Michael Jordan explains why today’s AI systems aren’t actually intelligent

CS Prof. Michael I. Jordan is the subject of an IEEE Spectrum article which describes his life, research, and philosophy.  A computer science pioneer, Jordan blended CS, statistics, and applied mathematics, to help transform unsupervised machine learning into a powerful algorithmic tool for solving problems in fields like natural language processing, computational biology, and signal processing.  He explains that machine learning is, in essence, a new field of engineering focused on the interface between people and technology.  The optimal goal of machine learning should not be artificial imitation of human thinking since that is something human beings can already do for themselves.  Instead, AI should be focused on helping humanity solve the problems that it has created.  “While the science-fiction discussions about AI and super intelligence are fun, they are a distraction,” Jordan says. “There’s not been enough focus on the real problem, which is building planetary-scale machine learning–based systems that actually work, deliver value to humans, and do not amplify inequities.