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.

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 AI 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

AI 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 AI.

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 AI, 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.

Guest Profile

• Bio at University of California Berkeley
• Profile at International Telecommunication Union
• Stuart Russell on LinkedIn

His Work

• Stuart Russell on TED
• Stuart Russell on Google Scholar
• Artificial Intelligence: A Modern Approach (4th Edition)
• Human Compatible: Artificial Intelligence and the Problem of Control
• Do the Right Thing: Studies in Limited Rationality (Artificial Intelligence Series)
• The use of knowledge in analogy and induction (Research notes in artificial intelligence)