Episode 40: Stuart Russell

Listen to Episode on:

 
 

Watch the Unabridged Interview:

Order Books:

Deep Dive into AI: Ethics, Design, and Human Compatibility

Popular culture often portrays artificial intelligence (AI) as a super-powerful, ominous threat to jobs, lives, and ultimately humanity. As AI is moving out of the lab into the real world, how can we harness its potential for good? In this episode, Stuart Russell talks about how to avoid this impending problem, a topic he covers in his book Human Compatible.

Listen as he takes us on a deep dive into the history of AI  and how a new foundation can be used to develop machines that are sensitive to human preferences.

Episode Quotes:

Should computer science students be seriously concerned about ethics?

“Computer science students do need to understand more than their technical discipline. And that's what one would expect for a discipline that starts to impact the real world. I think there's more to it. Because you know, the products of civil engineering, for example, the bridges, don't think and participate and act in our democracy the way some AI systems may be starting to do. So, in the long run, if we are making things that function as if they were minds — I'm not going to say that they are minds, but functioning as if they were minds. Then you're going to bring in all the considerations.”

How long ago was it that experts began seriously thinking about AI's practical applications, from the time the first computer was invented by Charles Babbage?

“So, the real impetus for A.I. was the development of the computer in the second world war, which arose from Turing's mathematical work in his 1936 paper. And Turing himself, as soon as he figured out that you could actually start computing, and he understood this idea of universal computation, he wanted to build intelligent machines.”

Misconceptions about A.I. as a practice

“A.I. is a problem, not a technology. So, it can't fail. Right. It can just take longer to solve, you know? And you wouldn't say physics failed because of confusion. So people have always had this strange idea, in the outside world and the media, that AI is a technology. So, nowadays, people often confuse deep learning and A.I.”

What happens every time there’s a new discovery in A.I.?

“Every time, there's a small gain in function in one branch of A.I., because of the generality of these techniques, there's a big explosion in economic interest. As long as people see all kinds of things in the real world that they can apply them to, that will continue to happen. Deep learning is just one step. There'll be another half dozen such steps. And each of those will probably increase the scope of applications by a factor of 10.”

Show Links:

Guest's Profile:

His Work:

Previous
Previous

Episode 41: Simon Lack

Next
Next

Episode 39: Paul Ehrlich