Machine learning computer systems, which get better with experience, are poised to transform the economy much as steam engines and electricity have in the past. They can outperform people in a number of tasks, though they are unlikely to replace people in all jobs. So say Carnegie Mellon University’s Tom Mitchell and MIT’s Erik Brynjolfsson in a Policy Forum commentary to be published in the Dec. 22 edition of the journal Science. Mitchell, who founded the world’s first Machine Learning Department at CMU, and Brynjolfsson, director of the MIT Initiative on the Digital Economy in the Sloan School of Management, describe 21 criteria to evaluate whether a task or a job is amenable to machine learning (ML). “Although the economic effects of ML are relatively limited today, and we are not facing the imminent ‘end of work’ as is sometimes proclaimed, the implications for the economy and the workforce going forward are profound,” they write. The skills people choose to develo...