Why machine learning, not artificial intelligence, is the right way forward for data science

We bandy about the term "artificial intelligence," evoking ideas of creative machines anticipating our every whim, though the reality is more banal: "For the foreseeable future, computers will not be able to match humans in their ability to reason abstractly about real-world situations." This is from Michael I. Jordan, one of the foremost authorities on AI and machine learning, who wants us to get real about AI. "People are getting confused about the meaning of AI in discussions of technology trends--that there is some kind of intelligent thought in computers that is responsible for the progress and which is competing with humans. We don't have that, but people are talking as if we do," he noted in the IEEE Spectrum article. Instead, he wrote in an article for Harvard Data Science Review, we should be talking about ML and its possibilities to augment, not replace, human cognition. Jordan calls this "Intelligence Augmentation," and uses examples like search engines to showcase the possibilities for assisting humans with creative thought.