A More Perfect Human

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And then around 14,000, 60,000 years ago, boom. The big bang of the human mind. Something amazing happens, and our ancestors across the world, by the way, right, right, start creating art, start to narrate, tell stories about how they experience the world.

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When love beckons to you, follow, though his ways are hard and steep. Through these stories, we project our hopes, fears and dreams onto the canvas of the invisible unknown.

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All the earth is a grave, and nothing escapes it.

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And that meant also that we were able to transfer information and knowledge to the next generation. The divine gift does not come from our higher power, but from our own mind. And that's what kicked off this amazing journey of our species to where we are today.

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So much of the driving force behind Collins' 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.

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There were covers of Life magazine saying, discovering the secret of life.

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Was it actually discovering the secret of life?

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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 on a biological basis of life, yeah, this was discovering that. It's kind of 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.

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Potential.

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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.

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

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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. You know, the most disturbing part of the history of AI for me comes from the fact that these men who are 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.

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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?

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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.

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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.

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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.

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

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This is George Zarkadakis again.

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So there was always this idea of replicating nature, replicating movement because movement was related to life. I think industrialism was in many ways a culmination of all those ideas that have been, people have been experimenting on and off for at least 2000 years.

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

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Something happened to our collective psyche after the atom bomb.

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

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They hoped that it would put an end to this wall, put an end to a good tree that has

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And it's such a confident moment in American academia. 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 detente and in particular mutually assured destruction rely very specifically on information processing capability. You need to know where your enemies nuclear. Arsenal's are, you need to know if you've been attacked or that you were about to be.

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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.

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

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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 quote-unquote 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. Bodies don't matter, society doesn't matter.

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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.

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Would you like to play?

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Play. It's a game. A test of sorts.

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If you're 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 party goers 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?

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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.

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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.

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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.

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

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

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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.

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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 impoverishness that I felt from considering human beings solely as mechanical entities and the appeal of the notion that there was something outside of that 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 kind of be a little bit in awe? 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?

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Some have said to me that sequencing the human genome will diminish humanity by taking the mystery out of life. And we're chemical computers.

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This is the program that runs us.

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Nothing could be further from the truth.

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There's a deep desire for the human condition not to be a deterministic output of our chemical or genetic or cultural forces, but for there to be something that allows for free will and surprise and creativity that belongs to us.

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Math is a system of symbolic logic. It is not the indefinable thing that makes us human. 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. That's not how relationships work. So there's a 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.

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And I'm just imagining a world in which you have more intelligent machines operating on humans are the decisions those machines are making in those moments.

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

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

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So Dr. Frankenstein creates life 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. And put them together and then coat them and boom.

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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.

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Look, I'm incorrigible optimist by nature. So that's why I grew up in the Soviet Union. Yes, and I saw the collapse of democracy in Russia. And I still believe that, you know, the history of humanity gives us reasons to be optimistic.