Over the past 25 years, major advances have been made in the development of machine learning, also referred to as "deep learning," a branch of artificial intelligence (AI) whereby computers are programmed to analyze large data sets and make inferences about new data. The capacities of deep learning machines to see and understand, listen and speak, read and write, and integrate information and make judgments are developing at amazing rates. Among other uses, deep learning algorithms are automating jobs done by humans at an ever-increasing rate. While we have grown accustomed to thinking that robotics would take over most manufacturing tasks, most of us have not begun to grapple with what machine learning advances mean for the professions such as law, medicine, and education. These developments have major implications for education and training at all levels. Bold new educational design research initiatives are needed to increase the odds that humans will prevail in the accelerating race between human learning and machine learning.