The Signal

[Music] If there was a big rent button that would just demolish the internet, I would smash that button with my forehead. From the BBC, this is the interface. The show that explores how tech is rewiring your week and your world. This isn't about quarterly earnings or about tech reviews. It's about what technology is actually doing to your work, your politics, your everyday life. I'm all the bizarre ways people are using the internet. Listen on BBC.com or wherever you get your podcasts. [Music] [Click] [Music] I'm Gregory Warner and this is The Last Invention. On November 30th, 2022, the world, as we know, it changed forever with the introduction of chat GPT. The robots are taking over. The internet's going crazy. Over new artificial intelligence called chat GPT. So much of this moment that we're in. In the AI revolution, so much of this debate that we're having about what we should do next, was triggered by the arrival of chat GPT. The next generation of artificial intelligence is here. It took Netflix more than three years to reach 1 million users, but it took chat GPT just five days. The program can write really complex essays, books, news articles, and even computer code. And whether you're a chat GPT fan or not, that single AI chatbot and the models that followed, a supercharged industry shifted our relationship to AI and fueled this debate about our future with intelligent machines. In that moment, that meteoric impact on our collective conversation, that wasn't just predicted. That moment was forged over 70 years ago in the middle of a war. Great. So in a lot of ways, what we think of today as artificial intelligence, it comes out of the Second World War. Reporter Andy Mills. And actually not just the war, but one battle in them. The Battle of the Atlantic continues. As our convoys pass to and fro, you boats lurk in the vast waters, preparing to cut our lifelines at every opportunity. Alright, so for context, it's 1940, and the Germans have all but cut off the supply lines between the US and Great Britain in the Atlantic Ocean. Thanks in part to this technological edge that their navy has in the form of you boats. Hitler has loosened the whole weight of his you boat force against our lifeline in the Atlantic. And it became clear that if they couldn't stop these you boats, they might lose the war. The Battle of the Atlantic holds first place in the thoughts of those upon whom rest the responsibility for procuring the victory. One great hope that they had to reverse Germany's dominance in the Atlantic was to crack their enigma code that they used to communicate with these you boats. But the trouble was month after month, as hundreds and thousands of soldiers died and ship sank, nobody could crack it. Right. And just to clarify, so code breaking at that point in history was still a very human endeavor. Yes, at this point, it is very common for pretty much every military across the world to have a team of code breakers that they work with where they try and intercept and decode the communications of their enemies. Right. But none of those teams in the allied forces were able to crack this code. And so back in England, a team was assembled of a somewhat unlikely group of people. You had mathematicians, academics, even some chess masters, and these were folks who were not in the military. The military was trying to recruit beyond their ranks. Yes, they were recruited out of the classrooms, recruited out of their research labs. And essentially given an enigma and the government said, look, we need help. Is there anything you could do? And eventually, after a lot of trial and error, they end up constructing this electro mechanical, essentially calculator that could sift through the government. Sift through millions and millions of possible configurations of this code, something that would have taken a human group of code breakers, weeks and weeks in just hours. And lo and behold, German submarines have been surrendering all over the place in fairly satisfactory numbers. They crack in Nigma. It opens up the Atlantic. And this is how you get events like D-Day. Americans could now travel the Atlantic to Europe, and many people think that this is one of the key factors that leads to the Allies victory over the Nazis. Time and time again, the very issue of the war depended on the breaking of the U-Boot-Bake. And now as some of the last U-Boot came in from sea, no one forgot the lives given and the battles fought against the very grave menace they implied. And the main guy behind that code breaking team, his name was Alan Turing, and according to the people that I interviewed, right there in the middle of the war, looking at this big electro mechanical contraption that he had helped make, he was already envisioning the day when that machine would be able to think for itself. If we were trying to tell the story of where AI is at right now and where it might be headed next, where does that begin? Alan Turing. Alan Turing, obviously one of the godfathers of computer science, and was the father of AI. So from almost day one, Turing saw computers, not just his tools that could break codes, but as machines that could think at the highest level. Yes, and from the very beginning of this field of computer science, he inspired this goal to make what today we call AGI. It is the genesis, the or like philosopher stone of the field of computer science. Basically, this is the holy grail of the last 75 years of computer science. And even more dramatically than that, he believed that ultimately the machines would think even better than humans. And that when that happened, they would be able to take control. He talks about how surely one day, you know, there will be machines that can converse with each other, improve upon their things, do anything that you've been can do, and they will surely leave humanity behind. The idea that this is possible has been around for very long time. Alan Turing in 1951 said that the default outcome is that the machines are going to take control. This is something that I talked to Max Techmark about. He teaches machine learning at MIT and is a very influential voice in the AI debate we're having today. Because he didn't think of AI as just another technology like this team engine thought about it as a new species. But Turing was pretty chill about it and said, you know, don't worry about it. It's far away. It was right. It was far away from 1951. And he said, but I'll give you a test. So you know when you're close, he'll give you canary in the coal mine. It's called a Turing test. And Max says that this is one of the reasons that he created what's called the Turing test. You know the Turing test, right? I mean, I think the Turing test is where you're chatting with a possibly a machine, possibly a human, something on the other side of the screen. And the goal of the test is can the machine fool you into thinking that you're actually chatting with a human? Yes, that in short is the Turing test. Can you be in conversation with a machine and not know the difference between it and a human being? And Techmark, he was saying that this was not a benign test. This wasn't even necessarily just a test of the machine. But it was a way to send a signal to people in the future to say that once you've crossed this threshold, when machines can master language and knowledge at the level of humans, then you're close. It was like a warning shot to the future to tell them there's no going back. Because soon it will be outside of our control. And did Turing see this future of machine-staking control as something good or something he was warning us about? Well, that question is very much up for debate right now. A lot of the people who are worried about this moment we're in with artificial intelligence now. They look at this one line where he said once the machine thinking method has started, it would not take long to outstrip our feeble powers. At some stage, therefore we should have to expect the machines to take control. And they say obviously that sounds very foreboding. He was warning us that this was going to be dangerous. But in most of his lectures, he's far more matter of fact. And a lot of people point out that Turing himself, he wasn't a moralist. He was a contrarian. And he often win as far as to say that when this happened, the machines would "deserve our respect." And so a lot of the people that I spoke to said that trying to take Turing or the Turing test and to turn it into something doomer or something accelerationist is missing the point. I actually think the difference between the optimists and the pessimists can be overstated. I think the fundamental difference has always more fundamentally been between people who thought this was a real possibility to take seriously and the people who didn't. And I think the main thrust of the argument was to say Look, people take this seriously. This is a thing. This is something that I was talking about with Rob Enhancin. He is an economist, but he also for many years was an AI researcher. It's a rhetorical device to try to get people to take a space of possibility seriously. There's certainly in academia, there's just a long tradition, quite reasonable, saying, "until you can even tell me what your words mean." I'm not really interested in taking your conversation seriously, right? Uh-huh. So, Turing was primarily trying to just make sure we could talk about an AI and have that be somewhat precisely defined so that you wouldn't dismiss the idea by just saying that's too vague. It sounds like Turing didn't just give us a test of how we'd know the AI could think, but actually gave us some kind of practical, concrete way of saying, "Okay, no, this is artificial intelligence. When it can talk back to us and convince us it's human." See, it's more complicated than that. That's what I thought the Turing test was for a long time, that once it can do this, it is now officially an AI, but he actually didn't think that it was going to suddenly be super useful in this moment. It wasn't that now you are in the presence of a true thinking machine and it's tomorrow going to start taking over. What he was doing was more nuanced. He was giving the field of computer science a goal that they could shoot for. He was saying, "This is something you could technically go out and build." But in this deeper sense, he was producing this story that the broader public could understand and making this prediction that once this moment happened, once a machine could so thoroughly mimic how an intelligent person communicates that we would treat it differently, that we would imbue it with something profound and utterly transformative. So, it's not just a test of the machines and how far it's come, but it would change our relationship to the machine. Right. In some ways, it's just as much a test about us as it is a test about the machine. So, what happens to that dream of Turing's? Well, sadly, Turing dies in 1954. It's a terrible story. He was prosecuted by his own government for being gay. Because homosexuality was illegal in England at that time. Yes. He was sentenced to what they called chemical castration and allegedly he committed suicide. But Turing's dream doesn't die with him. He gets picked up by a group of scientists in the U.S., many of whom actually knew Turing personally, a lot of them had corresponded with him, and they raised money for a 10-week summer program at Dartmouth, where the idea was to come together, create a prototype of a true thinking machine, and to turn the entire pursuit into a proper field of study. So the AI discipline is founded in the summer of 1956. This is a story that I talked to Karen Howe about. She is a tech reporter and the author of Empire of AI. The people that had gathered together were already very accomplished scientists, giants, in their own fields. So this summer program included people like Claude Shannon, who was the inventor of information theory. Also, Claude, the namesake of the Anthropic AI Model Claude. Indeed, he was. Nathan Rodchester was there. He was the maker of the first commercial computer at IBM. There were also people there like Marvin Minsky and John McCarthy, who would found the first AI labs at MIT. The reason why this is considered the origin story of the field is because a Dartmouth professor, John McCarthy coined the term artificial intelligence and started using it for the first time to form this new field. This is where we first get the name artificial intelligence. What did they call these thinking machines before that? Well, Turing called them thinking machines. Some of them were calling it a tomato. John McCarthy tried originally to call it a tomato studies, which personally I like. And it just didn't sound exciting. They were trying to attract funding from government and from nonprofits and it just wasn't working. So he specifically went to cast about for a more evocative phrase and hit upon artificial intelligence. And this name, artificial intelligence. Karen says that this would forever shape the field partly because it would tie it to the thorny question of what actually is human intelligence. And because there is no consensus around where human intelligence comes from, there was plenty of debate and discourse at the time about what would it actually take to get machines to think. So everybody there believed in what Turing was saying that machines could think that AI could be built. But the debate was more about what exactly are we mimicking? What is the intelligence we're copying? Yes. How does our intelligence work and therefore how would we recreate it? And right away that question, it splits the AI researchers into these two different groups. And it gives birth to two different paths towards AI that continue to this day. And the dominant tube camps that emerged were called the connectionists and the symbolists. So the symbolists believe that human intelligence comes from the fact that we know things. And so if you want to recreate intelligent computer systems, you need to encode them with databases of knowledge. So this created a branch of AI focused on building so-called expert systems. All right. So the first group, the symbolists, they get their name because they believed you could build intelligence into a machine by writing rules and using symbols like numbers and words. And that you could essentially encode human-like intelligence and create something like a human expert. But the connectionists, they believe human intelligence comes from the fact that humans can learn. And so to recreate intelligent computer systems, then we need to develop machine learning systems, software that can learn from data. But the second group, the connectionists, they say human intelligence, it doesn't come from shoving a bunch of expertise and logic into our brains. It comes from our ability to find our own patterns in the world and to find our own connections between those patterns. Right. So instead of trying to build something that's like a human expert, we should try and build something closer to a human toddler or a baby. When you watch babies grow up, they're constantly exploring the world, they're gathering all of this experience, and they're quickly updating their model of their environment around them. And that's what the connectionists believe was the primary driver of how we become intelligent. That's kind of cool that you could create an AI not that knows the things you taught it, but that it could go out and learn new things from the patterns it finds from the data. But thinking about a baby that will grow up and come to its own conclusions to drive its own values, wouldn't that model be a lot less predictable than the simplest human expert? You're teasing at the current drama. Greg, yes. The connectionist model would be far less controllable, far more unwieldy, and eventually, that's going to strike some fear into many a heart. In the long run, the framing that they picked, the ideas that they discussed back then, the debates that emerged that summer have continued to have lasting impact to present day. Okay. Some are programmers and they have a new name, they have a debate. What else do they got? Well, they've got a lot of dreams, they've got a lot of theories, but they do not have a lot of money. Remember, like we said, computer science is a brand new field. Artificial intelligence is like a branch of computer science is a new experimental field inside of a new and experimental field. And so they don't have the resources that they need to really build the models and turn their math and their dreams into something functional in the world. However, all that was about to change because of the arrival of the many ways a new battle. CBS television presents a special report on Sputnik 1, the Soviet Space Satellite. On October 4th, 1957, the USSR becomes the first nation to ever get a satellite into orbit. Really quite an advancement for not only the Russians, but for international science. So first time anybody has ever been able to get anything out that far in space and keep it there for any length of time. It's this absolutely amazing achievement for science. But of course, it comes right in the midst of the Cold War. It gets the American people along that a foreign country, especially an enemy country, can do this and we fear this. And it triggers all of these fears about the communists winning the space race. Let's not fool ourselves. This may be our last chance to provide the means of saving Western civilization from annihilation. And in response to this, in a move that modern day accelerationists say that we should embrace in our current AI race with China, the United States decides, "All right, let's accelerate." "These are extraordinary times, and we face an extraordinary challenge. Our strength, as well as our convictions, have imposed upon this nation the role of leader in freedom's course." They flood a bunch of money and a bunch of resources into universities, into science labs. They make this huge national effort to recruit all kinds of young talented people to go into space, to go into technology. "Now it is time to take longer strides. Time for this nation to take a clearly leading role in space achievement, which in many ways may hold the key to our future on earth." "Test, nine, ignition sequence start, six." "And it works." "Lip stop, we have a lif stop, lif stop on a party level." The U.S. wins the race. We are the first to get to the moon. "It's one small step for man, one giant leap for man." And it becomes really one of the most inspiring events in history. This realization of an enormous dream, this example of what can happen when people put everything into this goal of reaching beyond what was previously thought possible. And it turns out that this also was an absolute boom time for the field of artificial intelligence. "The Cold War was really a fountain of youth for research." I found this interview of Marvin Minsky, he was one of the guys at the Dartmouth Summer Program. "There was huge amounts of money, more than you needed." And he was saying that suddenly these AI labs had more money than the NUWA to do with. They were finally able to build the first AI models. They ended up actually building the first AI chatbot named Meliza. "Things proceeded very, very rapidly. A new generation of ideas every two or three years was a wonderful period where you had to change everything you thought." And in fact, the field of AI was moving at such a rapid pace that a lot of AI researchers began to think that by the time the astronauts got to the moon, that we were going to be living here on Earth alongside thinking robots. "The Thinking Machine, produced by the CBS Television Network." I found this old CBS archive from the 1960s. "Can machines really think? I'm David Wayne and as all of you are, I'm concerned with the world in which we're going to live tomorrow. A world in which a new machine may be of even greater importance than the atomic bomb." And in it, they're interviewing all these AI researchers at the time, "But I think the computers will be doing the things that men do when we say they're thinking." And all of them are confident that this breakthrough was close. "I confidently expect that within a matter of 10 or 15 years, something will emerge from the laboratories, which is not too far from the robot, a science fiction thing." "I'm convinced that machines can and will think in our lifetime." "Okay, so they sound very optimistic about the AI they were going to make, but were there any fears and doubts about what would happen once they made it?" "Well, this is something that a lot of people, especially those who are worried about our current AI marvel at about this time period. This is something that came up when I was talking to Nick Bostrom, the author of that book, Super Intelligence." "The early pioneers were actually quite optimistic about the timelines. They thought maybe, you know, in 10 years or so, we would be able to get machines that can do all the humans can do." So in some sense, they took that seriously. I guess that's part of what drew them into, trying to program computers to do AI stuff. But in another sense, they weren't serious at all because they didn't then seem to have spent any time thinking about what would happen if they were right, if they actually did succeed in getting machines to do everything that humans can do." So you're saying that in the research labs during this time, there weren't people who were saying, "Oh my God, what's this going to do to the economy? Oh my God, what if this changes the society forever?" "Yeah, that was very little, I mean, thinking about, you know, the ethics of this, the political implications, like the safety, it was as if their imagination muscle had so exhausted itself in conceiving of this radical possibility of human level AI. That they couldn't take the obvious next step of saying, well, probably if we get that, we will have super intelligence not too long after." I think that the best explanation for just why this time period had such a different mindset than we do today came from something that I heard from Robin Hanson. Why is it that you think there was not a big robust discussion about AI safety and that they were moving so fast, asking so few questions? Why wasn't it more safety at the time? Well, first of all, safety as a cultural trend is just something that's happened since then, mostly in the world. The world back then wasn't very safety-est, honestly. Right, no seat belt lock. They didn't have seat belts, for example. Okay. And secondly, this was a technological framing. This was a "can we do this?" is this technologically feasible. And you said you have to put yourself into their mindset, which is that they are living in the aftermath of the Second World War. Many of these people were veterans of the Second World War. They are worried about another war that could break out with the Soviets. And there was this idea that if your scientists could conceive of a new technology, you have to assume that your opponent's scientists have also conceived of that technology. Because right after World War II, there was clearly this strong perception that the winners are the ones who more effectively pursue possible technological changes. There was this expectation of technological progress and an expectation that in order for your nation to stay competitive with the world, you needed to pursue feasible technologies. The idea of being that it would be a better world if we made this technology and not our enemies. Good, maybe for humanity, but plausibly also more good for our people, for our nation. Or whatever if we are pursuing this before the rest. And do we know if they actually thought the Soviets were trying to compete in AI? Yes. There was a rumor that was going through the Department of Defense circulating through the government that the Soviets and their AI researchers were right on America's heels. When you read the communication about it, it sounds so similar to how we think of China and the US with AI today. Like, the US has no choice but to barrel forward with creating this AI because God forbid the Communist get their hands on it first. Different communists, but same fear as now. However, there was this one guy in the field of AI research who did express some serious concerns about what might happen. His name was Dr. I.J. Good. His friends called him Jack. But literally Dr. Good. His name is? His name is literally Dr. Good. He was friends with Alan Turing. They worked together on that code breaking machine in World War II. And too many of those who are concerned about AI today, they think that Good is just as influential to this debate as Turing. As a consequence, I think mainly of conversations with Turing during the war, I was also fascinated though not to the extent that Turing was obsessed with the notion of producing thinking machines. So I was quite interested in them. And in fact, in 1958, I think. And that's because Good was the first person to publish this idea that he called ultra intelligence, which today we call super intelligence. This idea that once the thinking machine became a true artificial intelligence, so that could think as good or better as a human, that that machine would then create an even more intelligent machine, which would create an even more intelligent machine. And you would have what he called an intelligence explosion. Almost like a nuclear chain reaction. Right. That it affects everything around it. This moment where everything would change for the human race. But what's interesting about it is that he opens up this paper, he wrote, by saying that humanity has no choice really but to create this machine. Well I wrote a paper in 1965 called Speculations Concerning the First Ultra Intelligent Machine. And I started off that letter by banging a gong by saying the survival of humanity depends on the early construction of an ultra intelligent machine. And why did IJ Good think that our survival as a species depended on making this machine and it sounds like making it quickly? Meaning not just that we, oh we really should make this thing but we need to make it for our own survival. Well he wrote this paper and he put this idea out there in 1965 and in some ways 1965 is a world away from 1956. And at the time he and many others had started to worry about the quote unquote existential risks facing humanity. The most obvious one being this fear of a nuclear war between the US and the Soviet Union that ended up leading to mutual destruction for everyone on earth. Right. This is a time when public school kids are regularly doing nuclear drills jumping under their desks and just in case. Exactly. This was also a time of the largest population boom in the history of humanity. There was concerns about there maybe not being in a food defeat all of these new humans that were coming into the world. This was the early days of what would become the environmentalist movement. Concerns about what cities full of smog and pollution were going to do to our increasingly crowded world and people like IJ good were saying that we are going to need a technological solution to the problems of our age and that this ultra intelligent machine. This would be a safeguard to all future existential crises that face the human species. What strikes me though is that all of these existential concerns are concerns brought about by technology. IJ good felt like more technology was the answer to these technological problems. Once again, one of the reasons that he is now so legendary among those who are concerned about this AI moment we're living in right now is that he was the first to really point out that even though there would be all these amazing benefits in having a super powerful intelligent machine that it also would pose its own existential threat. The most famous line in this paper is quote, "The first ultra intelligent machine is the last invention that man ever need make." Because every other invention passed then would be invented by AI. We wouldn't need to make invent anything else. Exactly. But he follows that line up by saying that to experience the benefits and the protections of this intelligence explosion that we would need to find some way to ensure that that machine is docile. That was his word. It's almost like he's offering hope, but with a very large caveat. Yes, essentially he's saying we will make this, maybe we need to make this right, but everything hinges on how we make this and what we do between now and when that machine arrives. Because if we succeed in making this machine before we figure out how to make it quote, unquote, docile, his warning was that man's last invention might end up being our final mistake. We'll be right back after the short break. Hello, this is Matt and this episode is sponsored by Ground News. Ground news is one of the most helpful tools that I use every day to avoid the echo chambers and media bias online. Here's an example of what I mean. "Roll the window down." "Roll that one down too." 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That's hollowsocks.com for up to 50% off your order. After you purchase, they will ask you where you heard about them, and you can support our show and tell them who sent you. Okay, so Andy, where we left off, Alan Turing had infused the field of computer science with this dream of a thinking machine and the summer program at Dartmouth took up that dream, founded the field, gave it the name AI. And the Cold War supplied way more money than anyone knew what to do with. And then AI is actually starting built at that point, right? And there's all this confidence that we're going to the moon. We're also going to start living with robots. We did make it to the moon. We did not start living alongside intelligence robots. Sadly no. So why? Well, what happened to Turing's dream? So in short, throughout the 1960s, as incredible in some ways as the advancements were that the field of AI was making, they failed to live up to the hype that they created. Their AI models don't scale. They're not seen as very useful. They failed to hit a number of their benchmarks. And eventually their funding starts to dry up. Eventually the US government does realize that the USSR is not on the brink of creating a true thinking machine. And the entire field of AI enters what many people call an AI winter. But the idea of artificial intelligence, it does not enter an AI winter. In fact, if anything, it moves even further into the mainstream, but not because of any advancements being made by the world of technology, but because of the world of science fiction. And much of that stems from the 1968 movie 2001, A Space Odyssey by Stanley Kubrick and Arthur Clark. So, okay, 2001, a Space Odyssey, great movie. But is this then the first time AI appears on the screen? Well, yes and no. On the one hand, there had been these somewhat intelligent machines that had been in movies like Metropolis going back to 1927. Riders like Isaac Asimov in the 30s and the 40s were writing these really interesting stories about a time where human beings lived alongside intelligent robots. But what makes 2001 so singular is that its main character isn't a humanoid robot, but it's something much more like a super intelligent AI system. What's the difference between a robot and a super intelligent system? So, previous ideas of this thinking machine were sort of a cross between the Tin Man and Frankenstein, right? They spoke robotically and they were sort of dumb. But how 9000? Good afternoon, how's everything going? Good afternoon, Mr. Raymer. Everything is going extremely well. He's not a clunky robot, but but he's something more like software. And he's rational, he's smart, he's curious. - Good evening, Dave. - How you doing, huh? - Everything's running smoothly, and you? - Oh, not too bad. - Have you been doing some more work? - A few sketches. - May I see them? - Sure. - Right, even the way he's manipulative, it feels human, some way. - Do you mind if I ask you a personal question? - Like a kind of nosy HR rep. - No, no, no. Well, forgive me for being so inquisitive. But during the past few weeks, I've wondered whether you might be having some second thoughts about the mission. - And one of the reasons that How 9,000 feels so different is because Stanley Kubrick and Arthur Clark, his co-writer, they actually constructed the character of Howl in consultation with the top AI researchers at the time. - One day he just turned up, and he was going to make this movie. He was intrigued by artificial intelligence and invited me to come out to the studios. - Marvin Minsky, who was a part of the original Dartmouth summer program, he worked with Kubrick on the film. - Well, that was a very amusing cooperation because Stanley Kubrick would not tell me anything about the plot. - And he says that specifically Kubrick consulted him and his colleagues at MIT about what the AI system would look like, how it might function, what kind of aesthetics it might have. But for the question of how an AI system might pose a real danger, might break bad, they consulted, none other than IJ Good. - And so what did Dr. Good let them know about how AI might break bad? As you remember, most of the movie takes place inside of a spaceship. There are a number of human astronauts as well as Howl 9000 and they're on this mission. You never quite get to know exactly what the mission is they're on, but you understand that it is of grave importance for the entire human race. - Howl, you have an enormous responsibility on this mission. In many ways, perhaps the greatest responsibility of any single mission element, does this ever cause you any lack of confidence? - And early on in the film, you realize that control center back on Earth has given Howl strict orders to ensure that the mission is successful. - Let me put it this way, Mr. Raymer. No 9000 computer has ever made a mistake or distorted information. We are all by any practical definition of the words, foolproof and incapable of error. - And the drama in the movie is that at a certain point, Howl becomes convinced that the human astronauts on this spaceship are an impediment to Howl 9000 accomplishing its ultimate mission. - Oh, Howl, do you read me? Do you read me Howl? Affirmative days, I read you. - And so in a somewhat cold and calculated way, - Open the pod bay doors, Howl. - I'm sorry, Dave. I'm afraid I can't do that. Howl makes the decision to kill the hibernating crew and in the iconic scene in the movie. - What's the problem? I think you know what the problem is just as well as I do. - What are you talking about? - Howl locks the captain out of the ship. - This mission is too important for me to allow you to jeopardize it. - I don't know what you're talking about, Howl. Open the doors. - Dave, this conversation can serve no purpose anymore. - Goodbye. - Howl. Howl. Howl. - And this is of course the scene where he goes rogue. He doesn't follow a direct order by the captain of the ship. - Well, this is also one of the things that makes 2001 a space Odyssey such a singular movie, especially in this time, because how doesn't go rogue the way that Frankenstein goes rogue. How doesn't go rogue the way that the robot in Metropolis goes rogue? - He doesn't try to destroy his creator and he doesn't become a monster. - No, I mean, he does become a murderer. He murdered a mass murderer of people that he knows. That's not good. But the idea is that it is not coming from some sort of rage or some evil. - Yeah, some sense of evil. He is actually doing this out of an enactment of the values he's been programmed to have. And this is an idea born not just out of a desire for a great plot, although it is a great plot, but out of IJ Good trying to imagine the kinds of conflicts that we are going to come into one day in the future when he believed we would begin to make these ultra intelligent machines. (dramatic music) And so in a way, the movie becomes most people's introduction not just to artificial intelligence, but to the kind of threat that a future AI might pose. And of course, 2001, it's this absolutely massive hit. - The Winter is Stanley Cooper, in 2001. (audience applauding) - It wins the Academy Award. It wins like every major award. It's now seen as one of the most influential films of all time. And really from that moment in 1968, up through today, artificial intelligence becomes this main stay in American entertainment. - You're reading a magazine. You come across a full page nude photo of a girl. - Is this testing whether I'm a replicant or a lesbian Mr. Deckard? - Just answer the questions, please. - Movies like Blade Runner, The Terminator. - Come with me if you want to live. - The Matrix. - The future is our world. More of this. The future is our time. - More recently, ex-Makina. - Hello. - Hi. - Do you have a name? - Ava. - And over time, AI's place in science fiction, it has presented this interesting problem for everyone today who is concerned about AI. - One of the effects in some sense is to make people aware of possibilities and to have images to hang words onto when topics come up, right? - Again, Robin Hansen told me that while sci-fi did the same thing that Alan Turing was trying to do, it gave the public a way to talk about AI, a way to picture AI. - Right, so if we talk about robots and how they might be in society and what they might do, these images from science fiction are available for us to use to fill in those words with images. - But at the same time, it also weirdly put AI into this category that makes it easier to dismiss. - By having this category of science fiction, which everybody agrees shouldn't be taken seriously, a concept that shows up and seems to fit into science fiction can just be dismissed among serious people. And it has been. - Right, this idea that that's just sci-fi, we don't need to take it seriously. - Exactly. But that works on both the doomer and the acceleration aside. - This is something that came up when I was talking with Sam Harris. He was saying that the idea of AI almost seems too cool for people to see it as a real threat. - There's just something fun and sexy about these science fiction tropes. Me, watch a film like X Machina. It is just fun and it's hard to, you're not really thinking about your kids dying, awful deaths. It's not the same thing as flesh eating bacteria where you just think, let's avoid this at all costs. I don't wanna think about it. It's just like this is just all awfulness. Anyway, I look at it. What's going on in the glass box in X Machina? That's fun. - On the other side though, this acceleration can say yes, but most of the academic safetyism and government safetyism, it's also neglecting a key emotion, which is the enthusiasm and joy and excitement of humanity accelerating forward into vast spaces of technical possibilities. - Right, there's not a lot of movies out there where the plot is, we create AI in the future is awesome. - Exactly. Our world needs to see that excitement and enthusiasm to allow us to be less safety is because they say, plausibly that our world is not realizing the potential of a lot of technologies because we're so safetyist. - When I talk to people who are more accelerationist, they say that the sci-fi problem is exactly the opposite of what Sam Harris is saying. - The contemporary AI safety discourse, when you actually look at where they got these ideas from, it's literally fiction. People like the online commentator and social scientist Justin Murphy. - The fact is that this is a highly imaginative and highly creative possibility, which is definitely worth thinking about, but it's not scientific or nearly as technical as it pretends to be. It is literally grounded, primarily in fiction. - He was saying that the scouts, the doomers, They've essentially allowed signs. science fiction and these science fiction tropes to scare them and shape their sense of reality. So it sounds like you're saying that science fiction is actually playing an important role in where we're at with this technology, where we're at with this debate right now. Absolutely. I've always taken the STEM view of we should have, you know, careful analysis of what's possible and that we should achieve. And I've always assumed that the ends we were trying to pursue were just shared and obvious. And I've, you know, more recently in the last couple of years really come to appreciate cultural evolution and its power. I realize that you can't take inspiration and motivation for granted. Honestly, motivation is the closest thing to magic we have in our world. People are motivated. They do far more than if they're not and we just don't really understand how it works. What actually motivates people? But it's the power that makes everything work. And science fiction has been a reservoir of motivation. Robin Hansen was saying that in many ways we wouldn't be in this moment we're in right now. Like you and I wouldn't be doing this podcast. There wouldn't be this big debate happening around AI. If it were not for science fiction and the ways that it colored how we saw things like chat GPT when chat GPT showed up three years ago and people saw that they could talk to something that seemed to talk back reasonably. That had an enormous cultural impact in part because it resonated with decades of science fiction. Right. The trillions of dollars of investment that is going into AI is substanti- they're in substantial part because of that resonance. That's what made them excited to invest and pursue AI. When you saw chat GPT right in front of you talking back, it's that reservoir of science fiction motivation that convinced people, wow, I should be pursuing this. And it's the reservoir of science fiction fear that will convince people if they do that they should be scared of this. Both of those are in the reservoir. They're both resources for both sides of this. But unfortunately, the logical and analytical arguments are just not the main force that powers action in these areas. And since point, at least how it hit me, was that ultimately this comes down to what story human beings believe were living in. And this debate swirling around artificial intelligence, it may be decided by what we come to believe happens next in that story. Which is why chat GPT just feels so eerie because it's a new technology, but it's not a new story. It is literally a lintering story finally coming true. That's exactly what I keep thinking that the technology that has launched us into this moment is a technology that has found a mastery of human language and communication exactly as he predicted. And here we are having that other side of the line moment as a human species. From the 50s when the term artificial intelligence was coined until four years ago, AI was chronically overhyped. Everything took longer than promised. This is something I was talking to Max Tecmark about. He and his colleagues, they believe that signal that turned sent all those years ago were in the moment now. And then it switched about four years ago to becoming underhyped when things happened faster than we expected. Something is good as even chat GPT was decades away and it wasn't. It already happened. And since then AI systems have gone from high school level to college level to PhD level, the professor level to beyond in some areas. A lot faster than even people thought after chat GPT. So we're in this underhyped regime now when something we thought we were going to have decades to figure out the question of how to control smarter than human machines. We might only have two years or five years. And I think that's fundamentally why so many people are freaking out about this and why you're doing this important piece of journalism now. It's not like we didn't know that we were going to have to face this at some point, but it's been a big surprise to most of the community that now is not 2050, that it's only 2025. And we're already here getting so close to the precipice. Next time on the last invention, the Battle of Man Against Machine, the AI Winter Thaws. Machine didn't just beat man but trounced him. The victory seemed to raise all those old fears of superhuman machines crushing the human spirit. How neuroscientists, games and gamers end up unlocking the door to artificial intelligence. Oh, the computer like this machine can be creative. The last invention is produced by Longview. To learn more about us and our work, go to Longview Investigations.com. Special thanks this episode to Peter Clark. See you soon and thanks for listening.