First, given what a sea change fully autonomous vehicles are to the way we've been driving for 100 years, there's a threshold question about safety. AVs have a remarkably strong safety record. It's the top priority of every AV CEO I've ever met or worked with. The occasional software glitch or fender bender does deserve scrutiny, but such incidents receive lopsided attention and ought to be weighed against the tens of thousands of traffic deaths on U.S. roads each year caused by drunk, distracted or reckless humans. Second, critics say after all the hype and money spent, AVs aren't even on public roads or capable of serving passengers and businesses.

With ML (machine learning), algorithms rewrite themselves as the machine "learns" more and more about patient care. I've written about a recent case where IBM's Watson computer "read" a Japanese leukemia patient's medical records, genetic data, and 20 million journal articles on leukemia (all in around 10 minutes) and concluded that teams of doctors had misdiagnosed her illness and treated her with the wrong medications. Watson effectively, continually reprogrammed itself to analyze the patient's illness in ways no human had done.

Many people find recent advances in artificial intelligence (AI) quite alarming. Indeed, luminaries, ranging from Nobel laureate Stephen Hawking to technology pioneers Elon Musk and Bill Gates, have warned that artificial intelligence technology might be more dangerous to humankind than the atomic bomb. Oxford philosopher Nick Bostrum has argued that an "intelligence explosion" may lead to the extinction of humanity at the hands of rampant robots. These arguments distract us from the large and more imminent threat -- seismic loss of jobs, surging unemployment, and potentially calamitous social strife. This week, when the White House launches a sequence of workshops studying the future of AI, they should focus on the real dangers, not imaginary ones.