Podcast: Can you teach a machine common sense?

Artificial intelligence has become such a big part of our lives, you'd be forgiven for losing count of the algorithms you interact with. But the AI powering your weather forecast, Instagram filter, or favorite Spotify playlist is a far cry from the hyper-intelligent thinking machines industry pioneers have been musing about for decades. Deep learning, the technology driving the current AI boom, can train machines to become masters at all sorts of tasks. But it can only learn only one at a time. And because most AI models train their skillset on thousands or millions of existing examples, they end up replicating patterns within historical data--including the many bad decisions people have made, like marginalizing people of color and women. Still, systems like the board-game champion AlphaZero and the increasingly convincing fake-text generator GPT-3 have stoked the flames of debate regarding when humans will create an artificial general intelligence--machines that can multitask, think, and reason for themselves. Beyond the answer to how we might develop technologies capable of common sense or self-improvement lies yet another question: who really benefits from the replication of human intelligence in an artificial mind? "Most of the value that's being generated by AI today is returning back to the billion dollar companies that already have a fantastical amount of resources at their disposal," says Karen Hao, MIT Technology Review's senior AI reporter and the writer of The Algorithm. "And we haven't really figured out how to convert that value or distribute that value to other people."