Explore the current limitations of artificial intelligence and the possibility of creating human-compatible technology.

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In the coming years, artificial intelligence is probably going to change your life— and likely the entire world. But people have a hard time agreeing on exactly how AI will affect our society. Can we build AI systems that help us fix the world? Or are we doomed to a robotic takeover? Explore the limitations of artificial intelligence and the possibility of creating human-compatible technology.

This video is based on interview excerpts from the Radio Davos Podcast. The episode is called, “The promises and perils of AI - Stuart Russell on Radio Davos”. 
Listen to the full episode here: https://www.weforum.org/agenda/2022/01/artificial-intelligence-stuart-russell-radio-davos

Directed by Christoph Sarow, AIM Creative Studios.

This video made possible in collaboration with World Economic Forum
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In the coming years, artificial intelligence is probably going to change your life, and likely the entire world.

But people have a hard time agreeing on exactly how.

The following are excerpts from a World Economic Forum interview where renowned computer science professor and AI expert Stuart Russell helps separate the sense from the nonsense.

When you ask a human to fetch you a cup of coffee, you don't mean this should be their life's mission and nothing else in the universe matters.

Even if they have to kill everybody else in Starbucks to get you the coffee before it closes, they should do that.

You mean all the other things that we mutually care about, they should factor into your behavior as well.

And the problem with the way we build AI systems now is we give them a fixed objective, right?

The algorithms require us to specify everything in the objective.

And if you say, you know, can we fix the acidification of the oceans?

Yeah, you could have a catalytic reaction that does that extremely efficiently, but, you know, consumes a quarter of the oxygen in the atmosphere, which would apparently cause us to die fairly slowly and unpleasantly over the course of several hours.

You might say, okay, well, just be more careful about specifying the objective.

And then of course, some side effect of the reaction in the ocean poisons all the fish.

Okay, well, I meant don't kill the fish either.

Okay, don't do anything that's going to cause all the seaweed to die and on and on and on, right?

And the reason that we don't have to do that with humans is that humans often know that they don't know all the things that we care about.

If you ask a human to get you a cup of coffee, you know, and you happen to be in the Hotel Georges Sank in Paris, where the coffee is, I think, 13 euros a cup, it's entirely reasonable to come back and say, well, it's 13 euros.

Are you sure you want to go next door and, you know, get 1.

And It's a perfectly normal thing for a person to do right to ask you know I'm gonna repaint your house is it okay if I take off the drain pipes and then put them back.

We don't think of this as a terribly sophisticated capability but AI systems don't have it because the way we build them now, they have to know the full objective.

If we build systems that know that they don't know what the objective is, then they start to exhibit these behaviors, like asking permission before getting rid of all the options in the atmosphere.

In all these senses, control over the AI system comes from the machine's uncertainty about what the true objective is.

It's when you build machines that believe with certainty that they have the objective, that's when you get the sort of psychopathic behavior.

And I think we see the same thing in humans.

What happens when general purpose AI hits the real economy?

Amazingly, Aristotle actually has a passage where he says, look, if we had fully automated weaving machines and plectrums that could pluck the lyre and produce music without any humans, then we wouldn't need any workers.

That idea, which I think it was Keynes who called it technological unemployment in 1930, is very obvious to people, right?

They think, yeah, of course, if the machine does the work, then I'm going to be unemployed.

If you think about the warehouses that companies are currently operating for e-commerce, they are half automated.

The way it works is that on old way how's where you've got tons of stuff piled up all over the place and humans go and rummage around and then bring it back and send it off.

There's a robot who goes and gets the shelving unit that contains the thing that you need, but the human has to pick the object out of the bin or off the shelf, because that's still too difficult.

But you know, at the same time, if you make a robot that is accurate enough to be able to pick pretty much any object, and there's a very wide variety of objects that you can buy.

That would, at a stroke, eliminate 3 or 4000000 jobs.

Forster wrote where everyone is entirely machine dependent.

The story is really about the fact that if you hand over the management of your civilization to machines, you then lose the incentive to understand it yourself or to teach the next generation how to understand it.

You can see War Lee actually is a modern version where everyone is enfeebled and infantilized by the machine.

And that hasn't been possible up to now, right?

We put a lot of our civilization into books, but the books can't run it for us.

And so we always have to teach the next generation.

If you work it out, it's about a trillion person years of teaching and learning and an unbroken chain that goes back tens of thousands of generations.

And I think that's something we have to understand as AI moves forward.

The actual date of arrival of general purpose AI, you're not going to be able to pinpoint, right?

It's also not the case that it's all or nothing.

So with every advance in AI, it significantly expands the range of tasks.

So in that sense, I think most experts say by the end of the century, we're very, very likely to have general purpose AI.

I'm a little more on the conservative side.

I think the problem is harder than we think.

I like what John McCarthy, who was 1 of the founders of AI, When he was asked this question, he said, well, somewhere between 500 and 500 years, and we're going to need, I think, several Einsteins to make it happen.

But how will the economy change in the meantime?

Watch this video to hear economist Kate Raworth explain why growth is not always a good thing, or continue to expand your understanding of economics on the World Economic Forum's YouTube channel.


Speaker 0: In the coming years, artificial intelligence is probably going to change your life, and likely the entire world. But people have a hard time agreeing on exactly how. The following are excerpts from a World Economic Forum interview where renowned computer science professor and AI expert Stuart Russell helps separate the sense from the nonsense.

Speaker 1: As the objective to an AI system. When you ask a human to fetch you a cup of coffee, you don't mean this should be their life's mission and nothing else in the universe matters. Even if they have to kill everybody else in Starbucks to get you the coffee before it closes, they should do that. No, that's not what you mean. You mean all the other things that we mutually care about, they should factor into your behavior as well.

And the problem with the way we build AI systems now is we give them a fixed objective, right? The algorithms require us to specify everything in the objective. And if you say, you know, can we fix the acidification of the oceans? Yeah, you could have a catalytic reaction that does that extremely efficiently, but, you know, consumes a quarter of the oxygen in the atmosphere, which would apparently cause us to die fairly slowly and unpleasantly over the course of several hours. So how do we avoid this problem?

You might say, okay, well, just be more careful about specifying the objective. Don't forget the atmospheric oxygen. And then of course, some side effect of the reaction in the ocean poisons all the fish. Okay, well, I meant don't kill the fish either. And then well, what about the seaweed?

Okay, don't do anything that's going to cause all the seaweed to die and on and on and on, right? And the reason that we don't have to do that with humans is that humans often know that they don't know all the things that we care about. If you ask a human to get you a cup of coffee, you know, and you happen to be in the Hotel Georges Sank in Paris, where the coffee is, I think, 13 euros a cup, it's entirely reasonable to come back and say, well, it's 13 euros. Are you sure you want to go next door and, you know, get 1. And It's a perfectly normal thing for a person to do right to ask you know I'm gonna repaint your house is it okay if I take off the drain pipes and then put them back.

We don't think of this as a terribly sophisticated capability but AI systems don't have it because the way we build them now, they have to know the full objective. If we build systems that know that they don't know what the objective is, then they start to exhibit these behaviors, like asking permission before getting rid of all the options in the atmosphere. In all these senses, control over the AI system comes from the machine's uncertainty about what the true objective is. It's when you build machines that believe with certainty that they have the objective, that's when you get the sort of psychopathic behavior. And I think we see the same thing in humans.

What happens when general purpose AI hits the real economy? How do things change? Can we adapt? This is a very old point. Amazingly, Aristotle actually has a passage where he says, look, if we had fully automated weaving machines and plectrums that could pluck the lyre and produce music without any humans, then we wouldn't need any workers.

That idea, which I think it was Keynes who called it technological unemployment in 1930, is very obvious to people, right? They think, yeah, of course, if the machine does the work, then I'm going to be unemployed. If you think about the warehouses that companies are currently operating for e-commerce, they are half automated. The way it works is that on old way how's where you've got tons of stuff piled up all over the place and humans go and rummage around and then bring it back and send it off. There's a robot who goes and gets the shelving unit that contains the thing that you need, but the human has to pick the object out of the bin or off the shelf, because that's still too difficult.

But you know, at the same time, if you make a robot that is accurate enough to be able to pick pretty much any object, and there's a very wide variety of objects that you can buy. That would, at a stroke, eliminate 3 or 4000000 jobs. There's an interesting story that E.M. Forster wrote where everyone is entirely machine dependent. The story is really about the fact that if you hand over the management of your civilization to machines, you then lose the incentive to understand it yourself or to teach the next generation how to understand it.

You can see War Lee actually is a modern version where everyone is enfeebled and infantilized by the machine. And that hasn't been possible up to now, right? We put a lot of our civilization into books, but the books can't run it for us. And so we always have to teach the next generation. If you work it out, it's about a trillion person years of teaching and learning and an unbroken chain that goes back tens of thousands of generations.

What happens if that chain breaks? And I think that's something we have to understand as AI moves forward. The actual date of arrival of general purpose AI, you're not going to be able to pinpoint, right? It isn't a single day. It's also not the case that it's all or nothing.

The impact is going to be increasing. So with every advance in AI, it significantly expands the range of tasks. So in that sense, I think most experts say by the end of the century, we're very, very likely to have general purpose AI. The median is something around 2045. I'm a little more on the conservative side.

I think the problem is harder than we think. I like what John McCarthy, who was 1 of the founders of AI, When he was asked this question, he said, well, somewhere between 500 and 500 years, and we're going to need, I think, several Einsteins to make it happen.

Speaker 0: But how will the economy change in the meantime? Will it be able to keep growing? Watch this video to hear economist Kate Raworth explain why growth is not always a good thing, or continue to expand your understanding of economics on the World Economic Forum's YouTube channel.

See all TED-Ed transcripts on Youtube

How will AI change the world?