Will AI destroy us... or save us?

Like it or not, artificial intelligence is deeply rooted in our lives. Its invisible architecture stretches everywhere from dating apps to medical care. In this new world, what remains uniquely human? On today's episode, we explore the tension between our love of AI and our fear of it — and try to decode the humans behind the machines. This episode originally published in March of 2023. Guests: George Zarkadakis, author of In Our Own Image: Will Artificial Intelligence Save or Destroy Us? Francis Collins, physician-geneticist who led the Human Genome Project Stephanie Dick, assistant professor in the School of Communication at Simon Fraser University Meredith Broussard, data journalism professor at New York University, and author of More Than a Glitch: Confronting Race, Gender and Ability Bias in Tech To access bonus episodes and listen to Throughline sponsor-free, subscribe to Throughline+ via Apple Podcasts or at plus.npr.org/throughline. See pcm.adswizz.com https://pcm.adswizz.com for information about our collection and use of personal data for sponsorship and to manage your podcast sponsorship preferences. NPR Privacy Policy https://www.npr.org/about-npr/179878450/privacy-policy

• 0:00Speaker 00

  This message comes from the Southern Environmental Law Center. No one voted for dirty air and water. That's why S E L C is fighting back to defend the healthy environment everyone depends on. Because it's not political, it's fundamental. Learn more at S E L C dot org.

• 0:24Speaker 01

  Open the pod bay doors, Hal.

• 0:28Speaker 02

  I'm sorry, Dave. I'm afraid I can't do that.

• 0:33Speaker 02

  This conversation can serve no purpose anymore. Goodbye.

• 0:49Speaker 03

  Most of us, when we hear the term AI, we think about Hollywood.

• 0:54Speaker 04

  Why do you cry?

• 0:56Speaker 03

  You mean people?

• 0:56Speaker 04

  Yeah.

• 0:57Speaker 03

  I don't know. We just cry. We think about The Terminator, we think about Ex Machina. Did you program her to flirt with me? If I did, would that be cheating, wouldn't it? We think about Star Trek. Please state the nature of the medical emergency. Or maybe Star Wars. Hollywood is so deeply embedded in our brains.

• 1:23Speaker 04

  I'll be back.

• 1:28Speaker 05

  What this AI actually mean, you know, really mean.

• 1:35Speaker 05

  AI is not a magic wand, but it's not a Terminator. This system learns by accessing data. AI is not a harbinger of utopia or dystopia. And it changes its configuration in order to be able to predict stuff. AI is something invented by us to advance our progress.

• 1:54Speaker 03

  It's really complicated, beautiful math, but it is fundamentally just math.

• 2:01Speaker 06

  AI is deeply entangled with our desire to be in control, both of ourselves and the world around us. To control human behavior, to control the future, to control environmental outcomes, to control institutions and societies.

• 2:16Speaker 05

  AI is already here.

• 2:19Speaker 06

  It's in your phones.

• 2:22Speaker 07

  Google or Alexa. Your cars. Google Maps uses a very smart algorithm to provide. Your homes. The home security system uses artificial intelligence to keep your family safe. Your skies. From drones to unmanned aircrafts and beyond. Your hospitals. Interpreting X-rays. Your love lives. The dating apps.

• 2:40Speaker 05

  Your virtual lives. Social media companies spy on us. Your governments. What it means for the future of our democracy. So we are, in fact, totally immersed in an AI world.

• 2:53Speaker 07

  The challenge is not to act automatically. It's to find an action that is not automatic, from painting to breathing to talking to falling in love.

• 3:13Speaker 07

  Are you capable of falling in love?

• 3:17Speaker 05

  I don't have feelings or emotions like love, and I don't have a subjective experience. I exist solely to assist with generating text. This is ChatGPT. I am an AI language model developed by OpenAI. I can answer questions, provide information, and engage in conversations on a variety of topics. How may I assist you today? AI has become an invisible architecture upon which modern life is being built. It's wrapped up in our jobs, our government, our wars, our art. Sometimes without us even realizing it. Right now, we're inside a computer program? Is it really so hard to believe? You've been living in a dream world, Neo.

• 4:03Speaker 05

  There's something powerful about the story The Matrix and countless other sci-fi books and movies tell. The AI becomes sentient, surpasses human intelligence, and lays claim to our world. Sure, it's a terrifying thing to imagine, and yet, we're fascinated by these stories.

• 4:21Speaker 00

  Exploring that feeling, the tension between our love of AI and.

• 4:26Speaker 04

  Our fear of it is what this episode is really about. In a sense, decoding the humans behind the machines.

• 4:33Speaker 05

  As an animal, we're a very weak creature. The only thing that we have is our social structure and our collective and individual minds. And those minds compel us to extend our capabilities. And that is, I think, in many ways, why, you know, people sort of imagined gods being just like them, only more powerful.

• 4:56Speaker 04

  This is George Zarke Dacus.

• 4:58Speaker 05

  I have a PhD in AI and I'm actively working in the field over many years.

• 5:04Speaker 04

  He also wrote a book all about the history of artificial intelligence from ancient times to present day called.

• 5:10Speaker 05

  In Our Own Image: Will AI Save Us or Destroy Us?

• 5:16Speaker 00

  At the heart of this history are a few key questions. Why do we want to create artificial intelligence? What would it mean for a machine to become intelligent? And how would that change our lives?

• 5:28Speaker 05

  Most of the questions I don't think we'll be able to answer at this particular point in history, but I don't think we can resist the temptation of asking them and trying to answer them.

• 5:40Speaker 04

  Coming up, we begin at the very beginning, the Big Bang of the human mind.

• 5:51Speaker 06

  This is Carone de Mars from San Antonio, Texas. You're listening to Throughline from NPR.

• 6:00Speaker 00

  Stay tuned for the following announcements and messages from our sponsors.

• 6:04Speaker 04

  This message comes from Live Right, publisher of John U. Bacon's New York Times bestseller, The Gales of November, a chronicle of the S.S. Edmund Fitzgerald's 1975 shipwreck. "Never has it been told better than by Mr. Bacon in this colorful book," writes John J. Miller of The Wall Street Journal, while author Hampton Sides proclaimed. It's destined to be a classic. The Gales of November, now in paperback.

• 6:30Speaker 00

  This message comes from the podcast Morrison Mysteries. Dateline's Keith Morrison brings his signature storytelling to the haunting works of Edgar Allan Poe. Search Morrison Mysteries to follow now.

• 6:42Speaker 06

  The 2026 midterm elections are upon us. On November 3rd, voters will determine what the next two years of their local leadership and the balance of national government will look like. Listen to the NPR News Now podcast for all the updates you need ahead of and after November 3rd from NPR News.

• 7:07Speaker 06

  What is a human?

• 7:15Speaker 06

  A human is a species of primates characterized by advanced cognitive abilities and a capacity for abstract reasoning. They have a highly developed brain and have created complex societies over thousands of years. They have the unique ability of self-awareness, allowing them to understand their own thoughts, emotions, and experiences. Humans are capable of both great kindness and compassion, as well as violence and aggression.

• 7:45Speaker 06

  Part one. I think, therefore, I am.

• 7:53Speaker 06

  Wonder is the feeling of the philosopher, and philosophy begins in wonder.

• 8:04Speaker 05

  I lived in Athens then. I was like five, six years old, and it was summertime. And in Greece, they still do it. They have like open-air cinemas, right? Where in the summer, you go in an open-air cinema. There's no roof, you know, there's a screen in front of you. You sit there, you make a lot of noise. It's, it's, it's great. And my mother took me to, to watch a film that, you know, the people who had the cinema decided to show. It was an old film. It was called Forbidden Planet.

• 8:36Speaker 05

  It was all about, you know, a spaceship landing on another planet and finding this sort of this crazy scientist who had a robot. And that was the first time I actually saw a robot in my life.

• 8:50Speaker 01

  Welcome to Al-Tehor, gentlemen. I am to transport you to the residence.

• 8:56Speaker 05

  I never imagined there would be a thing.

• 8:59Speaker 01

  If you do not speak English, I am at your disposal with 187 other languages along with their various dialects.

• 9:07Speaker 05

  Made of metal, tin, that had a mind.

• 9:10Speaker 01

  You are a robot, aren't you? That is correct, sir. For your convenience, I am monitored to respond to the name Robbie.

• 9:20Speaker 05

  Ever since that moment, I was so fascinated with the idea that we can develop artifacts, artificial things, that can think, that can act, that can behave like us humans.

• 9:34Speaker 00

  It was 1969 when George watched in wonder as Robbie the robot rolled across the big screen, something that may have seemed like a far-off reality for a kid growing up in the 60s. But then again, humans had just witnessed man landing on the moon.

• 9:53Speaker 05

  I mean, that was the culmination, the realization of centuries of dreaming about going to space.

• 10:01Speaker 00

  For George and millions of others around the world, it was proof that humans can imagine and then create the capacity to transcend ourselves and that stories provide the roadmap.

• 10:14Speaker 05

  I interviewed a lot of people to see what made them become scientists or engineers. And it was always some kind of, you know, book, kind of comic, something, right, that excited them, that triggered their imagination. It could be, you know, the outer space of planets and asteroids and whatnot, but it could also be the inner space, the human body. So those stories are very powerful. And I tried to explore those stories, where they come from, what are they telling us about this desire to become, in a way, like gods?

• 10:56Speaker 05

  So, you know, Big Bang of the Universe, whatever was before, something happened, it changed. Boom.

• 11:05Speaker 05

  We have something different now. Protons and, I don't know, dogs, cats, you and me, whatever.

• 11:15Speaker 05

  Our species has been around, probably for maybe 300, 400,000 years. And yet, for most of that time, we're doing, you know, chiseling some stones, hunting some animals, you know, living very simply in caves. Not a lot was happening.

• 11:35Speaker 05

  And then around 14,000, 60,000 years ago,

• 11:40Speaker 05

  boom.

• 11:46Speaker 05

  The Big Bang of the human mind.

• 11:52Speaker 05

  Something amazing happens, and our ancestors, across the world, by the way, right? Start creating art. Start to narrate, to tell stories about how they experienced the world.

• 12:08Speaker 05

  When love beckons to you, follow him,

• 12:11Speaker 04

  though his ways are hard and steep. Through these stories, we project our hopes, fears, and dreams onto the canvas of the invisible unknown. All the Earth is a grave,

• 12:24Speaker 05

  and nothing escapes it. And that meant also that we were able to transfer information and knowledge to the next generation.

• 12:34Speaker 04

  The divine gift does not come from a higher power,

• 12:41Speaker 04

  but from our own minds.

• 12:44Speaker 05

  And that's what kicked off this amazing journey of our species to where we are today.

• 12:55Speaker 05

  What seems to have happened is some kind of genetic mutation that furnished us, our species in particular, with the ability of language.

• 13:09Speaker 04

  Language and stories. We know they're part of what makes us human. But what else?

• 13:22Speaker 07

  How did it begin?

• 13:26Speaker 07

  People somehow think maybe we knew about DNA for the last several centuries. We didn't. It really wasn't that clear what was the hereditary material that passes from parent to child and that carries all those genetic factors.

• 13:40Speaker 00

  This is Francis Collins. Maybe you've heard of him. But in case not, I asked ChatGPT to write up a bio. Here's what it gave me. Francis Collins is a renowned physician geneticist. He earned his MD and PhD at Yale University and is best known for his leadership of the Human Genome Project, a landmark international research effort to decode the entire human genetic blueprint.

• 14:05Speaker 07

  The people at the University of North Carolina will be upset to hear that ChatGPT said, "I got my MD from Yale," but that's okay.

• 14:15Speaker 00

  Oh, so there's an error in there.

• 14:17Speaker 07

  There is an error.

• 14:18Speaker 00

  Were there any other mistakes?

• 14:19Speaker 07

  It was a bit of an omission. I don't think there was any mention of the 12 years I spent as the director of the National Institutes of Health under three presidents, but that's okay.

• 14:31Speaker 00

  We asked ChatGPT to comment on its error. I apologize for any errors in the biography of Francis Collins. As a language model, I am trained on a large data set of text. I may make mistakes or omissions. I recommend fact checking any information that I provide. Don't worry, we will.

• 14:52Speaker 04

  So much of the driving force behind Collins's work is trying to understand what makes humans human, like at the most basic molecular level, but also beyond that. Growing up in the 1950s, he was amazed by the recent discovery of the structure of DNA.

• 15:11Speaker 07

  There were covers of Life magazine saying, "Discovering the Secret of Life."

• 15:15Speaker 06

  Was it actually discovering the secret of life?

• 15:18Speaker 07

  It's maybe a little over the top because I actually think there's more to life than just molecules. But certainly, if you want to talk in the biological basis of life, yeah, this was discovering that. It's kind of, you know, the book of life that's inside each cell. It's incredibly inspiring to think about this, and it is the same kind of molecule that all living things on this planet use. Another reason to be pretty sure that we're all descended from some common ancestor and that as this information molecule evolved over time, it took on different letters and different orders, but it was still that double helix with all of that potential.

• 15:59Speaker 04

  Potential. Part of what this discovery did was show us humans a way into understanding things about ourselves we hadn't yet discovered. And Collins believed to further unlock the secrets of who we are, we needed to decode our genetic programming.

• 16:15Speaker 07

  The big question was, okay, this is a book. We are information organisms, and this is our information source. It's digital, but it's not actually carrying out the actions. How does that happen? How do you take this information and cause a cell to actually do something? If we were going to get that intelligent about our own instruction book, maybe we could not just read it, but we could actually occasionally figure out how to do a find and replace when something was misspelled. It was clear to me, if we want to do this, we've got to have a better database to work with. We need the human genome. That became my dream.

• 16:56Speaker 01

  If you're talking about what you can feel, what you can smell, what you can taste and see, then real is simply electrical signals interpreted by your brain. This is the world that you know.

• 17:22Speaker 00

  of the sage computer. Every instrument in this room is constantly monitoring, testing, pulse-taking, controlling.

• 17:36Speaker 00

  This era, when humans were seeking mastery of the sky and the body, was in many ways dependent on another groundbreaking technology of the time, an additional brain that can work faster than ours, but does what we wish we could do: the computer.

• 17:53Speaker 05

  In the old days, the word "computer" usually meant a person, usually a woman, actually, that sat down and did mathematical calculations, by hand, okay? And by rule, a ruler, right? And then that word "computer", which described a human being, was transposed into the machine, because the machine can do it better.

• 18:15Speaker 06

  So the mainframe computers would only fit in these massive rooms in the basement, which is fitting because these devalued laborers who did the actual programming work were down there.

• 18:28Speaker 06

  My name is Stephanie Dick, and I'm an assistant professor in the School of Communication at Simon Fraser University.

• 18:34Speaker 00

  She holds a PhD in the history of science with a specialization in the history of mathematics and computing.

• 18:43Speaker 06

  These machines produced massive amounts of heat and noise. And working with them, you had to carry these boxes of punch cards back and forth as input and output and stick it into the machine. This is like a sweatshop. Everything was really slow, very different from the machinery that we're all used to today, which is almost as fast as light and, you know, conforms to our every demand.

• 19:12Speaker 06

  You know, the most disturbing part of the history of AI for me comes from the fact that these men who were working in artificial intelligence looked at those massive, noisy, hot, mainframe computers and saw themselves in it. They looked at them and identified a deep affinity, that there was something fundamentally shared between their minds and these machines.

• 19:42Speaker 04

  Coming up, as we unlock the secrets of man and machine, we ask the question, will this knowledge bring us closer to perfection or destruction?

• 19:59Speaker 04

  Hi, this is Christopher from Los Angeles, California.

• 20:02Speaker 00

  I love throughline because it is always informative and keeps me alive. Stay tuned for the following announcements and messages from our sponsors. This message comes from Live Right, publisher of John U. Bacon's New York Times bestseller, The Gales of November, a chronicle of the S.S. Edmund Fitzgerald's 1975 shipwreck.

• 20:24Speaker 06

  Never has it been told better than by Mr. Bacon in this colorful book, writes John J. Miller of The Wall Street Journal, while author Hampton Sides proclaims it's destined to be a classic. The Gales of November, now in paperback. This week on the NPR Politics Podcast, the midterm elections are wrapping up and millions of people have already voted. We're taking one final check of the electoral pulse with a new NPR PBS News Marist Poll. It shows Democrats still poised to make gains, but also with some warning signs for just how many. We'll explain on the NPR Politics Podcast.

• 21:02Speaker 07

  Oh, Kevin, it feels good to be back.

• 21:04Speaker 01

  It sure does, Casey. And what a time. The world is talking about AI and what's going on in Silicon Valley. And we are here with a new show to tell you all about it.

• 21:13Speaker 07

  That's right, Kevin. On our new show, Machine Gods, twice a week, we'll be bringing you the biggest news in tech and bring you unmatched access to the real titans of this industry.

• 21:21Speaker 01

  You can find Machine Gods from NPR on the NPR app or wherever you get your podcasts.

• 21:29Speaker 00

  What is a machine?

• 21:34Speaker 00

  A machine is a device that can perform specific tasks more efficiently or with greater precision than humans can do alone. The basic idea behind the machine is to make work easier. Humans have been creating machines for thousands of years, starting with simple tools like the wheel and advancing to complex machines like computers and robots. The relationship between humans and machines continues to evolve and is likely to become increasingly important as advances in artificial intelligence continue to shape our world.

• 22:08Speaker 03

  A more perfect human.

• 22:13Speaker 03

  It's 1956. It's summer. It's the Dartmouth Math Department. And everybody has left, so the department is empty. And 10 men get together to invent the field of artificial intelligence.

• 22:32Speaker 06

  It was instigated by John McCarthy, who was a mathematics professor at Dartmouth. The proposal that John McCarthy wrote pulls no punches at all. Quote,

• 22:43Speaker 03

  "We propose that a two-month, 10-man study of artificial intelligence be carried out during the summer of 1956 at Dartmouth College in Hanover, New Hampshire."

• 22:54Speaker 06

  Second sentence.

• 22:56Speaker 03

  "The study is to proceed on the basis of the conjecture that every aspect of learning

• 23:01Speaker 06

  or any other feature of intelligence can, in principle, be so precisely described

• 23:08Speaker 03

  than a machine can be made to simulate it."

• 23:11Speaker 06

  So, right from the beginning, there's this pronouncement that human learning and intelligence can be mechanized and automated.

• 23:19Speaker 03

  It fascinates me. It's an enormously grandiose idea.

• 23:24Speaker 03

  My name is Meredith Broussard. I'm a data journalism professor at NYU, and I'm the author of More Than a Glitch: Confronting Race, Gender, and Ability Bias in Tech. Something else that I think was really interesting about this conference is they decided on the name Artificial Intelligence as the name of their new field. I think the name was chosen aspirationally. Most of the people who are at the forefront of artificial intelligence are great consumers of and lovers of science fiction. And so, there's a lot of desire to make science fiction real, that you're going to make a sentient machine.

• 24:16Speaker 06

  The Dartmouth Conference has become an origin myth commemorated with a plaque and everything. On this site, artificial intelligence was born. But in practice, the conference was a bit of a flop, actually. There was a lot of conflict and tension and disagreement, and there wasn't actually a coherent field that emerged out of the conference. Of course, the origin myth served to empower these men to tell their own story, and it's a story full of erasure.

• 24:49Speaker 06

  We hear nothing in that origin myth about the relationship that AI has to industrialization, or to capitalism, or to these colonial legacies of reserving reason for only certain kinds of people and certain kinds of thinking.

• 25:16Speaker 04

  That deeper story takes us back to the early days of industrialization. In the late 1700s and early 1800s, factories started popping up across the world, reshaping the nature of work. More and more tasks that had once been done only by human hands were now the work of machines.

• 25:37Speaker 06

  Over in England, Charles Babbage, English mathematician, was touring factories in the context of industrialization and thinking, "Wow, these factories can tell us something about the human mind, because they tell us about how processes can be broken down and what the elementary steps even of thought might be." So we also see in this moment a kind of devaluation of the classes of people and/or machines who do this sort of repetitive mechanical, broken-down labor in service of efficiency and profit maximization in industrialization and early capitalism.

• 26:25Speaker 06

  Babich was really dismissive of working-class people. He thought they were annoying and filthy, and they were always making noise and singing songs. And said famously, "I wish to God these calculations had been produced by steam," by which he meant the steam engine, which was driving factory automation at the time.

• 26:46Speaker 05

  People have been playing around with what is called automata, essentially machines that would automatically do something simple for centuries.

• 26:58Speaker 04

  This is George Zarkadakis again.

• 27:01Speaker 05

  So there was always this idea of replicating nature, replicating movement, because movement was related to life.

• 27:12Speaker 05

  I think the Industrial Revolution was in many ways a culmination of all those ideas that have been, people have been experimenting on and off for at least 2,000 years.

• 27:23Speaker 07

  Our blowers will destroy their whole modern industrial plant and organization.

• 27:30Speaker 05

  Something happened to our collective psyche after the atom bomb.

• 27:35Speaker 07

  At zero minus 15 seconds, a warning tone sounds in the plane.

• 27:41Speaker 07

  They hoped that it would put an end to this war, put an end to a butchery that had been going on for many years.

• 27:57Speaker 05

  Until then, everybody was excited about the new things and about new discoveries and about new technologies. And then we discovered something that can destroy us completely. And it was terrifying.

• 28:11Speaker 05

  I still remember the day very well. Because this was a river filled with dead bodies. And I think that's when people realized that maybe there are some technologies that are not for good. And that's when we became gradually, as you know, as public, more skeptical to technologies.

• 28:35Speaker 03

  But some elite academics and scientists believed that better technology was actually the key to our future because it could help us bypass the messy parts of being human.

• 28:46Speaker 06

  What if human decision-making procedures were too slow? What if people's judgments are clouded by their emotions?

• 28:52Speaker 03

  To give us more control over ourselves and the world around us.

• 28:56Speaker 06

  Our machines will churn out the right answers and the right decisions and the right judgments.

• 29:02Speaker 03

  And in effect, replace God with science.

• 29:06Speaker 06

  And it's such a confident moment in American academia.

• 29:13Speaker 06

  After the war, there was more money, there were more people, there was more cultural capital, more political capital for science and technology than ever before. There's also a real concern about the practicalities of preventing a nuclear war, which was a very real threat at that time. We all know the atomic bomb is very dangerous. That's why these children are practicing to duck and cover. We hope it never comes, but since it may be used against us, we must get ready. Nuclear détente, and in particular mutually assured destruction, rely very specifically on information processing capability.

• 29:55Speaker 06

  You need to know where your enemy's nuclear arsenals are. You need to know if you've been attacked or that you were about to be.

• 30:04Speaker 05

  And the argument went that if the United States could have a system that could think, that could strategize, that could react more intelligently than a group of generals and admirals, then we would have a clear advantage over the Soviet Union.

• 30:25Speaker 06

  The fear that people were too limited to be trusted to preserve peace. So let's double down on high technological hyper rationalism.

• 30:36Speaker 05

  And that's how artificial intelligence came about.

• 30:40Speaker 07

  Your scientists were so preoccupied with whether or not they could, they didn't stop to think if they should.

• 30:51Speaker 04

  Which brings us back to that famous Dartmouth Conference in the summer of 1956. With the Cold War driving interest in artificial intelligence, there was a lot of money up for the taking. And a conference of mathematicians and scientists from top-tier universities and labs seemed like a pretty good investment.

• 31:10Speaker 06

  There was exactly one running computer program that was operational and presented at the conference, and it was the logic theory machine that had been developed by Alan Newell and Herbert Simon at the Rand Corporation. And it enshrined a particular vision of the human mind. Herbert Simon is famous for saying that human minds and modern digital computers are "species of the same genus." They are fundamentally the same, just a symbol processing machine that takes symbolic information as input, manipulates it according to a set of rules, and outputs decisions, solutions, judgments, and so on.

• 31:54Speaker 06

  Bodies don't matter. Society doesn't matter.

• 31:57Speaker 04

  One proposed measure of machine intelligence was something called the Turing Test, named for its creator, British mathematician Alan Turing, who you might remember from the movie The Imitation Game. Would you like to play? Play? It's a game.

• 32:15Speaker 06

  A test, of sorts, for determining whether something is a machine or a human being. It was based on a parlor game for swapping gender that says a man and a woman leave the room, and the partygoers have to figure out who's the man and who's the woman by sending questions back and forth on paper. And the man's job is to try to pretend to be the woman, and the woman's job is to be herself. And he says, "What if we took the same test and replaced the man by a computer and the woman by any person?" And then the judge, of course, is meant to be able to figure out whether the machine is the human or the human is the human.

• 32:57Speaker 06

  And what I have always found so shocking about the Turing test is that it reduces intelligence to telling a convincing lie, to putting on the performance of being something that you're not.

• 33:12Speaker 06

  From the beginning, with this disembodied conception of intelligence, the question that Turing posed, what can the mind do without a body, and therefore, what might the machine do, since it doesn't have one, chess was one of the first answers given.

• 33:29Speaker 03

  Why did they pick chess? Well, the early days of artificial intelligence and the early days of computing are dominated by men, mostly white men, who were educated at elite institutions.

• 33:47Speaker 04

  Skill at chess was considered a universal marker of intelligence.

• 33:51Speaker 06

  White men wanted to call themselves universal and produce themselves in the machine.

• 33:58Speaker 03

  The problem is that this small and homogeneous group of people has common biases, and people embed their own biases in technology. And so we see the blind spots of the creators then reflected in the technological artifacts that they create.

• 34:23Speaker 04

  They had all this hope and optimism about how fast they could accomplish their sci-fi-inspired dreams of a sentient machine, a machine that could beat a human at chess. But from the 1970s to the 1990s, it was a cycle of hype and disappointment. The technology was just not there yet, and eventually, the funding dried up. Periods like this came to be known as AI winters.

• 34:48Speaker 06

  I hesitate to use the term, in part because outside of the United States, it was the 80s and 90s that really led to a burgeoning of AI research in other parts of the world, including both China and Russia. So it may have been a winter in America, but it was a time of great creation and creativity in other parts of the world.

• 35:10Speaker 00

  The early pioneers of the field had underestimated the complexity of humans and overestimated the capabilities of machines.

• 35:19Speaker 06

  I think underneath all of that arrogance and hubris is a real lack of faith in people.

• 35:27Speaker 07

  He rejected everything that did not contribute directly to the progress of work. In fact, he rejected the man and made the robot.

• 35:37Speaker 05

  The word "robot" means worker.

• 35:39Speaker 06

  It's a translation of the Slavic word for a serf, for a slave, for a servant. It originated in-

• 35:45Speaker 05

  In the early 20th century.

• 35:47Speaker 06

  Carl Kapek's play R.U.R., Rossum's Universal Robots.

• 35:50Speaker 05

  Rossumovi univerzalni roboti. Who imagined the future and imagined artificial humans. And they were manufactured.

• 36:01Speaker 07

  His sole purpose was nothing more or less than to prove that God was no longer necessary.

• 36:10Speaker 00

  In 1920, decades before the Dartmouth Conference, before the atomic bomb, before the mainframe computer, Rossum's Universal Robots grappled with the costs and consequences of treating workers as nothing more than their parts. It was an indictment of the exploitation and oppression that people had experienced for centuries in the name of progress. A mistake which, in the play, man was repeating with machines.

• 36:37Speaker 07

  The robots are not people.

• 36:38Speaker 06

  Robots are so-

• 36:39Speaker 07

  Mechanically, they are more perfect than we are. They have an enormously developed intelligence. But they have no soul, ala nemay dushi.

• 36:49Speaker 00

  At the end of the play, the robots have brought about the downfall of humanity. Yet, unable to reproduce, their days are numbered. But then, two robots awaken to each other's presence and discover emotions previously thought exclusive to humankind. Love blossoms between them, and a soul stirs within.

• 37:16Speaker 04

  The soul is not often a subject for science. But long before he became a geneticist, Francis Collins started to wonder if we had to grapple with that big unknown in order to better understand who we are as human beings.

• 37:32Speaker 07

  I went to medical school, and I found my atheism wasn't feeling like it settled very well when I was sitting at the bedside of good, honorable North Carolina people who were dying of diseases that we didn't have much to offer. And I wondered how I would handle that and figured, for some of these people, clearly their faith was a source of great comfort. So I began a two-year journey to try to understand, why did people believe in God? Ultimately, I began to realize the impoverishment that I felt from considering human beings solely as mechanical entities, and the appeal of the notion that there was something outside of that

• 38:16Speaker 07

  that fits into things like love and beauty, altruism and goodness and morality. Does our DNA tell us that that beautiful sunset was something to stop for just a moment and be a little bit in awe?

• 38:36Speaker 07

  Does the way in which listening to Beethoven's Third Symphony bring me to tears? Is that written in my DNA? What is that about?

• 38:55Speaker 00

  Coming up, we enter a new era where the souls of man and machine might converge.

• 39:18Speaker 07

  Hi, this is Chelsea. And Katie, calling from Philly. You're listening to NPR's Throughline.

• 39:26Speaker 07

  Stay tuned for the following announcements and messages from our sponsors. This message comes from Live Right, publishers of John U. Bacon's New York Times bestseller, The Gales of November, a chronicle of the S.S. Edmund Fitzgerald's 1975 shipwreck. The Gales of November, in paperback wherever books are sold. Midlife brings a lot of changes. Your Turn with Alison Aubrey is a new podcast to help you navigate the twists and turns.

• 39:54Speaker 03

  From health and relationships to creativity and purpose, we can help steer your next chapter with Your Turn with Alison Aubrey. Find it on the NPR app or wherever you get your podcasts. Support comes from NPR sponsor AARP.

• 40:08Speaker 07

  This midterm election season, let the NPR app be your guide for clear, independent coverage. You'll find big picture analysis, stories from your community, and learn what to watch for on election night and beyond. Head to the polls and stay informed this midterm election season. Download the NPR app at npr.org/2026election. Everything you need in one place.

• 40:37Speaker 00

  Can you tell me the story of your ancestor, Deep Blue?

• 40:44Speaker 00

  Certainly.

• 40:47Speaker 00

  Part Three: Souls of Silicon.

• 40:52Speaker 00

  The match was held on the 35th floor of a skyscraper in downtown Manhattan with a large crowd of onlookers and a throng of journalists and cameras.

• 41:02Speaker 00

  Garry Kasparov, considered one of the greatest chess players of all time.

• 41:07Speaker 07

  Yes, I was confident. Yeah, that's the, that's confident arrogance. Let's, let's remember that before 1997, I haven't lost a single match, period. I was unbeatable at the chessboard.

• 41:19Speaker 00

  He went up against the machine, IBM's supercomputer, Deep Blue, capable of analyzing 200 million positions per second. Last year in Philadelphia, Kasparov won against a slower, weaker version of Deep Blue. This rematch, played in Manhattan, was seen as the ultimate test of man against machine.

• 41:40Speaker 07

  I couldn't say I know, it was too tempting. You know, it's just it's understanding better relations between humans and computers, you know, would be very important for our progress. Trying, you know, just to find out, so what are the limits of computers?

• 41:53Speaker 00

  The atmosphere was tense as the players sat down at the chessboard. Kasparov with a focused, determined expression. And Deep Blue with its bank of blinking lights and silent fans. The game began. Kasparov made his first move with a steady hand. Deep Blue responded with a move of its own. Calculated with lightning speed.

• 42:16Speaker 00

  It became clear that both players were evenly matched. Kasparov's experience and intuition were met with the machine's raw computational power and ability to analyze large amounts of data.

• 42:28Speaker 05

  The bishop can easily fall victim to what we call an overload tactic. When one piece has to deal with so many pieces.

• 42:41Speaker 07

  I grew up in the city of Baku, in the deep south of the USSR. Watched my parents trying to solve chess puzzles.

• 42:52Speaker 07

  I cannot give you any more information because nobody was there to tweet about this moment when Garry Kasparov discovered chess. And I climbed very rapidly on this chess ladder.

• 43:07Speaker 01

  So how is Kasparov going to draw up some sort of miracle attack from this position? Those pawns pushing, Danny, they look frightful. He's famous for sudden tactical swoops. To keep moving in. Intricate traps. Rook takes knight, my god.

• 43:19Speaker 07

  I was the junior champion under 18 of the USSR at age 12. At 17, the world champion under 20. And at 22, world champion. And kept the title for 15 years. It seems everybody is interested now in home computers. From the onset of the computer science, they all thought about chess, the game of chess, as being an ultimate test for machines intelligence. Even before my famous matches with Deep Blue.

• 43:47Speaker 05

  In 1996, 997, we, when I say we, top players, we already suffered some of the defeats against these chess engines in blitz, 5-minute chess, or in rapid chess, 25-minute chess.

• 44:02Speaker 05

  So when I faced Deep Blue, it was already, you know, like a sign on the wall.

• 44:08Speaker 05

  Gary is not, he looks, I mean, he looks, we, we very... I, what, are we missing something on the chessboard now that Kasparov sees?

• 44:19Speaker 00

  In the end, it was Deep Blue who emerged victorious.

• 44:22Speaker 05

  And whoa, Deep Blue, Kasparov, after the move c4, has resigned.

• 44:31Speaker 00

  With Kasparov conceding defeat after the machine's 19th move in the sixth game. The match was a historic moment, marking the first time a machine had defeated a reigning world champion in a match under tournament conditions.

• 44:50Speaker 05

  I was really, you know, furious and I wanted to, to, to, to come back and just to tear this machine down.

• 44:58Speaker 05

  It was painful, I was really angry, but mostly with myself.

• 45:04Speaker 05

  So it, it, it was a clear sign for me that the history of us competing with machines will be over soon.

• 45:15Speaker 06

  There's a lovely article that comes out in the New York Times in the wake of Kasparov losing, that says, "Well, it makes sense that the computer won at chess. Chess is a small problem, but I want to see if a computer will ever be able to beat a world champion at the game Go, for which there are more board positions than atoms in the universe." And it's a really exact and clear example of the so-called receding horizon, where people really want to reserve something for ourselves that is not mechanizable. What is it that is uniquely human? Maybe it's our ability to write a poem.

• 45:56Speaker 06

  Or maybe it's intuition, whatever that is.

• 46:00Speaker 06

  Maybe it's certain forms of creativity or certain types of emotion. And then people try to automate those things.

• 46:10Speaker 06

  We then redefine our humanness again and again.

• 46:17Speaker 04

  Krasparov's defeat marked a turning point. A computer had beaten a human at a game humans taught it to play. For scientists, it was a sign that maybe it was time to stop competing with machines and start collaborating with them.

• 46:40Speaker 07

  He felt that he had learned the language in which God created the universe.

• 46:50Speaker 07

  Today, we are learning the language in which God created life.

• 47:07Speaker 07

  Now, I'd like to invite Dr. Francis Collins to the lecture. So, Dr. Collins. I had plenty of occasions to imagine having to give the speech where I would say, basically, we failed, we give up.

• 47:20Speaker 00

  When geneticist Francis Collins and his team first embarked on the Human Genome Project, it was a daunting task. They wanted to map out the order of the 3 billion base pairs that made up a tiny molecule, our DNA. In just over a decade, they did it.

• 47:38Speaker 07

  Mr. President, distinguished ambassadors, ladies and gentlemen. It is truly a humble, humbling, and profound experience to be asked to speak here this morning. On June 26, 2000, in the East Room of the White House, I had my chance to talk about what this meant and to give a big shout-out to those 2,400 scientists who made it possible. And I think all of us, one level or another, we're also thinking about this in terms of its implications for who we are, maybe even theologically. We are doing something pretty profound here that's never been done by any species on this planet, or maybe in the universe.

• 48:21Speaker 07

  We're reading our own instruction book, and we're part of that, and we're watching it emerge day by day, and putting all that information up on the internet as fast as we get it.

• 48:33Speaker 06

  During that same time, hardware gets way cheaper, computers proliferate.

• 48:38Speaker 03

  And there was a big breakthrough in a subfield of artificial intelligence called neural nets. This ushered in this new era in artificial intelligence, the era of machine learning.

• 48:58Speaker 06

  So what if we didn't try to model the human mind first? What if we didn't try to encode human knowledge first? What if we let the computer learn on its own?

• 49:08Speaker 03

  What you do when you build one of these systems is you get a ton of data and you feed it into the computer and you say, "Computer, I want you to create a model of the patterns that you see in the data." And the computer very obligingly makes a model of the mathematical patterns that it sees in the data.

• 49:32Speaker 06

  These massive data sets were suddenly feasible to store and process in computer memory, which had sort of been prohibitively expensive before.

• 49:44Speaker 07

  It's the beginning of a future of medicine. It's the end of ignorance. Gene-based medicine. Drug discovery, drug development, and curing diseases.

• 49:54Speaker 01

  Some have said to me that sequencing the human genome will diminish humanity by taking the mystery out of life. You know, we're chemical computers. This is the program that runs us. Nothing could be further from the truth.

• 50:09Speaker 06

  There's a deep desire for the human condition not to be a deterministic output of our chemical or genetic or cultural forces.

• 50:23Speaker 06

  But for there to be something that allows for free will and surprise and creativity that belongs to us.

• 50:30Speaker 03

  Math is a system of symbolic logic. It is not the indefinable thing that makes us human.

• 50:41Speaker 03

  And when you are building a computer program, it'll work if you do it this way, and then it won't work if you do it the other way. But that's not how culture operates, right? That's not how relationships work.

• 50:59Speaker 03

  So there's really a fundamental difference between what we can do with computers and what we can do in society. Because when it comes right down to it, computers are machines that do math. They compute. And we forget that when we get grandiose about artificial intelligence and we get grandiose about our imaginings.

• 51:19Speaker 06

  And I'm just imagining a world in which, you know, you have more intelligent machines operating on humans. Are the decisions those machines are making in those moments, which, you know, for humans, for example, you might make informed by instinct. Without that, you know, is something missing?

• 51:41Speaker 07

  Or without that, are you making fewer mistakes? Sometimes the gut feeling is not one you should have followed.

• 51:50Speaker 05

  So Dr. Frankenstein, you know, creates life, right, out of dead matter. In a way, that's what we do with AI as well. We take dead matter, it's like silicon chips and wires and metals and whatnot, you know, and put them together and then, you know, coat them and boom.

• 52:10Speaker 07

  Artificial intelligence is becoming a sort of black box with law enforcement. Google uses AI and misinformation spreads wildly on Google. The Chinese Communist Party is using this technology to build the ultimate surveillance state.

• 52:25Speaker 07

  Look, I'm incorrigible optimist by nature. So that's why, yeah, I grew up in the Soviet Union, yes, and I saw the

• 52:32Speaker 04

  Collapse of democracy in Russia. And I still believe that, you know, the history of humanity gives us reasons to be optimistic.

• 52:40Speaker 05

  I'd like to imagine a future where we have built, we have developed human systems that bring the best out of us rather than the worst out of us.

• 52:52Speaker 04

  I think it's a time where we have to reconsider, you know, this is how in this new environment, which is dominated by computers, we can find a robust democracy. Because humans still have monopoly for evil.

• 53:07Speaker 04

  And that's why, you know, let's stop worrying about the terminators and metrics. Let's recognize that it's about us.

• 53:15Speaker 04

  A machine is like a mirror. And if you don't like what we see in the mirror, you have two choices. Either you can work on your body to improve the picture or you can try to distort the mirror.

• 53:27Speaker 04

  The latter decision is just, it's a risk for disaster.

• 53:46Speaker 03

  That's it for this week's show. I'm Rund Abdelfatah.

• 53:50Speaker 04

  I'm Ramtin Arablouei. And you've been listening to Throughline from NPR.

• 53:55Speaker 03

  This episode was produced by me.

• 53:57Speaker 04

  And me and?

• 53:59Speaker 00

  ChatGPT. Lawrence Wu. Zhu Li-Kane. Anya Steinberg.

• 54:03Speaker 06

  Yolanda Sangweni. Casey Miner. Kristina Kim. Devon Karyama.

• 54:09Speaker 04

  Yordanos Tisfazion. Fact checking for this episode was done by Kevin Vogel.

• 54:14Speaker 03

  Thank you to Olivia Chilcote, Devon Karyama, Shahir Khan, and Magdalena Devojakva for their voiceover work.

• 54:22Speaker 04

  Thanks also to the Clinton Presidential Library, YouTube creator Brian Kay, Micah Ratner, Rachel Sellar, Taylor Ash, Olivia Chilcote, Ryan Mitchell, Tamar Charney, and Anya Grunman.

• 54:35Speaker 03

  This episode was mixed by Alex J. Wenskis. Music for this episode was composed by Ramtin and his band, Drop Electric, which includes?

• 54:43Speaker 00

  Anya Misani.

• 54:45Speaker 02

  Naveed Marvi.

• 54:46Speaker 04

  Sho Fujiwara. And finally, if you have an idea or like something you heard on the show, please write us at [email protected].

• 54:55Speaker 03

  Thanks for listening.

• 55:04Speaker 06

  Stay tuned for the following announcements and messages from our sponsors. Midlife brings a lot of changes. Your Turn with Alison Aubrey is a new podcast to help you navigate the twists and turns. From health and relationships to creativity and purpose, we can help steer your next chapter with Your Turn with Alison Aubrey. Find it on the NPR app or wherever you get your podcasts.

• 55:30Speaker 00

  This message comes from Capella University. That spark you feel? That's your drive for more. Capella University's FlexPath learning format lets you earn your degree at your pace without putting life on pause. Learn more at capella.edu.