If AI's So Smart, Why Can't It Grasp Cause and Effect?

A self-driving car hurtling along the highway and weaving through traffic has less understanding of what might cause an accident than a child who's just learning to walk. A new experiment shows how difficult it is for even the best artificial intelligence systems to grasp rudimentary physics and cause and effect. It also offers a path for building AI systems that can learn why things happen. The experiment was designed "to push beyond just pattern recognition," says Josh Tenenbaum, a professor at MIT's Center for Brains Minds & Machines, who led the work. "Big tech companies would love to have systems that can do this kind of thing."