No longer a topic for science fiction, the power of artificial intelligence is already reshaping our lives in ways that were unimaginable just a couple decades ago.
AI goes well beyond self-driving cars, Facebook ads, and robots that can run obstacle courses. Your email client can respond to messages for you; your preferred music provider will customize your playlist; and Google Translate is improving by learning from its millions of users, rather than waiting around to be programmed. In the US, courts are even using AI-trained algorithms to decide the most effective sentences and parole conditions for offenders. (A troubling development, to be sure.)
It can all sound very scary. Keep in mind, though, that almost all of this progress on artificial intelligence is on the performance of specialized tasks, data collection, or predictive algorithms. The type of AI that is particularly important now is often called “machine learning.” This branch of AI includes powerful computer programs dedicated to solving specific problems, but these algorithms not to grow on their own and consider other kinds of problems to tackle. In other words, there is not even an inkling of “general intelligence” in the machine learning tools that are being developed at a dizzying pace around the world. The robot that jumps the hurdles will not stop and think about what the hurdles are made of. The computer that drives the car will not stop and question the ethics of allowing a crowd-skipper into the exit only lane at the last minute.