Whether truck drivers or marketing executives, all workers consider intelligence intrinsic to how they do their jobs. No wonder the rise of “artificial intelligence” is uniquely terrifying. From Stephen Hawking to Elon Musk, we are told almost daily our jobs will soon be done more cheaply by AI.
Yet AI is too amorphous a label to actually convey anything useful about what, precisely, it’s supposed to displace. Instead, think of it as a technology that does one thing particularly well: predictions. Such as, will that mark on the X-ray prove to be a tumor? Is the object in the road a paper bag or a child? Which headline will get the most readers to click on an article?
Treating prediction as an input into an economic process makes it much easier to map AI’s impact. History and economics show that when an input such as energy, communication or calculation becomes cheaper, we find many more uses for it. Some jobs become superfluous, but others more valuable, and brand new ones spring into existence. Why should AI be different?