Speaker 1: Will writers and artists and musicians become unemployed by AI?
Speaker 1: What are the new capabilities that we're seeing all around us,
Speaker 1: and what is this.
Speaker 2: Going to mean for human creativity?
Speaker 1: And what does this have to do with diamonds and
Speaker 1: Westworld and effort and Frankenstein in Beethoven and the Stark
Speaker 1: Family and Game of Thrones. Welcome to Inner Cosmos with
Speaker 1: me David Eagleman. I'm a neuroscientist and an author at
Speaker 1: Stanford University, and in this episode, I get to dive
Speaker 1: into something that's right at the intersection of science and creativity.
Speaker 1: Most of my podcasts are about evergreen topics about our
Speaker 1: brains and our psychology, but there's something so extraordinary happy
Speaker 1: right now.
Speaker 2: We're in the middle of a revolution with AI, and
Speaker 2: what's called generative AI in particular. So I'm going to
Speaker 2: do a two part episode on this. For today, I'm
Speaker 2: going to dig into what generative AI is and what
Speaker 2: it means for human creativity, and then in the next episode,
Speaker 2: I'm going to tackle the question of sentience. Are these
Speaker 2: ais conscious and if not, now, could they be soon?
Speaker 2: And how would we know when we get there?
Speaker 1: So let's start in twenty seventeen when almost no one
Speaker 1: in the world paid attention when a team at Google
Speaker 1: Brain introduced a new way of building an artificial neural network.
Speaker 1: So this was different than the architectures that came before it,
Speaker 1: which were called things like convolutional neural networks and recurrent
Speaker 1: neural networks. Instead, they presented a new model that was
Speaker 1: called a transformer. Now, transformer is not one of those
Speaker 1: robots that shapeshift into trucks and helicopters.
Speaker 2: Instead, a transformer model is.
Speaker 1: A way to tackle sequential data like the words that
Speaker 1: are in a sentence or the frames in a video.
Speaker 1: And a transformer model takes in everything at once, and
Speaker 1: it essentially pays attention to different parts of the data.
Speaker 1: And this allows training on enormous data sets, bigger than
Speaker 1: what was trained on before. Like now it's essentially everything
Speaker 1: that has been written by humans that is on the Internet,
Speaker 1: which is petabytes of data. So these models they digest
Speaker 1: all of that and what do they do. They essentially
Speaker 1: look at a sequence of inputs like the words and
Speaker 1: a sentence, and they ask what word is most likely
Speaker 1: to come next in that sequence. Now we'll come back
Speaker 1: to that in a second, but I just want to
Speaker 1: note that this transformer model is finding uses way beyond text. So,
Speaker 1: for example, a recent Nature paper used this kind of
Speaker 1: model to look at amino acids, which run in a
Speaker 1: sequence to make proteins, and they looked at these chains
Speaker 1: of amino acids like techt strings, and they set a
Speaker 1: major new water mark in determining how proteins fold, which
Speaker 1: is a very difficult problem. And people are using transformers
Speaker 1: for everything from making music to reading giant reams of
Speaker 1: medical records and so on. These transformer models are built
Speaker 1: into search already, and soon they're going to be in
Speaker 1: your phone and in your car, and in your bank
Speaker 1: and in your doctor's office. So what everyone in Silicon
Speaker 1: Valley is talking about is how this new kind of
Speaker 1: AI is going to disrupt the workforce. And a lot
Speaker 1: of people are thinking about white collar jobs that have
Speaker 1: traditionally required memorization of long textbooks, and these jobs, whether
Speaker 1: they're legal or medical, suddenly seem to be kind of outmoded.
Speaker 1: And so we're all thinking about what this means for
Speaker 1: the economy because so many jobs are going to be
Speaker 1: displaced by this new technology. Now, there's nothing totally new
Speaker 1: about this kind of worry, because every generation sees new
Speaker 1: technologies take over old jobs. That's natural, and we don't
Speaker 1: lament the fact that we don't have elevator operators anymore,
Speaker 1: or switchboard operators at telephone companies, or factories that make
Speaker 1: VCRs or eight track tape players, because new technologies continuously
Speaker 1: replace the old, and industries change and people adapt. But
Speaker 1: the concern that we're seeing with the AI revolution is
Speaker 1: the speed of it. It's probably the case that we've
Speaker 1: never before had a move forward in technology that's so
Speaker 1: unbelievably rapid. So this is why everyone's talking about this
Speaker 1: with a different point of view than we did with
Speaker 1: previous innovations. But I want to zoom in on something
Speaker 1: a little different for this episode. I want to know
Speaker 1: what this all means for human creativity, because the thing
Speaker 1: to note is these models have been trained up not
Speaker 1: just on the handful of novels and conversations and schoolwork
Speaker 1: that you have experienced on your thin trajectory through space
Speaker 1: and time, but they have been trained with everything that's
Speaker 1: ever been written by humans. Every textbook, every article, every poem,
Speaker 1: every blog post, every novel. We're talking seventy one billion
Speaker 1: web pages and hundreds of trillions of words, It's something
Speaker 1: that's so far beyond any human's capacity to consume even
Speaker 1: a fraction of it, or to really imagine a corpus
Speaker 1: of text that large. Oh and by the way, it
Speaker 1: has a perfect memory for every word that it's read.
Speaker 1: So now you're talking about a system that's not the
Speaker 1: same as a brain, but is incredibly powerful at generating
Speaker 1: text or visual art or music and soon video. And
Speaker 1: so while we'll talk about sentience next week, this week,
Speaker 1: I want to address a social point that has quickly
Speaker 1: risen to the surface, which is what will all this
Speaker 1: mean for human art and human creativity? Personally, I'm working
Speaker 1: on my next several books right now, and these are
Speaker 1: all projects that have spanned years, and so I'm fascinated
Speaker 1: and terrified about whether AI is going to replace me
Speaker 1: as a writer. What does this kind of new AI
Speaker 1: mean for writers, for visual artists, for musicians who studied
Speaker 1: their whole lives to be able to compose beautiful piece
Speaker 1: of music? Is human creativity destined for the dust bin
Speaker 1: of history? So let's start with the downside of these models.
Speaker 1: So in my book Live Wired, I talked about how
Speaker 1: AI algorithms don't care about relevance they memorize whatever we
Speaker 1: ask them to. So, now this is a very useful
Speaker 1: feature of AI, but it's also the reason AI is
Speaker 1: not particularly human like, because AI models don't have any
Speaker 1: sort of internal model of the world. They have no
Speaker 1: idea what it is to be a human and have
Speaker 1: drives and concerns. They don't care which problems are interesting
Speaker 1: or germane. Instead, they memorize whatever we feed them. So
Speaker 1: whether that's distinguishing a horse from a zebra in a
Speaker 1: billion photographs, or tracking flight data from every airport on
Speaker 1: the planet, or composing music in the style of Brian Eno,
Speaker 1: they have no sense of importance except in a statistical sense,
Speaker 1: which is to say, which signals occur more often.
Speaker 2: So contemporary AI could never.
Speaker 1: By itself decide that it finds irresistible a particular kind
Speaker 1: of ice cream, or that it abhors a particular kind
Speaker 1: of music, or that it's heartbroken by King Lear's speech
Speaker 1: over his dead daughter. So AI can dispatch, you know,
Speaker 1: ten thousand hours of intense practice in ten thousand nanoseconds,
Speaker 1: but it doesn't care about any zeros and ones over
Speaker 1: any others. As a result, AI can accomplish incredibly impressive feats,
Speaker 1: but not the feat of being quite like a human.
Speaker 1: And so some critics of AI say, look, it's like
Speaker 1: you want a sandwich, and what this transformer model does
Speaker 1: is it looks at all the billions of sandwiches out
Speaker 1: there in the world, and it gives you a slurry
Speaker 1: and it pours it out in.
Speaker 2: The shape of a sandwich.
Speaker 1: A fellow writer gave me that analogy the other day,
Speaker 1: and that doesn't sound particularly appealing, right, And yet these
Speaker 1: ais have massively surprised us.
Speaker 2: The text generation is so good, it's.
Speaker 1: So complete, it's so human like that we find ourselves
Speaker 1: not so much in the phase of invention like with
Speaker 1: all the machines we've made before. Instead, the whole scientific
Speaker 1: community is finding itself in a process of discovery. Everyone
Speaker 1: is exploring to find out what these enormous models are
Speaker 1: capable of, because nobody quite knows. They keep blowing our
Speaker 1: minds with things they're able to do which weren't pre
Speaker 1: programmed and not even foreseen. Have a friend who works
Speaker 1: with a big city symphony, and she's trying to play
Speaker 1: a program for the symphony several months out, which is
Speaker 1: a typical timescale for symphony planning, but she's scheduling to
Speaker 1: put on a program with music composed by AI, and
Speaker 1: she's at a loss for how to plan this because
Speaker 1: she's well aware that things are moving so fast that
Speaker 1: the musical world and the skill level of AI composition
Speaker 1: is going to be entirely different. In a few months,
Speaker 1: it's can be more advanced. So she was telling me
Speaker 1: that she doesn't quite know how to nail down plans
Speaker 1: for this, because unlike every symphony planner who has come before,
Speaker 1: she's now in a world where if she nails down
Speaker 1: a choice of music and trains up the musicians, it
Speaker 1: is guaranteed to be badly outdated some months from now.
Speaker 1: And this is the world we're operating in now. So jennertive,
Speaker 1: AI is moving so rapidly that we have entered this
Speaker 1: massive revolution without most of us realizing that we were
Speaker 1: going there.
Speaker 2: Art and writing and music aren't.
Speaker 1: Going away, but they're going to completely change from how
Speaker 1: we know them today.
Speaker 2: Now.
Speaker 1: I told you earlier that AI doesn't have any idea
Speaker 1: of what it is to be a.
Speaker 2: Human, but I think it doesn't matter.
Speaker 1: AI doesn't need to feel anything to write great literature
Speaker 1: or great art or great music, because while you can
Speaker 1: think of it as a sandwich slurry. You can also
Speaker 1: think of chat GPT as a remix of every human
Speaker 1: writer that has come before. Its training set is humankind,
Speaker 1: and so even if it's just statistical, it's generating the
Speaker 1: expressions and the passions and the fears and the hopes
Speaker 1: of millions of people. So it doesn't matter if it
Speaker 1: feels or knows or has theory of mind, or if
Speaker 1: it cries at king Lear's speech, because it can convincingly
Speaker 1: tell you a story that breaks your heart. And it
Speaker 1: does this by drawing on the best of human writing
Speaker 1: over the centuries. So as a result, it's incredibly good
Speaker 1: and it puts together things in a new way. And
Speaker 1: I think part of understanding this requires acknowledging a really
Speaker 1: important point, which is that the AI is really good,
Speaker 1: but also that humans are so easily hackable. The phrase
Speaker 1: humans are hackable is a phrase that I first started
Speaker 1: hearing from my friend Lisa Joy Nolan, who with her
Speaker 1: husband Joan Nolan, created the television show Westworld, and that
Speaker 1: was a big theme in that show. The humans could
Speaker 1: so easily get seduced by the robots, or convinced to
Speaker 1: do bad actions or act violently and the robots were
Speaker 1: just running AI. But if they say the right thing,
Speaker 1: then they can get humans to do things, whether that's
Speaker 1: fighting or fornicating or whatever. It's like turning the key
Speaker 1: in the lock. Now, there's a point that I want
Speaker 1: to dig into here. If you saw Westworld, you may
Speaker 1: remember the scene from the first episode where a man
Speaker 1: named William has just arrived to Westworld and he's greeted
Speaker 1: in a room by a beautiful woman who guides him
Speaker 1: to pick out his cowboy outfit and his gun in
Speaker 1: his hat, and she makes it clear that she's available
Speaker 1: for him sexually, and he uncomfortably asks her, are you real?
Speaker 1: And she says, if you can't tell, does it matter?
Speaker 2: Now?
Speaker 1: This is a major theme throughout Westworld. Humans are hackable,
Speaker 1: and if you can't tell the difference between something that
Speaker 1: has evolutionary importance to you and a fake version of it,
Speaker 1: then it makes no difference. And this is what we
Speaker 1: see when we look at the text that is spit
Speaker 1: out from chat GPT. It is statistically sound, meaning it
Speaker 1: falls in the orders and rhythms of millions of people
Speaker 1: who have written things like it before, and so we
Speaker 1: can be just as compelled by the text, and therefore
Speaker 1: the fact that AI can write a story that moves
Speaker 1: us and impresses us is no surprise. It's easy to
Speaker 1: move and impress us. In a sense, it's no more
Speaker 1: surprising than drawing a pornographic cartoon that turns someone on.
Speaker 1: You're just plugging into deeply carved programs. A human can't
Speaker 1: mate with the cartoon. But nonetheless, it's easy enough to
Speaker 1: activate the biological programs, so a story can make you
Speaker 1: shed tears or laugh even if the transformer is just
Speaker 1: pushing around zeros and ones. And therefore we shouldn't be
Speaker 1: surprised that AI can write these really great pieces of prose.
Speaker 1: It doesn't have to be real and it doesn't matter.
Speaker 1: So now that we can write beautiful prose with AI,
Speaker 1: what does this mean for the future of books. Well,
Speaker 1: I think we can imagine a pretty cool future for
Speaker 1: AI generated literature. We can imagine generating infinite, wonderful material.
Speaker 2: And you know what, Back in the day.
Speaker 1: Kings and emperors had poems written that were bespoke. The
Speaker 1: poems were written just for them. And now it's going
Speaker 1: to be trivial for us to all live as royalty,
Speaker 1: having bespoke literature written just for us as much as
Speaker 1: we want, as often as we want, in seconds, and
Speaker 1: maybe we'll come to enjoy dynamic novels, by which I
Speaker 1: mean a piece of literature that's not pre written, but
Speaker 1: instead is written on the fly depending on the decisions
Speaker 1: that you make, like a choose your own adventure. So
Speaker 1: you say this is a good book so far. Now
Speaker 1: I want to see what happens if I go in
Speaker 1: the neighbor's door and get a view on his life,
Speaker 1: or the mailman life who just passed by, or the
Speaker 1: traffic cop and the book just keeps writing itself on
Speaker 1: the fly, thousands of pages that end up being.
Speaker 2: Unique for me, for you, for everyone as they go
Speaker 2: on their own adventure.
Speaker 1: Instead of having some poor author who has to write
Speaker 1: every possible branching path, now there's no need to do that.
Speaker 2: You just generated on the fly.
Speaker 1: So now we'll all get to experience literary worlds that
Speaker 1: are infinite in all directions. So in that light, it
Speaker 1: certainly seems that AI is going to replace human creatives.
Speaker 1: It can do things better and millions of times faster,
Speaker 1: and it can be there to write the next pages
Speaker 1: according to your wishes. So it looks like writers are
Speaker 1: going the way of the mastodon?
Speaker 2: Or are they?
Speaker 1: I think the real story is not so simple. I'm
Speaker 1: fairly sure that while AI will augment human told stories,
Speaker 1: there's essentially zero danger that it's going to do a
Speaker 1: wholesale replacement of human creatives. And I'm going to argue
Speaker 1: this for four reasons. The first is that we care
Speaker 1: about the overarching arc of a story, and at least
Speaker 1: at the moment, AI can't even come close to constructing this.
Speaker 1: And this is because of a fundamental limitation in its architecture.
Speaker 1: And this isn't just a question of pouring more money
Speaker 1: in and getting more massive computers on the job. It
Speaker 1: has to do with the exponentially increasing computational cost of
Speaker 1: representing longer pieces of work. So currently with chat GPT four,
Speaker 1: it looks at the past four ninety six tokens, which
Speaker 1: is about three thousand words, and it decides what the
Speaker 1: most likely next word is. But without getting into the
Speaker 1: details of the math, I want to point out that
Speaker 1: this requires a matrix. Think about it like a big
Speaker 1: spreadsheet that has four thousand ninety six rows in four
Speaker 1: thousand ninety.
Speaker 2: Six columns and an entry in every cell.
Speaker 1: That represents something about the probability of those words going
Speaker 1: with each other.
Speaker 2: Now, this matrix will grow larger.
Speaker 1: With time, but the size of the output is inherently
Speaker 1: constrained by this structure, and as a result, chat GPT
Speaker 1: is perfect for poems or blonde posts or small articles,
Speaker 1: but not something the size of a novel. Why because
Speaker 1: a novel has arcs and plot twists and cleverly planted
Speaker 1: clues and cliffhangers, and all of these operate at a
Speaker 1: longer timescale. So a human author mentally zooms in and
Speaker 1: out such that their stories have this sweeping arc to them. So,
Speaker 1: for example, in a mystery novel, we get to the
Speaker 1: end and we realize that all the clues and the
Speaker 1: red herrings we saw or subservient to the solution to
Speaker 1: the mystery, which of course the author knew from the beginning,
Speaker 1: and the author was just spooling out clues to you
Speaker 1: one at a time. In writing, you often have to
Speaker 1: know the end to structure the beginning in the middle.
Speaker 1: And this is, by the way, why chat GPT can't
Speaker 1: make up a new joke, even though it can repeat
Speaker 1: jokes that are already made.
Speaker 2: But it's because to construct a joke, just like a
Speaker 2: mystery novel, you have to know the punchline first, and
Speaker 2: then you construct the joke backwards. But these large language
Speaker 2: models are simply constructing everything in the forward direction. It
Speaker 2: does statistical calculations on what the most probable word to
Speaker 2: come next is given all the words before it. So,
Speaker 2: coming back to the long arc, if you watched all
Speaker 2: eight seasons of Game of Thrones, for example, or you
Speaker 2: read those books, you come to care about these characters
Speaker 2: because you've been with them through so many trials and
Speaker 2: you feel like you know the and understand them, and
Speaker 2: you can predict things about their behavior, and you're invested
Speaker 2: in their long term trajectories. So all the children of
Speaker 2: the Stark family end up scattered in different directions in
Speaker 2: the world, and then in the final season, they end
Speaker 2: up reconvening. After what seems like a lifetime of adventure.
Speaker 2: They're all back together for the final big showdown with
Speaker 2: the Knight King. And when we watch the series and
Speaker 2: we get to season eight, we think, wow, I didn't
Speaker 2: see that coming, that they're all back together now, and
Speaker 2: now this story has a beautiful shape to it.
Speaker 1: I'm really in the hands of a professional here. At
Speaker 1: least with our current AI architectures today, it's impossible to
Speaker 1: achieve that, except possibly in a few thousand word version,
Speaker 1: because chat ept is playing its statistical game, and of
Speaker 1: course it's playing it extremely well and successfully.
Speaker 2: But the trick to recognize here is.
Speaker 1: That it is amazing at the level of paragraphs and
Speaker 1: possibly a few pages, but not at the level of
Speaker 1: thinking about the details of a five hundred page novel,
Speaker 1: or a two hour movie screenplay or an eight season epic.
Speaker 1: It's great at this small stuff because it can do
Speaker 1: that with statistics, but it's fundamentally limited for the longer
Speaker 1: stuff because it has no way to zoom out and
Speaker 1: think about the crops that it wants to plant for
Speaker 1: the long game. Okay, you might say, fine, maybe we'll
Speaker 1: get there at some point, but even for now, couldn't
Speaker 1: you build a big story out of smaller chunks. So
Speaker 1: one idea is to make this form of storytelling in
Speaker 1: which the world is infinitely big.
Speaker 2: Let's come back to this picture.
Speaker 1: I painted a moment ago of a choose your own
Speaker 1: adventure in which the AI generates plot points on the
Speaker 1: fly for you. So I say, okay, open that door
Speaker 1: to my left and the story continues as though it
Speaker 1: were all prescripted, as though I have an author, let's say,
Speaker 1: in the style of Henningway or Nibokov for Morrison, who
Speaker 1: has pre written every possibility. In certain ways, this would
Speaker 1: be amazingly cool, But I think the problem here is
Speaker 1: that a story like that would just equal randomness, and
Speaker 1: that's not actually what we want in a story. Instead,
Speaker 1: we want to feel like we're putting our trust into an.
Speaker 2: Author who sees the big picture.
Speaker 1: We want the Stark children to reconvene such as we
Speaker 1: feel the overarching pattern of the story and we have
Speaker 1: a sense of completeness. If you just wanted randomness, you'd
Speaker 1: go out into the world and find it there. You
Speaker 1: wouldn't sit on your couch and read about meaningless characters
Speaker 1: who are just in Brownian motion. And I think this
Speaker 1: is the same issue with AI music, at least as
Speaker 1: it stands now.
Speaker 2: Recent examples show.
Speaker 1: That it can compose incredible sounding music moment to moment.
Speaker 2: But the reason it doesn't beat out.
Speaker 1: A real human composer, at least today, is because it
Speaker 1: doesn't have any long term vision, and so the whole
Speaker 1: piece of music just hangs together. Statistically, moment to moment,
Speaker 1: and that's perfectly good for composing things like elevator music,
Speaker 1: which is for a short ride, or commercial music which
Speaker 1: only needs to be twenty seconds. But it won't for
Speaker 1: now replace a human composer who writes with the long
Speaker 1: arc in mind. For example, I was just talking with
Speaker 1: my friend Tony Brandt, who's a composer, and he was
Speaker 1: explaining to me that when Ludwig and vad Beethoven died,
Speaker 1: he left behind sketches for a tenth symphony. So a
Speaker 1: few years ago some computer scientists used AI to complete
Speaker 1: the symphony, to finish what was unfinished. Now did they
Speaker 1: do a good job. In one sense, it was an
Speaker 1: incredible feat. They extracted the statistics of Beethoven's choices and
Speaker 1: preferences from everything he'd written, and they used that to
Speaker 1: statistically guess what moves he would have made next had
Speaker 1: he lived, What notes, what chords, what instruments. But even
Speaker 1: with this feat, it was clear that the AI didn't
Speaker 1: know how to think long term. For example, Beethoven's Ninth
Speaker 1: Symphony ends with a chorus, which was such a surprise
Speaker 1: to end a symphony this way. It had not ever
Speaker 1: been done before, so the team training the AI decided
Speaker 1: Beethoven would have found a similar novelty to end his
Speaker 1: tenth Symphony, so they instructed the AI to include an organ,
Speaker 1: a church instrument that had also never been used in
Speaker 1: a symphony before. So at the start of the last movement,
Speaker 1: the AI generates an organ.
Speaker 2: But when we zoom in, we see the difference.
Speaker 1: The real Beethoven laid all sorts of clues in the
Speaker 1: Ninth Symphony to set the groundwork for the chorus. Like
Speaker 1: the orchestra plays a type of music called a recitative
Speaker 1: before the choir enters. Why because recitatives are found in opera,
Speaker 1: and opera has voices, So he was laying clues down.
Speaker 1: But in the AI tenth Symphony, there was no build
Speaker 1: up to the organ. There was no suspense, no hidden
Speaker 1: clues about.
Speaker 2: What was coming.
Speaker 1: The AI didn't know how to prepare the organ's arrival,
Speaker 1: how to give it the significance that's there for experts
Speaker 1: who listen for arcs that build through time. So, at
Speaker 1: least for now, AI is useful at writing brief articles
Speaker 1: and composing short ditties, but it doesn't have the architecture
Speaker 1: to write long pieces that humans love to create, and consume.
Speaker 2: So as I'm.
Speaker 1: Writing my next books, these large language models don't feel
Speaker 1: to me like a real threat, at least not yet.
Speaker 1: But let's imagine that we cut to ten years from
Speaker 1: now and some hardworking programmers have figured out how to
Speaker 1: build an AI with the right sort of architecture that
Speaker 1: zooms in and out on the scope of a story,
Speaker 1: and it can successfully generate a novel with cliffhangers and
Speaker 1: overarching themes and so on. It's certainly not impossible that
Speaker 1: we're going to get there, and it'll probably happen sooner
Speaker 1: than we expect. So let's imagine we get there in
Speaker 1: a year or five or ten. An AI can generate
Speaker 1: a million good novels in an hour. Then what Well,
Speaker 1: there are several directions in which things can go, And
Speaker 1: the possibility that I mentioned earlier is that novels might
Speaker 1: become bespoke, totally personalized to you. So you prompt your
Speaker 1: AI to make an adventure story of exactly the type
Speaker 1: that you might like. So you say, tell me a
Speaker 1: murder mystery about a basketball player who's killed by someone
Speaker 1: who appears to be his girlfriend. But then it turns
Speaker 1: out it's actually a CIA plot. That opens the door
Speaker 1: to a cover up involving a pharmaceutical company. Let's assume
Speaker 1: that the AI then spits out a book to your
Speaker 1: exact specification, and it does an amazing job, and it
Speaker 1: gives you a colorful story just how you wanted it,
Speaker 1: and you can enjoy that on the beach seconds later.
Speaker 1: Well that's cool, But I assert that this is never
Speaker 1: going to replace literature. And this is my second point
Speaker 1: why artists don't need to worry, because when you define
Speaker 1: your own plot, the surprise is diluted.
Speaker 2: The joy of literature is diluted.
Speaker 1: After all, even if you are a creative prompter, you
Speaker 1: are limited to versions of what you have experienced or
Speaker 1: read before. And much of what we love in literature
Speaker 1: is this surprise that comes from a particular point of
Speaker 1: view that you have never considered, like characters or plot
Speaker 1: points that would never be generated by your own limited
Speaker 1: point of view. In the end, I think we don't
Speaker 1: want to be limited by the parochial fence lines of
Speaker 1: our own imagination.
Speaker 2: I suspect that.
Speaker 1: No matter how far in the future we look, we
Speaker 1: are still going to want stories that surprise us, plot
Speaker 1: twists that we don't see coming. Okay, fine, you might say,
Speaker 1: so you agree that it's more exciting if we go
Speaker 1: on rides that we didn't predefine. But you might point
Speaker 1: out there's another thing that AI can do. So let's
Speaker 1: address the next issue, the idea that AI could someday
Speaker 1: generate millions of highly creative versions of a single story,
Speaker 1: so there'd be no need to stick with just one
Speaker 1: version of stories anymore. Instead of George R. R. Martin
Speaker 1: writing Game of Thrones over decades, future AI could generate
Speaker 1: thousands of fascinating versions in a second, and we wouldn't
Speaker 1: depend on him for the next slow novel. But I
Speaker 1: suggest that's not going to catch on either.
Speaker 2: Why.
Speaker 1: It's because we care about shared adventure. Would Game of
Speaker 1: Thrones have been so popular if we each saw our
Speaker 1: own version of it? In my version, John snow dies early,
Speaker 1: and in your version, danaris Mary's Tyrian lanister, and in
Speaker 1: your neighbor's version, Ariya marries into a royal family in
Speaker 1: some subplot island that never even appears in my version.
Speaker 1: If this sounds less appealing to you, to have mutually
Speaker 1: exclusive worlds, it illustrates the point that I want to make,
Speaker 1: which is a big part of story is this social aspect,
Speaker 1: the shared experience. We certainly could use AI to generate
Speaker 1: a million different versions of west Ros, and in the
Speaker 1: future we can generate instant video around these plots with
Speaker 1: terrific special effect. But as a society, I think we
Speaker 1: wouldn't want to each consume our own version. You want
Speaker 1: your John Snow to do the same thing as my
Speaker 1: John Snow. And this is because a huge part of
Speaker 1: story is this shared experience. We enjoy sharing fantasy worlds
Speaker 1: because we talk about them. This is why we do
Speaker 1: book clubs, so we can sit around and discuss something
Speaker 1: we all shared together. All the time, I hear people say, hey,
Speaker 1: did you see the latest episode of The Peripheral or
Speaker 1: Jack Ryan or Severance or Star Trek or whatever. And
Speaker 1: our love of communal stories stems partially from our need
Speaker 1: for shared references. For example, I'm always making reference and
Speaker 1: is to how Neo in the Matrix saw in slow motion,
Speaker 1: and that's decades after that movie came out, but it
Speaker 1: serves as a quick, culturally shared way that we can
Speaker 1: talk about concepts. We all have quick cultural references for
Speaker 1: time travel, where people say met me up Scotti when
Speaker 1: they're talking about teleportation, or we reference Obi wan Kenobi
Speaker 1: when we say may the force be with you, or
Speaker 1: we reference ex Machina or Westworld as a shorthand for
Speaker 1: AI going bad.
Speaker 2: And take this as an example.
Speaker 1: Imagine that you could generate a fantasy football game with
Speaker 1: your favorite players from any decade on one team versus
Speaker 1: players on another team, and you can now watch a
Speaker 1: full football game from stem to stern. But would you
Speaker 1: if no one else ever saw that game? In other words,
Speaker 1: would you follow teams all the way through the World
Speaker 1: Series if it was purely AI generated plays and games.
Speaker 1: I know that people might have different opinions on this,
Speaker 1: but to me, that sounds not the least bit appealing.
Speaker 1: Why it's because a giant part about sports is the
Speaker 1: culture of talking about the game. Hey did you see
Speaker 1: that play last night? Can you believe that shot he took?
Speaker 1: Can you believe the call that refmade? And stories are
Speaker 1: analogous to sports in this way. We come to our
Speaker 1: book clubs to take the world that we read in
Speaker 1: solitude and find a community with other people who were
Speaker 1: there with us from their own living rooms. So I
Speaker 1: suggest that as a culture, we are always going to
Speaker 1: desire and need a shared vocabulary, and the only way
Speaker 1: to grow that is to watch the same movies and
Speaker 1: read the same stories.
Speaker 2: And that's why I predict that.
Speaker 1: While individualized stories might find niche audiences, it won't replace
Speaker 1: our need for shared stories. This is an interesting dimension
Speaker 1: of literature that's not typically canered. Story gives us social glue. Okay, fine,
Speaker 1: so let's assume that at some point AI could write
Speaker 1: a story that's so evocative and beautiful that it becomes
Speaker 1: a shared story, an adventure which everyone taps into and enjoys.
Speaker 1: And now we arrive at my fourth point about why
Speaker 1: AI won't totally displace creatives, and that is the question
Speaker 1: of whether we get something more out of a piece
Speaker 1: of literature or art if we feel there's.
Speaker 2: A heartbeat behind it.
Speaker 1: I read a beautiful quotation in The Atlantic about a
Speaker 1: decade ago quote one of the only requirements for literature
Speaker 1: is that the reader can feel a heart pulsing back
Speaker 1: from them on the other side of the page. The
Speaker 1: heartbeat matters because when we read, we consider the intention
Speaker 1: of the author. We think, oh, this is Mary Shelley,
Speaker 1: whose mother died a couple of weeks after she was born,
Speaker 1: and she had a troubled childhood, and her father homeschooled her.
Speaker 1: And she married the romantic poet Percy bish Shelley, and
Speaker 1: he was already married and his wife committed suicide, and
Speaker 1: they moved to France, and she came back pregnant, and
Speaker 1: they were destitute, and their daughter died. And then they
Speaker 1: went to spend a summer in Geneva with friends, and
Speaker 1: they each set out to write a ghost story, and
Speaker 1: she ended up writing Frankenstein.
Speaker 2: So we read her.
Speaker 1: Novel and we think, this is her voice, and this
Speaker 1: is her viewpoint on the world, and these were the
Speaker 1: things that she knew and the things she didn't know,
Speaker 1: and the things she couldn't know.
Speaker 2: It isn't just the piece of art itself.
Speaker 1: It is the artist behind the art that colors our experience.
Speaker 1: So imagine we get Chad Gpt to adopt Mary Shelley's
Speaker 1: style and write a story involving cell phones and electric cars.
Speaker 1: It might be interesting and amazing, but I suggest we
Speaker 1: wouldn't enjoy it as much because we would recognize there's
Speaker 1: no unique human, no unique beating heart who had the
Speaker 1: experiences and slaved over the words. Now, you could argue
Speaker 1: that almost all of the authors we enjoy. We live
Speaker 1: apart from them in space or time, and we'll never
Speaker 1: meet them, and we just have the vaguest sense of
Speaker 1: their existence.
Speaker 2: And that might be true, but it's still worth.
Speaker 1: Noting that we know fundamentally that they are human and
Speaker 1: they are like us in some way. They may be
Speaker 1: more successful, or more impoverished, or maybe from a different country,
Speaker 1: but we know that fundamentally they are fellow travelers with
Speaker 1: us on the human journey. Now, obviously we love a
Speaker 1: lot of things that aren't real, like Spider Man or Batman,
Speaker 1: but we all I also love the actors behind them.
Speaker 1: If you had a chance to have dinner with or
Speaker 1: even to shake the hand of the actor behind some
Speaker 1: fantasy character that you love, you'd be thrilled about this.
Speaker 2: Now, I think that leads.
Speaker 1: To an interesting open question about some of these new
Speaker 1: avatars that are hitting the scene with hundreds of thousands
Speaker 1: of followers on Twitter. Even though they're fake. They're just avatars,
Speaker 1: they're not real people. The part that strikes me is
Speaker 1: really interesting is that the ones who get all the
Speaker 1: attention are the creators behind the avatar. In other words,
Speaker 1: if I told you there was an avatar on Twitter,
Speaker 1: with a one hundred thousand followers, and you could get
Speaker 1: the chance to meet the young woman behind all this,
Speaker 1: you'd be thrilled. What this tells me is that we
Speaker 1: are compelled by the heartbeat that is just behind the
Speaker 1: actor or the avatar. In many ways, that's more interesting
Speaker 1: to us than the actor or the avatar themselves. Now,
Speaker 1: I don't think this goes on in so let me
Speaker 1: just address the counterpoint. You might say, well, does that
Speaker 1: mean that if AI generated a thousand novels in a second,
Speaker 1: that I'd be really interested in meeting the team of
Speaker 1: young programmers behind that. I don't think so, because meeting
Speaker 1: the programmers doesn't expand your understanding of the story. But
Speaker 1: meeting an author who poured her heart into the story
Speaker 1: for years that does shape and color and expand your understanding.
Speaker 2: And by the way, beyond writing, I think.
Speaker 1: This applies to musical composers and visual artists in the
Speaker 1: same way, and in fact, to all human endeavors. I
Speaker 1: was just talking with a neighbor of mine. He and
Speaker 1: I spend a lot of time on airplanes flying to
Speaker 1: some city in the world to give a talk. He
Speaker 1: just got a three D scan and a high resolution
Speaker 1: avatar of himself made and he can combine that with
Speaker 1: Chad GPT to make his avatar give little speeches. And
Speaker 1: so he and I were really chewing on this because
Speaker 1: the question is, the next time he gets invited to
Speaker 1: speak on some stage and some random city around the world,
Speaker 1: can he just have the avatar give the speech online instead?
Speaker 1: Will conferences still want him to fly across.
Speaker 2: The globe to give a talk.
Speaker 1: Or will the avatar be good enough and save a
Speaker 1: lot of expense and plane fuel? Possibly, But the flip
Speaker 1: side is do people value going to the talk because
Speaker 1: of the beating heart.
Speaker 2: On the stage?
Speaker 1: And my long bet is that conferences will continue to
Speaker 1: invite flesh and blood humans because audiences are humans who
Speaker 1: care about other humans. So when it comes to legal documents,
Speaker 1: if AI can do it better, awesome, when it comes
Speaker 1: to medical diagnoses, if AI can do it better awesome,
Speaker 1: when it comes to hearing a speaker on the stage
Speaker 1: with his or her imperfections and limited knowledge and fundamentally
Speaker 1: human nature, I'm going to take the bet that that
Speaker 1: is going to last and beyond just appreciating the reality
Speaker 1: of another human. This maybe for another reason as well,
Speaker 1: an interesting psychological effect that I think is going to
Speaker 1: be at play here. This is what I'm going to
Speaker 1: call the effort phenomenon. I'll give you an example of this.
Speaker 1: A well known colleague of mine here in Silicon Valley
Speaker 1: recently announced that he had published a book half written
Speaker 1: by him and half written by AI. And when I
Speaker 1: first heard about this, I thought, I wish I wanted
Speaker 1: to read this, but I don't now. I did take
Speaker 1: a look at the book, and there are clever insights,
Speaker 1: and it's well written. But I'm simply not that inspired
Speaker 1: to read something that's even half written by AI, because
Speaker 1: it makes me feel, perhaps unfairly, that.
Speaker 2: He didn't put in the normal amount of effort.
Speaker 1: My analogy you would be if Picasso said, hey, will
Speaker 1: you buy this painting? My students painted most of it,
Speaker 1: but then I finished it off and put my signature
Speaker 1: on it. It feels like it would be slightly less valuable.
Speaker 1: So let's return to that scene in Westworld where William
Speaker 1: asks the host are you real? And she says if
Speaker 1: you can't tell, doesn't matter, Because this is the question
Speaker 1: that comes up.
Speaker 2: About a novel.
Speaker 1: If I spend seven years writing a novel, and if
Speaker 1: Chad Gpt or google bart spits out a novel that's
Speaker 1: word for word equivalent.
Speaker 2: Does it matter?
Speaker 1: And I think, perhaps surprisingly, the answer is yes, it matters.
Speaker 1: We care about the effort that went into it. If
Speaker 1: I were to show you two pieces of artwork that
Speaker 1: someone had done, and one of them just involves painting
Speaker 1: a single dot on the middle of a big white canvas,
Speaker 1: and the other one is the person carefully gluing marbles
Speaker 1: one on top of each other until they balance eight
Speaker 1: feet high. You may have a p for looking at
Speaker 1: one or the other, but just think about how much
Speaker 1: money you would, in theory, be willing to pay for
Speaker 1: each of these. If you're like most people, you think
Speaker 1: the thing that took a lot of effort is worth more.
Speaker 1: There have been psychology studies on this since the nineteen fifties.
Speaker 1: It's difficult for people to separate out the effort that
Speaker 1: went into something from its value. In other words, the
Speaker 1: effort is used as a shortcut for understanding quality. For example,
Speaker 1: in one paper done by Krueger at All, they had
Speaker 1: people rate a poem, or rate a painting, or rate
Speaker 1: a suit of armor, and the people generally thought it
Speaker 1: was better quality and worth more money, and they liked
Speaker 1: it better if they thought it took more time and
Speaker 1: effort to produce a friend of mine. Uses the example
Speaker 1: of diamonds. People will pay much more money for a
Speaker 1: real diamond with flaws than they will for a synthetically
Speaker 1: grown diamond from laboratory that has no flaws at all. Now,
Speaker 1: why would you pay extra money for flaws? Part of
Speaker 1: this has to do with the notion of effort. The
Speaker 1: real diamond was produced by mother nature over millions of
Speaker 1: years of compression, so it's a very special thing that
Speaker 1: took quote unquote effort on the part of mother nature.
Speaker 2: But the lab grown diamond that can be done in
Speaker 2: a day and a half.
Speaker 1: And so even though it's more perfect, it is less
Speaker 1: valuable because it just took less time to make it.
Speaker 2: We actually pay for flaws.
Speaker 1: Now, I'm not arguing that we can't be fooled at
Speaker 1: some point into loving AI generated literature. It seems quite
Speaker 1: possible to me that in the future there will be
Speaker 1: novels written by AI, and we might not always know it,
Speaker 1: because the AI will also generate a false story about
Speaker 1: the author, complete with a biography and a generated photograph.
Speaker 1: My assertion is simply that FA it is going to
Speaker 1: be an important part of what the AI will need
Speaker 1: to do, because it's more difficult to become invested in
Speaker 1: something that we think is simply doing massive statistical calculations
Speaker 1: rather than having a private, limited internal life. We care
Speaker 1: about other humans, So what's the big picture. My friend
Speaker 1: Kevin Kelly suggested to me the other day that generative
Speaker 1: AI may play a role that's analogous to the invention
Speaker 1: of the camera. What happened at that moment in history
Speaker 1: was that painters lamented that this was the end of
Speaker 1: painting because you could now capture anything instantly with the
Speaker 1: click of a button, and you could capture it with
Speaker 1: zero mistakes. So why would you sit there with a
Speaker 1: paint brush and painstakingly try to capture every detail by hand.
Speaker 1: At that moment in history, it seemed clear that painters
Speaker 1: were done for But as it turns out, photographs ended
Speaker 1: up filling a different niche.
Speaker 2: Absolute realism wasn't the only end goal of art.
Speaker 1: People didn't only want a maximumly realistic print of a scene.
Speaker 1: They also wanted swirls, an amazing color, and more importantly,
Speaker 1: things that didn't exist in the outside world. So canvas
Speaker 1: painting remained an active field, even while photography grew and
Speaker 1: ended up flowering on a neighboring field. So one possibility
Speaker 1: is that AI generated literature will not foment it takeover,
Speaker 1: but instead it's going to fill a new niche, one
Speaker 1: that we don't quite see yet, but it isn't the
Speaker 1: same plot of land. And I think there's one more
Speaker 1: possibility for where this could go for writers, not now,
Speaker 1: but in the coming years. And for that, I want
Speaker 1: to tell you what happened with the world champion Go
Speaker 1: player Could Jig. He was the world's number one player
Speaker 1: at Go, which is the game in which you use
Speaker 1: those small black or white rocks to define your territory
Speaker 1: and try to surround your opponent. So in May of
Speaker 1: twenty seventeen, he faced off against an AI program called
Speaker 1: Alpha Go, which was designed by Deep Mind, and Alpha
Speaker 1: Go had been trained on millions and millions of games
Speaker 1: of Go, so it had deeply absorbed the statistics of
Speaker 1: possible plays. So they played the first game and Jiu lost.
Speaker 1: Alpha Go had pulled moves that none of his human
Speaker 1: opponents had ever thought of, and then Jua lost the
Speaker 1: second game. The AI had won over a human in
Speaker 1: a game that's way more complex than chess, and subsequent
Speaker 1: versions of the AI are no doubt going to continue
Speaker 1: to win evermore. But that's not the interesting part of
Speaker 1: the story. The interesting part is what happened next. So
Speaker 1: Jig got over his embarrassment and he became mesmerized by
Speaker 1: what had just transpired, and he studied the games.
Speaker 2: That he lost.
Speaker 1: Before he played Alpha Go, Jia had won a majority
Speaker 1: of the games against his human opponents, but afterwards he
Speaker 1: found he was able to beat his human opponents even
Speaker 1: more easily. After his species shaming defeats in twenty seventeen,
Speaker 1: he went on to play twelve straight matches against humans and.
Speaker 2: He won them all in a row. So what had happened.
Speaker 3: He had been exposed to new kinds of moves and
Speaker 3: strategies that had been pulled by Alpha Go, and these
Speaker 3: all lay outside of traditional ways of doing it.
Speaker 2: All these moves that Alpha Go had done.
Speaker 1: Were legal and possible, but they were just different from
Speaker 1: what had been played over the last twenty five hundred years.
Speaker 2: If you're a Go officionado.
Speaker 1: This included things like playing a stone directly diagonal to
Speaker 1: your opponent's loan stone, or playing six space extensions, while
Speaker 1: humans tend to prefer.
Speaker 2: Five space anyway.
Speaker 1: Joe reported that playing against the AI was like opening.
Speaker 2: A door to another world.
Speaker 1: Once he was exposed to these alien game plays, he
Speaker 1: incorporated them, and this story I suspect typifies the future
Speaker 1: as humans and machines interface. Some people are worried that
Speaker 1: AI is going to take over, but we will continue
Speaker 1: to adapt as well. We will become better writers as
Speaker 1: we see examples that are allowed by the language but
Speaker 1: no one had ever tried it, or visual art techniques
Speaker 1: that involve moves that are allowable, but culturally we just
Speaker 1: never thought to do it, Or musical moves that are
Speaker 1: possible to.
Speaker 2: Do with notes, but no one does.
Speaker 1: Them because traditionally we just wouldn't think of going there.
Speaker 1: Because fundamentally, as a writer, I think I'm doing all
Speaker 1: kinds of original things, but there's a very real sense
Speaker 1: in which I'm simply remixing what I've absorbed before. I
Speaker 1: interpolate between examples that I've seen. So even if AI
Speaker 1: is just interpolating, it's read billions of times more texts
Speaker 1: than I have, and so it can do very clever interpolations,
Speaker 1: and I can learn from that a lot of people
Speaker 1: are worried that AI is going to leave humans far behind,
Speaker 1: and in many respects that's true. But as computers improve,
Speaker 1: so will we. In the battle of man and machine.
Speaker 1: Both are going to get better, and as we continue
Speaker 1: to adapt in parallel, the future definition of AI may
Speaker 1: well shift from our official intelligence to augmented intelligence. In
Speaker 1: the best case scenario, this isn't going to be a war,
Speaker 1: but a collaboration. It's going to be an ongoing, guided
Speaker 1: tour into areas that were previously just beyond our view.
Speaker 2: That's all for this week.
Speaker 1: To find out more and to share your thoughts, head
Speaker 1: over to eagleman dot com, Slash Podcasts, and you can
Speaker 1: also watch full episodes of Inner Cosmos on YouTube.
Speaker 2: Subscribe to my channel so you can.
Speaker 1: Follow along each week for new updates until next time.
Speaker 2: I'm David Eagleman, and this is Inner Cosmos.