When Google introduced its pay-per-click ad auction in 2002, what had started out as an idealistic quest for better search results became the basis of a hugely successful business. Fortunately, unlike other advertising business models, which can pit the interests of advertisers against the interests of users, pay-per-click aligns the interests of both.

Perhaps the most important question for machine learning, as for every new technology, though, is which problems we should choose to tackle in the first place. Jeremy Howard went on to cofound Enlitic, a company that is using machine learning to review diagnostic radiology images, as well as scanning many other kinds of clinical data to determine the likelihood and urgency of a problem that should be looked at more closely by a human doctor. Given that more than 300 million radiology images are taken each year in the United States alone, you can guess at the power of machine learning to bring down the cost and improve the quality of healthcare.