Should We Fear AI? Brian Cox & Stuart Russell on The Rise of The Machines

What if I told you I could offer you something that would enable you to walk again? I call it STEM, a computer chip that has the potential to change everything. From virtual assistants like Apple's Siri to robotic vacuums and self-driving cars, artificial intelligence has become a big part of our everyday lives. As the world and our lives grow increasingly dependent on artificial intelligence, it is essential to assess its perceived impact and the implications of this revolution. Should we be fearful of artificial intelligence and the pace at which it is progressing? Will we lose control over our future? Or will AI complement and augment human intelligence in beneficial ways? Professor Brian Cox explores the topic of artificial intelligence and its impact on our live and societal structures to use technologies to improve the quality of living. Artificial intelligence, that's a term that we're all probably aware of, usually, I think, via science fiction. So we tend to think of things like HAL in 2001 or Deckard in Blade Runner, Skynet, Terminator, which certainly gives us, probably in popular culture at least, a rather bleak outlook about the future of artificial intelligence. So now, a lot of the current advances in AI have been made possible in a scientific field called machine learning, which has grown rapidly in recent years. And there are many applications. You're probably familiar with them, although you might not know it. So Google Search, for example, uses machine learning. Spam filtering on email. Netflix film recommendations. Facebook feeds. All those use this technology, although perhaps we don't know it when we use it. And this is why the Royal Society has carried out a major policy project on machine learning. It's been investigating the potential of this technology in the near future and the barriers to safely realising that potential. While we are nowhere near creating a machine that has a mind of its own, we are witnessing the emergence of a new era of intelligent machines that can learn, adapt and solve problems on their own. Now, you have to go back to, in fact, we found in research, Homer's Iliad in 800 BCE to find the first accounts of automata. And over the centuries, those ideas have developed into the more familiar ideas of robots, cybernetics and now artificial intelligence. And it was Royal Society fellow Alan Turing who began to grapple with the notion specifically of a machine-based intelligence throughout the 1940s. And in the 1950s, he posed the question which has become known now as the Turing test, which is can machines think? And the idea is that a machine could be understood or presumed to think if it exhibits an intelligence which a human might think was actually human. And in reality, that might be considered to just point to the idea that humans are gullible rather than a measure or a perception of machine intelligence, if you like. But perhaps this tells us that our relationship with AI might be just as important as the relative intelligence of the machine itself. As the use of artificial intelligence grows and spreads throughout society, how do we feel about it making decisions on our behalf and doing jobs for us? The Turing test has long been a benchmark for machine intelligence. Recently, Google has fired an engineer who claimed an unreleased AI system had passed the Turing test. However, according to Google, the evidence does not support his claims. With AI advancing faster than expected, experts in the field predict that it is only a matter of time before artificial general intelligence emerges. Stuart Russell is a professor of computer science at the University of California, Berkeley. He is one of the world's most respected experts on artificial intelligence, addressing our collective unease around the rise of artificial intelligence. It's actually surprisingly difficult to draw a hard and fast line and say, well, this piece of software is AI and that piece of software isn't AI. Because within the field, when we think about AI, the object that we discuss is something we call an agent, right, which means something that acts on the basis of whatever it has perceived. And the perceptions could be through a camera, through a keyboard. The actions could be displaying things on a screen or turning the steering wheel of a self-driving car or firing a shell from a tank or whatever it might be. And the goal of AI is to make sure that the actions that come out are actually the right ones, meaning the ones that will actually achieve the objectives that we've set for the agent. And this maps onto a concept that's been around for a long time in economics and philosophy called the rational agent. So the agent whose actions can be expected to achieve its objectives. And so that's what we try to do. And they can be very, very simple. A thermostat is an agent. It has perception, just measures the temperature. It has actions, switch on or off the heater. And it sort of has two very, very simple rules. If it's too hot, turn it off. If it's too cold, turn it on. And is that AI? Well, actually, it doesn't really matter whether you want to call that AI or not. So there's no hard and fast dividing line. Like, well, if it's got 17 rules, then it's AI. If it's only got 16, then it's not AI, right? That wouldn't make sense. So we just think of it as a continuum from extremely simple agents to extremely complex agents like humans. According to Russell, there are risks from poorly designed AI systems. We have given them a free pass for far too long. However, there's also a positive side to technological development. It can help us create more efficient models for solving problems and tackling challenges in new ways to benefit society generally. And that's why many researchers around the world have been working to help develop sophisticated models of how machines, and in particular, artificial intelligence, can help us tackle some of the biggest challenges we face. AI is a technology. It isn't intrinsically good or evil. That decision is up to us, right? We can use it well or we can misuse it. There are risks from poorly designed AI systems, particularly ones pursuing the wrongly specified objectives. And I actually think we've given algorithms in general, not just AI systems, but algorithms in general, I think we've given them a free pass for far too long, right? And if you think back, there was a time when we gave pharmaceuticals a free pass. There was no FDA or other agency regulating medicines, and hundreds of thousands of people were killed and injured by poorly formulated medicines, by fake medicines, you name it. And eventually, over about a century, we developed a regulatory system for medicines that, you know, it's expensive, but most people think it's a good thing that we have it. And we are nowhere close to having anything like that for algorithms, even though, perhaps to a greater extent than medicines, these algorithms are having a massive effect on billions of people in the world. I don't think it's reasonable to assume that it's necessarily going to be a good effect, because we have billions of people engaging with social media hundreds of times a day. And every one of those engagements, clicking, swiping, dismissing, liking, disliking, thumbs-upping, thumbs-downing, you name it, all of that data is inaccessible. However, if you think about the way the algorithms work, what they're trying to do is basically maximize click-through, right? They want you to click on things, engage with content, or spend time on the platform, which is a slightly different metric, but basically the same thing. And you might say, well, okay, the only way to get people to click on things is to send them things they're interested in. So what's wrong with that? But that's not the answer. That's not the way you maximize click-through. The way you maximize click-through is actually to send people a chain of content that turns them into somebody else who is more susceptible to clicking on whatever content you're going to be able to send them in future. So the algorithms have, at least according to the mathematical models that we've built, the algorithms have learned to manipulate people to change them so that in future, they're more susceptible and they can be monetized at a higher rate. Now, at the same time, of course, there's a massive human-driven industry that sprung up to feed this whole process, the clickbait industry, the disinformation industry. So people have hijacked the ability of the algorithms to very rapidly change people because it's hundreds of interactions a day. Everyone is a little nudge, but if you nudge somebody hundreds of times a day for days on end, you can move them a long way in terms of their beliefs, their preferences, their opinions. The algorithms don't care what opinions you have. They just care that you're susceptible to stuff that they send. Thanks for watching. Did you like this video? Then show your support by subscribing and ringing the bell to never miss videos like this.