Welcome to a special members only edition of The Knowledge Project. This episode explores the world of artificial intelligence. Melanie Mitchell is the Davis Professor of Complexity at the Sante Fe Institute and the author or editor of six books including her latest, Artificial Intelligence: A Guide for Thinking Humans. Melanie and Shane discuss the roots of artificial intelligence, the difference between AI and machine learning, how it works, the key players, political implications and so much more.
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Here are a few highlights from the conversation:
When you teach your teenager how to drive, I don’t know if you’ve had that experience, but it’s quite frightening. But you don’t show them millions of hours of video of the road with everything labeled in it the way that we teach autonomous vehicles today. Your teenager presumably has some modicum of common sense, and you just take them out of the road and let them try things and hope that they don’t kill you and they learn from actually doing the task. So, this is something that we’d like machines to be able to do.
Common sense is something we take for granted. If you’re driving along the road and you see a little pile of snow in front of you, you know that you can just drive over it because you know what snow is like, you know it’s not going to break your car. Whereas if you see a giant pile of glass, broken glass, you don’t drive over it. Well, how do we know that? We know that because we have a very vast set of knowledge about the way the world works, about the basic way objects work, the basic the world operates, and machines don’t have that.
You put photos of yourself online and then companies can use that for all kinds of different reasons, or you give all kinds of information out. So should the companies be paying you because they’re making money off of your data? Maybe. Should you be able to tell them not to use your data? Yes, probably. But all of these things have kind of complex consequences, so we have to think through. So, I think it is a really complex field to think about. Who should own data? What should companies be allowed to do with data? Right now, it’s just the Wild West out there. They can almost do whatever they want, which is frightening.
