few days at a time requires solving hard problems, which is why we’re not very good at it. Most problems that involve the actions of groups of people are similarly hard to solve in any rigorous sense: however much we may understand human nature in the aggregate, individual humans will respond unpredictably. The tragic historical record of central planning is a testimony to the chaos of human choice and action, and of our inability to predict it.
Now here’s an ironic thing.
The easy questions have tended to come along late in our evolution, not least because we’ve made them up ourselves: nature never compelled us, after all, to invent the iPhone or send Voyager II to Neptune. We did those things because we wanted to, not because we had to.
In contrast, we started bumping up against the hard questions long before we invented rockets or algebra or the number zero — or even, most likely, before we tamed fire and made it our servant. Before all that technological progress could be made, we had to solve, however imperfectly, problems of social interaction, of exchanges of services, of political organization, of family and community. And so, through a process — through many processes — of trial and error, of false starts and failures and occasional successes, our ancestors came up with workable answers to many of the hard questions. Not perfect answers — these aren’t the kinds of problems that lend themselves to perfect answers, not for our ancestors nor for us — but adequate answers: answers they could live with until better answers could be found.
The rather unintuitive point of all this is that the hard questions are the least amenable to purely rational solutions and that’s good, because the tools of rationality, all the logic and philosophy and formalism we’ve brought to such a high level, weren’t available to us when we were forced as a species to address these hard questions. We (imperfectly) answered those questions and (imperfectly) solved those problems through a different process, one that relied on intuition and ritual and tradition and evolving human nature.
Unfortunately, our recent (that is, over the past few centuries) and spellbinding successes with easy questions tempt us to believe that we can improve upon, with the same confidence we bring to space travel and consumer electronics, the painstakingly evolved answers to the ancient, hard questions faced by the human animal. Worse, they tempt us to dismiss too readily those early discoveries in favor of shiny new theories that have yet to pass the only test the answers to most truly hard questions can face: the test of time.