For years, both the media and the business world have been captivated by the seemingly breathtaking pace of progress in artificial intelligence. It’s been 21 years since Deep Blue beat Kasparov, and more than 7 years since Watson mopped the floor with Ken Jennings and Brad Rutter on Jeopardy. The string of impressive advances has only seemed to accelerate since then, from the increasing availability of autonomous features in vehicles to rapid improvements in computer translation and promised breakthroughs in medicine and law. The notion that AI is going to revolutionize every aspect our lives took on the characteristics of gospel in business and tech journals.
But another trend has been slowly building in the background–namely, instances where AI has failed (sometimes quite spectacularly) to live up to its billing. In 2016, some companies were predicting that fully autonomous cars would be available within 4 years. Today, I get the sense that if you asked most watchers of the industry to give an over/under on whether fully autonomous vehicles will be on the road within 4 years, many-to-most would take the “over” in a heartbeat. This is in part due to regulatory hurdles, no doubt, but a substantial part of it is also that the technology just isn’t “there” yet, particularly given the need to integrate AVs into a transportation system dominated by unpredictable human drivers. The early returns on a widely-touted promise of an AI-powered revolution in cancer treatment are no better.
These are not the first time examples of technology failing to live up to its hype, of course. AI itself has gone through several hype cycles, with “AI winters” bludgeoning the AI industry and all but ending funding for AI research in both the mid-1970s and late 1980s. In each instance, the winters were preceded by periods of overheated investment in the AI industry and overheated predictions about the arrival of human-level intelligence.