Teach kids to code; watch them cure cancer
People list plenty of reasons why kids should learn how computers work. They could automate repetitive tasks; they’d be empowered to create in all kinds of media; they’d learn powerful new problem solving approaches. That last point (so innocent seeming!) has gripped my imagination most thoroughly: a mastery of abstraction offers stupendous power in practically every endeavor.
But perhaps the most important tower of abstraction—one whose structure we scarcely understand despite its supremely personal importance—is rarely mentioned in this context: life.
Say we cure cancer. Hooray for us! But we’ll face other diseases, then still more after we’ve addressed those. We address the analogues in software (bugs, security holes) at a totally different pace from those of life. Even the attitude is different. Software engineers know their software has bugs—and that it probably always will—but the industry nevertheless accelerates and thrives because when issues crop up, they’re generally resolved quickly and decisively.
We can fix software bugs quickly because we (mostly) understand the systems we’re addressing at all relevant levels of emergent behavior. We’ve established that understanding through composable abstractions about which we can reason in isolation, and by employing tools which enable us to rapidly test conjectures and gather data.
Personalized medicine applies some of these principles to healthcare: when a patient’s bacterial population evolves a resistance to a drug, we should be able to rapidly study that resistance and produce an appropriately targeted treatment. For this end, we’ll need diagnostic and fabrication tools, yes; but more fundamentally, we’ll need medical understanding at the many levels of emergent phenomena between organic chemistry and the consequent symptoms we observe.
Software engineering could provide a powerful microworld for biological engineering. A generation of children steeped as much in abstraction as in language would become a generation of adults extraordinarily well-equipped to understand our biology—and therefore to manipulate it. It’s difficult to comprehend the reach of explosive growth in this field. How many more generations will die of old age?