Speaker 1: Will AI make humans better? And what does this have
Speaker 1: to do with linguistics or the movie Arrival or self
Speaker 1: driving cars or debate and video games and elections and
Speaker 1: chess and the ancient game of go. Welcome to Intercosmos
Speaker 1: with me David Eagleman. I'm a neuroscientist and an author
Speaker 1: at Stanford and in these episodes we seek to understand
Speaker 1: why and how our lives look the way they do.
Speaker 1: In today's episode is about whether AI will make us
Speaker 1: better humans. I often find myself totally flabbergasted by the
Speaker 1: change that I've seen just in my lifetime. When I
Speaker 1: was a really little kid, personal computers didn't exist, and
Speaker 1: then we passed through a door and suddenly they did.
Speaker 1: And I saved up my money and I got a
Speaker 1: common or VIC twenty computer, which was something my parents
Speaker 1: had never seen the likes of. And I felt like
Speaker 1: I was living the largest change in human history, because
Speaker 1: for the first time, everybody could have a machine that
Speaker 1: would do all kinds of things. But that turned out
Speaker 1: not to even be the biggest change, because the next
Speaker 1: stop was even bigger, and that was the idea that
Speaker 1: some people had to build a system where we could
Speaker 1: keep information on computers and make computers talk to each
Speaker 1: other such that if the Soviets bombed America, the important
Speaker 1: information wouldn't just be stored on one computer, and messages
Speaker 1: could follow different routes on the network, and that way
Speaker 1: you had a very robust system for keeping information. That
Speaker 1: was of course Arpanet, which became the Internet, and not
Speaker 1: long after, the idea was introduced of a way that
Speaker 1: everyone could use this giant network, not just with text,
Speaker 1: but with graphics, and.
Speaker 2: That was the birth of the Worldwide Web.
Speaker 1: And as soon as that technology existed, then people started
Speaker 1: figuring out what to do with it, and one young
Speaker 1: man started to sell books over the Internet.
Speaker 2: And that became Amazon.
Speaker 1: And two graduate students at Stanford asked the question of
Speaker 1: how the heck we were going to be able to
Speaker 1: find information on this sprawling network, and they created a
Speaker 1: way of measuring all the connections between web pages and
Speaker 1: that gave the ability to search for it, and.
Speaker 2: That garage project grew into Google.
Speaker 1: And around the same time, a Harvard kid was thinking
Speaker 1: about a better way to allow his classmates to get
Speaker 1: to know each other, which was traditionally done at the
Speaker 1: beginning of the year by printing a booklet with everybody's
Speaker 1: picture and name, and that little booklet was called called
Speaker 1: a Facebook, and he thought of digitizing that, and on
Speaker 1: and on, people increasingly figured out how to take this
Speaker 1: new technology and make things that would live on top
Speaker 1: of it. And I felt very lucky to have experienced
Speaker 1: two truly world changing inventions in my lifetime, and I
Speaker 1: knew that had launched us into a world that was
Speaker 1: so different from what my great grandparents could have possibly imagined.
Speaker 1: But now here we are in the middle of a
Speaker 1: third revolution. It's related to the first two computers and
Speaker 1: the Internet, but it makes them look like warm up acts.
Speaker 1: And that's the fact that we have created a new
Speaker 1: intelligent species that we're going to be sharing the planet
Speaker 1: with from now on. This is not to say that
Speaker 1: AI has exactly the same type of intelligence that human
Speaker 1: brains have, but obviously it has absorbed the higher knowledge
Speaker 1: sphere of humankind and it can spit that back to
Speaker 1: us with all sorts of remixes. Now, the question is,
Speaker 1: are we in trouble because of this new invention? Have
Speaker 1: we taken things a step too far? Well, let me
Speaker 1: give you an example that's on people's minds. A few
Speaker 1: months ago, a Swiss research team carried out a secret
Speaker 1: experiment in online persuasion. They went to a forum on
Speaker 1: the website Reddit, and in this forum, users post opinions
Speaker 1: and invite other people to challenge them. And so these
Speaker 1: researchers quietly unleashed a set of AI accounts to pretend
Speaker 1: that they were people and to try to change other
Speaker 1: people's minds. So their large language models LMS, they participated
Speaker 1: in the debating just like any other human. These bots
Speaker 1: wrote arguments, they engaged with users, They debated with the
Speaker 1: hope of changing minds. Now, the researchers measured success by
Speaker 1: tallying whenever an original poster publicly admitted that their mind
Speaker 1: had been changed. So how did the bots do well?
Speaker 1: They achieved up to an eighteen percent success rate in
Speaker 1: changing people's minds. Now, the critical piece you need to
Speaker 1: know is that the average human success rate is about
Speaker 1: three percent. So the bots had absolutely crushed their human
Speaker 1: competition in an environment teeming with intellectuals. The bots not
Speaker 1: only survived, but they thrived. In fact, one of the
Speaker 1: AI accounts climbed into the ninety ninth percentile of all
Speaker 1: users on this subreddit. It racked up ten thousand karma
Speaker 1: points along the way. Now, one of the most surprising
Speaker 1: aspects of the experiment was how effectively a small team
Speaker 1: of researchers, operating with modest academic resources, how they were
Speaker 1: able to outperform essentially every human debater on the platform.
Speaker 2: So let that sink in for a second.
Speaker 1: You have a handful of graduate students armed with an
Speaker 1: LM and a sneaky deployment strategy, and they quietly demonstrated
Speaker 1: what it might look like if influence operations were scaled
Speaker 1: by AI. Now, when this data was released, one of
Speaker 1: the scariest parts to people was that nobody noticed that
Speaker 1: these debaters were actually AI and not real humans. This
Speaker 1: reddit channel prides itself as one of the most critically
Speaker 1: minded communities on the platform. If any place could sniff
Speaker 1: out an imposter, it should have been here. But for
Speaker 1: the entire four months of the experiment, the bots played
Speaker 1: along undetected by the humans. So that's worrisome. And there's
Speaker 1: another issue too, which is the role of personal data.
Speaker 1: When the bots were given just a basic profile of
Speaker 1: the user, their aged, their location, and their political leaning,
Speaker 1: the success rate bumped up by one percentage point. Now,
Speaker 1: you might say wait a minute, who cares. One percentage
Speaker 1: point is very small, but in political terms, one percent
Speaker 1: could be enough to swing a lot of national elections.
Speaker 1: The difference between nudging public sentiment one way or another
Speaker 1: can come down to.
Speaker 2: Very tiny tweaks.
Speaker 1: So the lesson that surface here is that even minimal
Speaker 1: personalization can significantly sharpen the edge of an AI's persuasive power.
Speaker 1: So when this story surfaced recently about these debaters not
Speaker 1: being real human beings, the reactions were very grim because
Speaker 1: everyone realized that this small academic experiment illustrated what stealth
Speaker 1: influence operations could look like in the near future. If
Speaker 1: a handful of real searchers could do this undetected, what
Speaker 1: happens when you have state actors or corporations or political
Speaker 1: campaigns with real resources doing the same thing at a
Speaker 1: scale thousands of times larger. Also, what's worse is that
Speaker 1: the failure of everyone to detect that these were bots
Speaker 1: that raises serious questions about how we can protect public
Speaker 1: discourse as we enter this new future. If smart reditor
Speaker 1: debaters couldn't spot the difference between a human and a bot,
Speaker 1: what hope is there for broader audiences. So even though
Speaker 1: the major AI companies have all pledged to avoid building
Speaker 1: models with dangerous capabilities like manipulating public opinion on mass.
Speaker 1: This Reddit experiment suggests the thresholds may already be easier
Speaker 1: to cross than any of us had anticipated. What this
Speaker 1: all means is that with major elections in future years,
Speaker 1: were genuinely gonna have to worry about this. The halcyon
Speaker 1: days are gone when we could assume that the replies
Speaker 1: to our online messages came from a fellow human, and
Speaker 1: the risks are real and the potential for abuse is obvious.
Speaker 1: But for today's episode, we're gonna look at all this
Speaker 1: from a very different angle. I think it might be
Speaker 1: worth asking a different question, which is why did the
Speaker 1: bots succeed? After all, they didn't hack people's brains with
Speaker 1: neural interfaces. They didn't spread fear or disinformation. They didn't
Speaker 1: manipulate emotions or overwhelm users with noise. They simply made
Speaker 1: better arguments. They didn't insult people while arguing with them.
Speaker 1: They didn't do little jabs and digs. They just made
Speaker 1: good arguments empathetically. The bots present their points calmly and
Speaker 1: rationally and persuasively, and when users changed their minds.
Speaker 2: It wasn't because they had been tricked.
Speaker 1: It was because they recognized that another perspective was worth considering.
Speaker 1: Humans often change their minds when faced with sound reasoning
Speaker 1: that can be backed up, and mind changing is a
Speaker 1: great thing. It means you're willing to reconsider some closely
Speaker 1: held opinion when the facts or logic warranted. It's a
Speaker 1: mark of intellectual strength, not a sign that you've been tricked.
Speaker 1: In that light, the success of AI debaters isn't necessarily
Speaker 1: a story about manipulation. It could also be a story
Speaker 1: about raising the bar of debating. Now, as I followed
Speaker 1: the outcome of this AI debater study, it struck me
Speaker 1: that there may be a helpful precedent for thinking about
Speaker 1: this moment, for thinking about how AI could.
Speaker 2: Actually improve us.
Speaker 1: So think about the events that unfolded in the hyper
Speaker 1: competitive world of chess. If you can remember back to
Speaker 1: nineteen ninety seven, IBM had built an AI system called
Speaker 1: Deep Blue, and it defeated the world champion, Gary Kasprov.
Speaker 1: This was seen as a seismic moment. The game of
Speaker 1: chess had been quote unquote solved, and everyone worried that
Speaker 1: human mastery was obsolete and then about two decades later,
Speaker 1: Alpha Go beat the world's top Go player, and the
Speaker 1: choir of concerned voices grew louder. But then something unexpected happened.
Speaker 1: In May of twenty seventeen, the world's number one Go player,
Speaker 1: Could G, faced off against his toughest opponent. G was
Speaker 1: the reigning champion in Go, and you know this is
Speaker 1: the game where two players use smooth black rocks or
Speaker 1: white rocks to surround more territory than their opponent. In
Speaker 1: G's case, he was playing against AI. He was playing
Speaker 1: against Alpha Go, which had been trained on many millions
Speaker 1: of games, and it had deeply absorbed the statistics of
Speaker 1: possible plays.
Speaker 2: So G lost the first game.
Speaker 1: Alpha Go had pulled moves that none of G's human
Speaker 1: opponents had ever thought of, and then G lost the
Speaker 1: second game. The fact is he didn't stand a chance.
Speaker 1: The AI had won over a human in a game
Speaker 1: that was way more complex than chess, and subsequent versions
Speaker 1: of this AI will without doubt continue to win ever more.
Speaker 1: But that's not the interesting part of the story. The
Speaker 1: interesting part is what happened next. G got over his
Speaker 1: embarrassment and he became mesmerized by what the heck had
Speaker 1: just transpired. He studied the games that he lost. Now,
Speaker 1: before he had played Alpha Go, G had won most
Speaker 1: of the games against his human opponents, But after he
Speaker 1: played Alpha Go, he was able to beat his human
Speaker 1: opponents even more easily. In other words, after his species
Speaker 1: shaming defeat in twenty seventeen, G went on to play
Speaker 1: twelve straight matches against fellow humans, and he won.
Speaker 2: Them all in a row. Now, what had happened.
Speaker 1: G had been exposed to new kinds of moves and
Speaker 1: strategies that AlphaGo was pulling off that lay outside the
Speaker 1: traditional ideas. All these moves were legal and pop pole,
Speaker 1: but they were different from what had been played over
Speaker 1: the previous twenty five hundred years. For go eficionados, this
Speaker 1: included novelties like playing a stone directly diagonal to your
Speaker 1: opponent's loan stone, or commonly playing six space extensions while
Speaker 1: humans tend to prefer five space. So G reported that
Speaker 1: playing against the AI was like opening a door to
Speaker 1: another world. Some people worry that AI might make games
Speaker 1: of Chess and Go irrelevant, but amazingly, that is not
Speaker 1: what's happened. When AI Trump's Chess champions and Go champions
Speaker 1: It does so with moves that seem inhumanly creative, but
Speaker 1: all the moves are allowed by the rules. Humans simply
Speaker 1: never thought to go there before. And the key is
Speaker 1: that once the moves are seen by humans, then they're
Speaker 1: easily incorporated into our models. GE's experience with Alpha Go
Speaker 1: illuminated new nooks and crannies in his landscape. It exposed
Speaker 1: pathways that have never been lit up before. So AI
Speaker 1: immediately became a tool for steep improvement. And nowadays all
Speaker 1: chests and Go players above a certain level they all
Speaker 1: train with AI. They study the surprising and sometimes counterintuitive
Speaker 1: and alien strategies of the artificial mind, and just like Koje,
Speaker 1: today's grand masters play a deeper and more creative game
Speaker 1: than ever before. In other words, many commentators are worried
Speaker 1: that AI is going to leave humans far behind, and
Speaker 1: in some respects that's true.
Speaker 2: But as computation improves, so will we.
Speaker 1: AI will illuminate dark parts of our maps, allowing us
Speaker 1: to see new roads we didn't even suspect. The key
Speaker 1: point I want to make here is that instead of
Speaker 1: dampening human excellence, AI sparked a renaissance. In these games,
Speaker 1: human minds are elevated by learning from our artificial cousins.
Speaker 1: And if it were just chests and go, that's one thing.
Speaker 1: But I think we can detect this pattern happening all
Speaker 1: over the place. For example, the same thing has happened
Speaker 1: in poker. Professional poker players master the art of bluffing.
Speaker 1: They project strength when they're weak or weakness when they're strong.
Speaker 1: This has always been seen like a deep test of
Speaker 1: human psychology. The players read faces, they watch for micro expressions,
Speaker 1: they guess intentions, So in this way, poker is a
Speaker 1: really human game. But then Carnegie Mellon cooked up an
Speaker 1: AI called Librotus. Obviously, it doesn't have a face, it
Speaker 1: doesn't sweat, it doesn't blink, so it wasn't really like
Speaker 1: playing another human. So Lebronis started playing poker, and it
Speaker 1: did things that baffled the human players. The AI began
Speaker 1: making betting choices that looked bizarre. Sometimes it over bet
Speaker 1: the pot by huge margins, a move that the human
Speaker 1: players considered reckless. Other times it made really tiny bets
Speaker 1: in situations where no human would bother and the human
Speaker 1: players dismissed this all as network nonsense. But as the
Speaker 1: games went on, they realized these inhuman strategies were working.
Speaker 1: The AI was winning, and it was doing so by
Speaker 1: reinventing the language of poker. And now, just like with
Speaker 1: chess and go, professional poker players study these strategies. You
Speaker 1: have human players adopting patterns of play that just didn't
Speaker 1: exist before the machines taught them. AI made humans better
Speaker 1: poker players. And let me give you another example. There's
Speaker 1: a strategy video game called StarCraft two where players build
Speaker 1: armies and manage resources and try to outwit their opponent.
Speaker 1: So the company DeepMind set some AI agents on it,
Speaker 1: and those agents showed humans an entirely different way of
Speaker 1: going about running the strategy. At first, people thought the
Speaker 1: AI play seemed unfair and robotic, but then human players
Speaker 1: began to adapt. They started rethinking their own strategies. They
Speaker 1: started redesigning their build orders. They discovered things like sometimes
Speaker 1: sacrificing entire groups of units early in the game could
Speaker 1: produce long term advantages. These were not moves that humans
Speaker 1: had come up with, or possibly ever would have come
Speaker 1: up with, but once they were revealed, they became part
Speaker 1: of the human playbook. Or take a different video game
Speaker 1: called Dota two. You've got professional players. But then open
Speaker 1: AI built a system that used strategies that looked to
Speaker 1: human professionals like they were clumsy. The AI would push
Speaker 1: aggressively when humans would retreat or take risks that seemed absurd,
Speaker 1: but more often than not, the machines won, and just
Speaker 1: like with Chests and Go and StarCraft, the human professionals
Speaker 1: were forced to ask themselves had they been playing with
Speaker 1: blinders on all along? After all, the machines were uncovering
Speaker 1: landscapes that we just never knew were there. In other words,
Speaker 1: whenever AI discovers new pathways inside the universe of a game,
Speaker 1: it illuminates something for us about the fence lines of
Speaker 1: our own imagination. Humans had decades to explore video games,
Speaker 1: and centuries to explore poker, and millennia to explore the
Speaker 1: games of Chess and Go. But within weeks AI uncovered
Speaker 1: strategies that had never even struck us. And this is
Speaker 1: the point of today's episode. AI can expand the possibility
Speaker 1: space for us. What we've seen in the past few
Speaker 1: years is the limits of our imagination. Even in domains
Speaker 1: we thought we had mastered, our internal models might be
Speaker 1: a lot more narrow than we had ever realized. But
Speaker 1: by playing with machines, we're learning how they think, and
Speaker 1: more importantly, how we might think differently. So beyond chests
Speaker 1: or go or video games, the bigger game is how
Speaker 1: we can expand our own internal models. A lot of
Speaker 1: people cast this as man versus machine, but I think
Speaker 1: a more productive lens is seeing it as man learning
Speaker 1: from machine. The prize is a new way of seeing
Speaker 1: the game, and maybe, by extension, a new way of
Speaker 1: seeing the world.
Speaker 2: So let's come back to that.
Speaker 1: Amazing Swiss experiment where they made debate bots on Reddit
Speaker 1: that performed way better than humans. I suggest it's possible
Speaker 1: and maybe even likely, that a similar dynamic is going
Speaker 1: to unfold in the world of persuasive argumentation that happened
Speaker 1: in chess and go in video games. If AI agents
Speaker 1: can model the best forms of debate, clear and structured
Speaker 1: and empathetic and rational, then we humans can learn something
Speaker 1: from our artificial cousins. We can try out new moves,
Speaker 1: We can sharpen our skills on digital grinding stones. Imagine
Speaker 1: a future where students practice crafting arguments by debating highly
Speaker 1: skilled AI tutors. Imagine online discussions becoming more useful because
Speaker 1: users have gotten used to high quality exchanges. Imagine politicians
Speaker 1: and journalists and everyday citizens pushed to improve their things
Speaker 1: and better articulate their positions. So, rather than dumbing down conversation,
Speaker 1: the rise of high performing debate bots could nudge public
Speaker 1: discourse toward a new level of reasoned discussion. If that
Speaker 1: turns out to be the case, then we may come
Speaker 1: to see AI not as an enemy but as a
Speaker 1: sparring partner, just like in Chest and Go, and that
Speaker 1: has very different implications. Now, some people will take just
Speaker 1: the opposite position. If AI is so much better at
Speaker 1: debating than we are, won't that cause us to lose
Speaker 1: the skill entirely because there doesn't seem to be a
Speaker 1: point in being a good debater if the computer can
Speaker 1: do it better. But I think this is not an
Speaker 1: issue because even when we extrapolate this era of AI,
Speaker 1: people will still be talking with each other most of
Speaker 1: the time. You'll still be with your family over dinner,
Speaker 1: or with your friends over a coffee, or arguing with
Speaker 1: your neighbor about where the fence goes, or debating with
Speaker 1: a stranger at a town hall or whatever. It's not
Speaker 1: like we are plugging into the matrix through a port
Speaker 1: in the back of our neck, and we're only going
Speaker 1: to be communicating with machines. We are intensely social creatures,
Speaker 1: and the success of our species has been in part
Speaker 1: because of our massive sociability. So I think we will
Speaker 1: debate other humans all the time, and AI is just
Speaker 1: going to train us to be a little bit better
Speaker 1: at it. Now, I don't want to minimize the risks
Speaker 1: we're facing. We need audit tools and authentication systems that
Speaker 1: can verify whether content was written by humans or AIA.
Speaker 1: We need technical solutions like water marking or cryptographic content authentication,
Speaker 1: and providence tracking. This is all essential, but beyond these
Speaker 1: defensive measures, we should also recognize the opportunity because like
Speaker 1: the chests and go engines that reshaped how champion players think,
Speaker 1: debate bots will reshape how we reason and argue and
Speaker 1: understand one another. If we take this on correctly, AI
Speaker 1: might just up our game. It's still early days, but
Speaker 1: my impression so far is that AI is already playing
Speaker 1: this role in many areas, including for example, the arts.
Speaker 1: At least in some ways, it's amplifying human creativity. It's
Speaker 1: like a jazz partner who plays a riff you weren't expecting,
Speaker 1: or a painting mentor who introduces a color that you
Speaker 1: never thought to use. AI forces us out of our
Speaker 1: group in the arts. It shows us that the boundaries
Speaker 1: of our imagination can be stretched by encountering minds, even
Speaker 1: synthetic minds that think differently. These AI systems presumably don't
Speaker 1: have esthetic tastes or emotional longing in the way that
Speaker 1: we do, but they're awesome at doing remixes and trying
Speaker 1: strange new things out, and in this way they teach
Speaker 1: us just how much more flexible and expansive our own
Speaker 1: creativity can be. The takeaway is that AI shakes us
Speaker 1: loose from esthetic grooves that we might never leave on
Speaker 1: our own, and AI is doing exactly that in science
Speaker 1: as well. Just as one example, in material science and
Speaker 1: drug design, AI is proposing molecular structures that humans just
Speaker 1: wouldn't think to try already. It's nudging us to rethink
Speaker 1: what counts as a reasonable chemical design, and we're seeing
Speaker 1: the same thing in AI assisted math proofs. There are
Speaker 1: systems like lean and GPT fueled theorem provers. There are
Speaker 1: these systems that are suggesting lemmas or strategies that mathematicians
Speaker 1: just hadn't thought of. They could have thought of it,
Speaker 1: they just never did. These AI math proofs sometimes come
Speaker 1: out strange or elegant or messy, but in all cases
Speaker 1: they force mathematicians to think differently about structure and possibility.
Speaker 1: So AI can serve as a creativity engine in arts
Speaker 1: and in science, pushing us outside of our intuition driven
Speaker 1: blind spots. And there's something else that AI might be
Speaker 1: able to help us with, which is our personal lives
Speaker 1: and how AI can uncover blind spots there as well.
Speaker 1: If you're a regular listener, you know I've talked on
Speaker 1: many previous episodes about the ways in which we fool
Speaker 1: ourselves because you're.
Speaker 2: Not one thing.
Speaker 1: Instead, you're built of many different drives, or, as I
Speaker 1: wrote my book Incognito, you can think about the brain
Speaker 1: as a team of rivals. So think about the way
Speaker 1: that many people approach fitness. Someone might sign up for
Speaker 1: an expensive year long gym membership because they're determined to
Speaker 1: get in shape, and on paper, that looks like a
Speaker 1: great decision. It's an investment in their health. But at
Speaker 1: the same time, that person keeps telling themselves that they
Speaker 1: just don't have the time to exercise, so months pass,
Speaker 1: the membership goes unused, the rationalization continues. We've all seen
Speaker 1: this sort of thing. An AI personal assistant reviewing their
Speaker 1: spending and scheduling could point out the contradiction. It could say, Hey,
Speaker 1: you know what, You've paid twelve hundred bucks for a
Speaker 1: gym that you rarely visit, but you also spend seven
Speaker 1: hours a week watching streaming shows and an hour every
Speaker 1: day doom scrolling on social media. You say you don't
Speaker 1: have time, but your calendar suggests otherwise. We humans are
Speaker 1: so good at fooling ourselves with our little stories. We
Speaker 1: smooth over inconsistencies without even realizing it. But a good
Speaker 1: AI isn't going to buy the story. It's going to
Speaker 1: see the data and it's going to highlight the bias
Speaker 1: for us. And when it does, it forces us to
Speaker 1: confront something we might have preferred to ignore.
Speaker 2: But in this way it can make us better.
Speaker 1: Finally, I'll just mention something in my life where I'm
Speaker 1: noticing that AI is improving me. I have been driving
Speaker 1: for decades, and knock on wood, I've never had an accident,
Speaker 1: presumably because I'm a perfectly good driver. But for the
Speaker 1: past half year, I haven't driven myself around too much
Speaker 1: because I have a Tesla with full self driving mode
Speaker 1: and I let it drive me everywhere. So you just
Speaker 1: tell the Tesla where you want to go, and it
Speaker 1: does all the every bit of it.
Speaker 2: And here's the important part.
Speaker 1: I've had to admit that it's a better driver than
Speaker 1: I am. There's the obvious stuff, like the fact that
Speaker 1: it never blinks or sneezes or gets distracted by something,
Speaker 1: but instead it has cameras that take thirty six frames
Speaker 1: per second and never ever rest, even for the length
Speaker 1: of an eyeblink. But more than that is a deeper,
Speaker 1: more subtle issue. It's taught me that there are certain
Speaker 1: reactions I have that aren't optimized. For example, when some
Speaker 1: car pulls down traffic in front of me, I tend
Speaker 1: to slow down, but on full self driving mode, the
Speaker 1: Tesla just keeps going about the same speed that it
Speaker 1: was going. And while I would have thought that that
Speaker 1: seems a little aggressive, it turns out to be just
Speaker 1: fine because the other car gets up to speed, so
Speaker 1: there was no real need to slow down. It turns
Speaker 1: out it's not aggressive, it's just optimized. And I see
Speaker 1: lots of examples of this subtle differences in the way
Speaker 1: that it drives versus me, and I am learning from it.
Speaker 1: And there's also a relationship point to be made here,
Speaker 1: because my wife generally thinks that I am a backseat driver,
Speaker 1: because I'll often react with my body when she's driving,
Speaker 1: and she's a perfectly great driver, but I can't help
Speaker 1: myself because I would slow down when someone pulls out
Speaker 1: in front of me and she doesn't. But ever since
Speaker 1: I've seen how AI drives, I'm no longer an insufferable passenger.
Speaker 1: Now I know what optimized driving is, and I admit
Speaker 1: that she was closer to it than I was. So
Speaker 1: I don't know if I'm going to argue that AI
Speaker 1: is going to help marriages, but maybe Okay, so let
Speaker 1: me zoom out to the big picture. We have very
Speaker 1: limited internal models, and the main thing we're going to
Speaker 1: get from AI is an illumination of ideas outside the
Speaker 1: borders of our models. And to this end, I was
Speaker 1: thinking the other day about the twenty sixteen movie Rival.
Speaker 1: If you haven't seen it, this is a wonderful science
Speaker 1: fiction drama where a linguist is recruited by the US
Speaker 1: military after mysterious alien spacecraft appear around the world, So
Speaker 1: rather than focusing on flashy battles, the film centers on communication,
Speaker 1: decoding the alien strange language to understand why they have come. Now,
Speaker 1: there's good suspense, but the movie is actually quietly building
Speaker 1: towards its philosophical core. It's a concept from linguistics known
Speaker 1: as the Sapier Wharf hypothesis, which I've talked about on
Speaker 1: a couple of previous episodes. This hypothesis suggests that the
Speaker 1: language you speak doesn't only allow you to express your thoughts,
Speaker 1: but more than that, it shapes the way you think
Speaker 1: and even possibly how you perceive reality itself. So in
Speaker 1: the movie Arrival, this hypothesis becomes the lens through which
Speaker 1: the entire story unfolds. So I won't give away the
Speaker 1: spoiler of the movie, but it pivots on this point.
Speaker 1: Once the linguist learns the alien's language, she's able to
Speaker 1: perceive and experience the world differently. Upon learning their language,
Speaker 1: she now has powers that humans don't normally have. So
Speaker 1: I think that's a good metaphor for thinking about our
Speaker 1: moment with AI landing here like an alien species. Are
Speaker 1: we going to be exposed to ideas and concepts that
Speaker 1: expand our thinking. When we think about the arrival of AI,
Speaker 1: it's tempting to frame it as a contest will the
Speaker 1: machine replace the worker and the scientist, and the gamer
Speaker 1: and the composer.
Speaker 2: But the more interesting story is not about competition.
Speaker 1: It's about collaboration and how AI is going to stretch
Speaker 1: the boundaries of human imagination. Go to eagleman dot com
Speaker 1: slash podcast for more information and to find further reading.
Speaker 1: Check out my newsletter on substack and be a part
Speaker 1: of the online chats there. And you can watch the
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Speaker 1: Until next time, I'm David Eagleman, and this is Inner Cosmos.