Why are those leading adopters so far ahead -- and what can others learn from them? MIT Machine Intelligence for Manufacturing and Operations (MIMO) and McKinsey and Company have the answer, revealed in a first-of-its-kind Harvard Business Review article. The piece chronicles how MIMO and McKinsey partnered for a sweeping 100-company survey to explain how high-performing companies successfully wield machine learning technologies (and where others could improve). Created by the MIT Leaders for Global Operations (LGO) program, MIMO is a research and educational program designed to boost industrial competitiveness by accelerating machine intelligence's deployment and understanding. The goal is to "find the shortest path from data to impact," says managing director Bruce Lawler SM '92.

A panel of academic and industrial thinkers has looked ahead to 2030 to forecast how advances in artificial intelligence (AI) might affect life in a typical North American city - in areas as diverse as transportation, health care and education--and to spur discussion about how to ensure the safe, fair and beneficial development of these rapidly emerging technologies. Titled "Artificial Intelligence and Life in 2030," this year-long investigation is the first product of the One Hundred Year Study on Artificial Intelligence (AI100), an ongoing project hosted by Stanford to inform societal deliberation and provide guidance on the ethical development of smart software, sensors and machines. "We believe specialized AI applications will become both increasingly common and more useful by 2030, improving our economy and quality of life," said Peter Stone, a computer scientist at the University of Texas at Austin and chair of the 17-member panel of international experts. "But this technology will also create profound challenges, affecting jobs and incomes and other issues that we should begin addressing now to ensure that the benefits of AI are broadly shared." The new report traces its roots to a 2009 study that brought AI scientists together in a process of introspection that became ongoing in 2014, when Eric and Mary Horvitz created the AI100 endowment through Stanford.