The Problem With Self-Driving Cars

3min Snip

00:00

Play full episode

Summary

Transcript

Episode notes

I think it's just a fundamental misunderstanding. I mean, you're talking about problems that even humans can't solve. One of the problems with AI is that it doesn't have that broad knowledge of the world. The biggest source of accidents and self-driving cars are people re-ending them. People expect cars to drive in a certain way. And these self- driving cars don't have enough common sense, if you will. So they're unpredictable. You know, you're not supposed to follow that close. But people do. It's got too much complexity around it to be too many trade-offs or uncertainty.

Computer Scientist and author Melanie Mitchell of Portland State University and the Santa Fe Institute talks about her book Artificial Intelligence with EconTalk host Russ Roberts. Mitchell explains where we are today in the world of artificial intelligence (AI) and where we might be going. Despite the hype and excitement surrounding AI, Mitchell argues that much of what is called "learning" and "intelligence" when done by machines is not analogous to human capabilities. The capabilities of machines are highly limited to explicit, narrow tasks with little transfer to similar but different challenges. Along the way, Mitchell explains some of the techniques used in AI and how progress has been made in many areas.