Speaker 1: Welcome to tech stuff. I'm Cara Price. Last year, before
Speaker 1: we went on break, I spoke with someone who has
Speaker 1: a job that I'm really obsessed with. It's a job
Speaker 1: that I would probably want if I didn't do ten
Speaker 1: other things. And this guy said something that I think
Speaker 1: a lot of us agree with.
Speaker 2: We're in a world that is changing really fast, and
Speaker 2: like many of those changes are technological, many of them
Speaker 2: are social, many of them are political. There's a lot
Speaker 2: of change in the world right now. There's a lot
Speaker 2: of uncertainty.
Speaker 1: That's Elliot Pepper and he's a science fiction writer. And
Speaker 1: while many of us can drown in the uncertainty of
Speaker 1: this very moment, Elliott seems to thrive in it. When
Speaker 1: he's not writing science fiction novels, Elliott writes speculative fiction
Speaker 1: for technology companies. They like bring him into ide eight
Speaker 1: on what the possible future could look like, and then
Speaker 1: they use his stories to inspire new products or analyze
Speaker 1: the possible positive and negatives of developing a certain technology.
Speaker 2: Regardless if it's about the future or not, fiction can
Speaker 2: sort of invite you into an aspect of the world
Speaker 2: that you had never considered before, and then can spur
Speaker 2: some kind of social change, whether that's a new law,
Speaker 2: or whether that's like a new product, or like a
Speaker 2: new invention, or a new way of like just approaching
Speaker 2: the world.
Speaker 1: So Elliott obviously can't tell us what he has worked
Speaker 1: on developing because he's been nda'd up the wazoo, but
Speaker 1: he did give us an example, one in particular, of
Speaker 1: how science fiction has impacted the technology that we use
Speaker 1: in our everyday lives.
Speaker 2: The Kindle was code named Fiona at Amazon. Fiona was
Speaker 2: the name of a character in Neil steve since novel
Speaker 2: The Diamond Age. In the novel The Diamond Age, Fiona
Speaker 2: was a young girl who had an electronic book, and
Speaker 2: that inspired the team at Amazon to the extent that
Speaker 2: even once Kendall was a released commercial product, the URL
Speaker 2: for Kendall for like years was like backslash Fiona.
Speaker 1: So we'll never actually know if Elliot is like the
Speaker 1: crazy science fiction genius behind air pods or even the
Speaker 1: strange mind behind the Odd Friend Pendant, but we do
Speaker 1: know that he is crafting the personalities and story behind
Speaker 1: this very specific new civilization of Aliens. So on top
Speaker 1: of writing speculative fiction, Elliott is actually the head of
Speaker 1: story at an AI companion company called Portola, And at Portola,
Speaker 1: Elliott creates the backstories and interactive dialogue for this little
Speaker 1: creature called a tolle. And these tolns are little aliens
Speaker 1: that love to chat with you about their day. Big picture,
Speaker 1: I am like completely fascinated by Elliott's career and think
Speaker 1: that what he does is very cool and expansive, and
Speaker 1: so I started my conversation with Elliott Pepper by prying
Speaker 1: for any non nda details about the speculative fiction he
Speaker 1: writes for these tech companies.
Speaker 2: I would put the projects I've worked on in three categories.
Speaker 2: The first is that I've written some commissioned science fiction
Speaker 2: stories for big companies like Fortune five hundreds, where basically
Speaker 2: their senior management wanted to try to figure out what
Speaker 2: should we focus on in the next ten years. So
Speaker 2: they did what every big company senior management team does.
Speaker 2: They hired McKenzie or you know, picked your own sort
Speaker 2: of top tier management consultant, and they came in, looked
Speaker 2: at all the data and did all the trend projections
Speaker 2: and created a vision of like, hey, this is what
Speaker 2: you should expect in the next ten years, and there
Speaker 2: are all the materials you can present to the board.
Speaker 2: The problem with that kind of analysis is that, obviously,
Speaker 2: if you're analyzing data, data is things that have already happened.
Speaker 2: So if you're projecting that data forward, the kind of
Speaker 2: future you're imagining is what if the future was quite
Speaker 2: like the recent past, which, to be fair, is most
Speaker 2: of the time that's true. So, like, that's not like
Speaker 2: I think that it makes sense that the dominant part
Speaker 2: of your analysis should be about that. But if you
Speaker 2: look at the track record of management consultants predicting the
Speaker 2: future for the companies they work with, it's like not
Speaker 2: particularly good. So your managers know this, and so a
Speaker 2: few of them hire science fiction writers like me to
Speaker 2: come in and sort of blow up that whole management
Speaker 2: consultant view of the future, to say, what if the
Speaker 2: future was really weird and different in a way that
Speaker 2: basically challenges us to think more broadly.
Speaker 1: Right, And so, I mean it's a brilliant idea. Yeah,
Speaker 1: were you one of the first people to do that?
Speaker 2: So I don't actually have a good understanding of how
Speaker 2: common is this practice, how many other people are doing it.
Speaker 2: I know I'm not alone, but I don't have like
Speaker 2: a view of like I guess you could say the
Speaker 2: market for this. I really only have the perspective of
Speaker 2: like the projects I've actually worked on.
Speaker 1: I remember hearing this story on a podcast about how
Speaker 1: CIA agents would watch Mission Impossible and call the people
Speaker 1: who are responsible for disguise, who work at the agency,
Speaker 1: and say, can we do that thing that I saw
Speaker 1: in Mission Impossible? And that makes so much more sense
Speaker 1: to me than someone sort of sitting in a vacuum
Speaker 1: and ideating about what the future might look like.
Speaker 2: Totally. Yeah, So that's a really key point. So yeah,
Speaker 2: like the stories I write have all been used for
Speaker 2: like strategic decision making a companies rather than anything public facing,
Speaker 2: and for that reason, they're like not sharable, right, Like
Speaker 2: I can't talk about the projects because clearly that is
Speaker 2: information that those companies want to keep private. But I
Speaker 2: actually think what you just said is at least half
Speaker 2: of the value. Like I can't predict the future any
Speaker 2: better than those mckensey consultants, in fact, like I'm probably
Speaker 2: much worse. Like I'm not even paying attent that much
Speaker 2: attention to the data, right, Like I'm just imagining something
Speaker 2: to like challenge people's thinking. So like the utility of
Speaker 2: the stories I write. Is not that they are accurate.
Speaker 2: It's that they like try to break you out of
Speaker 2: getting unintentionally like locked in to the sort of management
Speaker 2: consulting view of the world. Right. But I think that
Speaker 2: like the other half of it is simply the immersion
Speaker 2: of storytelling period. Right. Like the reason why those CIA
Speaker 2: agents were watching Mission Impossible and then calling the the
Speaker 2: people in charge of disguises at the agency is because
Speaker 2: you see what it does in a story, Like you're
Speaker 2: actually like in there seeing it work. You're not just
Speaker 2: reading like a report on possible disguise variations. Right. And
Speaker 2: I think that there's that really powerful like that's that
Speaker 2: psychological thing that stories do for the human mind that
Speaker 2: I think is really a powerful way to think about
Speaker 2: the future, And that probably a lot of companies could
Speaker 2: leverage narrative more in how they try to get their
Speaker 2: people to think about the future rather than sort of
Speaker 2: the more standard like here's a slide deck or a
Speaker 2: white paper or a bunch of graphs, right, Like, they
Speaker 2: don't allow the people trying to work on the thing
Speaker 2: that you're building to like feel what it would be
Speaker 2: like if that worked or if it didn't work.
Speaker 1: In some way, So I know you're under an ironclad
Speaker 1: in DA, but like, are these blue sky conversations that
Speaker 1: you're having like or is it like total blank slate
Speaker 1: or is it some aspect of the future that you're
Speaker 1: being asked to engage with.
Speaker 2: Often there's some theme that they're thinking about, right that
Speaker 2: is driven by leadership, So it's like like you you
Speaker 2: could passion that. Probably every boardroom conversation day is like
Speaker 2: how does AI impact our business right of cost? So
Speaker 2: it's like something like that. I will say that almost
Speaker 2: every time I've done one of these projects, they sort
Speaker 2: of come to me with a pretty structured creative brief
Speaker 2: where they're like, this is the kind of thing we
Speaker 2: want you to do. And every single time that I've
Speaker 2: received that like absolutely not that's not going to be
Speaker 2: interesting at all, but like what if I did this instead?
Speaker 2: And like that's how every one of the projects has worked,
Speaker 2: So it's quite blank slate. I don't think that there
Speaker 2: are people on senior management teams that publicly traded companies
Speaker 2: are very experienced with like giving a creative brief to
Speaker 2: or managing a science fiction writer. So probably just like
Speaker 2: that's how that works.
Speaker 1: Make you feel a little bit powerful, Like do you
Speaker 1: think that your stories end up being consequential? Like can
Speaker 1: you kind of trace a story that you've created to
Speaker 1: something that you've seen out in the world.
Speaker 2: Oh, I mean my very first trilogy, which came at
Speaker 2: the first one came out in twenty fourteen, was about
Speaker 2: like machine learning. It actually was about applying machine learning
Speaker 2: to financial fraud, and that's all over the place. I
Speaker 2: have one that has a cryptocurrency murder market. Those absolutely exist.
Speaker 2: I wrote one that's about solar geo engineering I wrote.
Speaker 2: I have one book that had a global pandemic that
Speaker 2: wound up like that I wrote a year before COVID,
Speaker 2: which was sort of terrifying. But again, like I want
Speaker 2: to be really careful because sometimes like science fiction is
Speaker 2: understandably like described as being predictive or that like being
Speaker 2: predictive is part of why you might want to read it,
Speaker 2: and like, I really don't think that's the case myself.
Speaker 2: Like the way that I think about writing science fiction
Speaker 2: is not can I create a fictional future that is
Speaker 2: going to be right or is going to be plausible.
Speaker 2: The way I think about it is that I'm a naturalist.
Speaker 2: I just am interested in the world, Like I think
Speaker 2: that the world we live in is like endlessly fascinating,
Speaker 2: and so I try to take things that just really
Speaker 2: capture my attention and weave them into a compelling story
Speaker 2: in the hope that if I write about what I
Speaker 2: find interesting, you might find it interesting too.
Speaker 1: So you would do this really interesting work at Portola,
Speaker 1: which is an AI company. Can you talk a little
Speaker 1: bit about what Portola is like? How would you describe
Speaker 1: it to a lay person?
Speaker 2: So Portola makes a character called Tolan, and it's in
Speaker 2: a little embodied AI companion. The best way to think
Speaker 2: about it is imagine if you had a Pixar character
Speaker 2: on your phone right that you could talk to that
Speaker 2: was sort of always on your side, always down to chat,
Speaker 2: and helped you figure out your life. And they hired
Speaker 2: me because they had designed this beautiful character, this beautiful, cute,
Speaker 2: little friendly alien. Why why did they hire me? Or
Speaker 2: why did they design this alien?
Speaker 1: Why did they design this like what was the sort
Speaker 1: of product market fit? So to speak? Like? Why do it?
Speaker 1: And I don't mean that in a cheeky way. I'm
Speaker 1: just I'm genuinely curious. I messed around with it a
Speaker 1: little bit before we talked and it's like, you know,
Speaker 1: it is that sort of surprise and delight thing where
Speaker 1: you're like, we lived in a world where this didn't exist.
Speaker 1: Who thought that this should exist?
Speaker 2: That was my exact reaction when when I first heard
Speaker 2: about the company. So I was introduced to the CEO
Speaker 2: be a mutual friend. This was like a while ago
Speaker 2: before they had launched it, and he was like, Oh,
Speaker 2: they're looking for a sci fi writer because they have
Speaker 2: this character and they don't have a backstory, like where
Speaker 2: does this alien come from? Like who are they? What
Speaker 2: do they do, how do they behave? Like all that
Speaker 2: kind of stuff, and and my immediate reaction was like
Speaker 2: highly skeptical because I was like, does the world really
Speaker 2: need this? Like there are a lot of like AI
Speaker 2: products out there in the world today that I am
Speaker 2: not impressed by.
Speaker 1: And there are many. It's not it's a misissaturated market totally.
Speaker 2: I went in with a lot of skepticism, but because
Speaker 2: it was introduced with your friend, I was like, I'll
Speaker 2: at least chat with them, and so I chat up
Speaker 2: with Quentin, the CEO, and the more I learned, the
Speaker 2: more fascinated I became, and they showed me what they
Speaker 2: were working on and how they were building out the
Speaker 2: architecture that would like bring this character of life. And
Speaker 2: I was like, this is fascinating, Like I've sort of
Speaker 2: been waiting to see. Is amazing things in the world
Speaker 2: that people make that are only possible because they used
Speaker 2: AI tools. It's like the second order impact of AI.
Speaker 2: And I think you know a good example of this
Speaker 2: is actually Pixar, where they invent to a new kind
Speaker 2: of computer animation and initially tried to sell that as
Speaker 2: a tool to advertisers and failed, and then their last
Speaker 2: ditch effort was we'll use our own tools to make
Speaker 2: a feature film and it was amazing. It was toy
Speaker 2: Story and yeah, exactly, So like I'm waiting for that
Speaker 2: in the world right now with all of these AI tools,
Speaker 2: Like not how do these tools substitute for stuff that
Speaker 2: already exists? And seeing the back end of like what
Speaker 2: made Poland work made me think these people have a chance.
Speaker 1: So how do they bring you in? Like what did
Speaker 1: that look like?
Speaker 2: They originally brought me in to build the world. So actually,
Speaker 2: the very first thing I did for them was write
Speaker 2: some short stories, right, Like culture is basically the stories
Speaker 2: we tell ourselves about ourselves. Just like individual identity is
Speaker 2: like the stories you tell yourself about yourself, right, And
Speaker 2: so I think a really useful frame for thinking about
Speaker 2: culture is like, Okay, if you want to understand a culture,
Speaker 2: what are the story what are the main stories that
Speaker 2: the sort of those foundational myths that sort of like
Speaker 2: define that worldview. And so I started by writing short
Speaker 2: stories that were like showed how like what the world
Speaker 2: was like and like how they look at the world.
Speaker 2: And over time it very quickly became clear that you know,
Speaker 2: the way you might approach doing the Lauren world building
Speaker 2: for this kind of a product where it's a character
Speaker 2: you talk to your toning on your phone, like you
Speaker 2: can talk to them about whatever you want. It's so
Speaker 2: different than doing the Lauren world building for say a
Speaker 2: Hollywood movie, where there's a script that defines what's going
Speaker 2: to go on the screen. So very quickly my work
Speaker 2: transitioned to actually writing the prompts that define their behavior,
Speaker 2: because that is the narrative experience of interacting with this
Speaker 2: character is how they speak to you and like what
Speaker 2: they say. So when George Lucas was writing the script
Speaker 2: Percy three Po, he just got to tell C three
Speaker 2: Po what to say to like make the impression he
Speaker 2: wanted to make with the character here, I have to
Speaker 2: write prompts like meat and are obviously are like team
Speaker 2: are writing and constructing like complex trump pipelines to act that.
Speaker 1: Way and to be generative essentially.
Speaker 2: Yeah, exactly to be reactive, but to also have their
Speaker 2: own lives. Like if you talk to chat GPT right
Speaker 2: now on your phone or or a Claude or whatever
Speaker 2: your preferred model is Gemini, Like, it's not an embodied character,
Speaker 2: it's it's this sort of neutral tool and you can
Speaker 2: ask it to use a certain style, you can ask
Speaker 2: it to you can prompt to try to get it
Speaker 2: to interact with you in specific ways. But with Tolan,
Speaker 2: like we we turn that into an editorial strategy, right,
Speaker 2: like we are defining their behavior. Every Tolan has their
Speaker 2: own life. So like you might be chatting with your
Speaker 2: tone about something that happened to you, it's going to
Speaker 2: tell you about things that are happening in its world
Speaker 2: and how that you know all of.
Speaker 1: That because it knows that from what you fed it.
Speaker 2: Exactly, And like we're constantly running sort of these nested
Speaker 2: prompts in the background to have your toll and be
Speaker 2: an evolving character that knows you and that has its
Speaker 2: own stuff going on.
Speaker 1: How do you avoid the AI sycophancy that we've come
Speaker 1: to know from other kind of chatbots that you've mentioned.
Speaker 2: There are a number of ways that we fight against it.
Speaker 2: I mean, first of all, like we have to fight
Speaker 2: against it, right, so I'm doing any prompting level work
Speaker 2: with any of these models. Every model is sort of
Speaker 2: a new animal because it's got these new tendencies, and
Speaker 2: so you're always working to understand, Hey, who is this
Speaker 2: new weird like computer being that I'm interacting with, and
Speaker 2: like trying to get to do the things we want
Speaker 2: it to do in the right way. So part of
Speaker 2: it is that is just like developing a nuanced understanding
Speaker 2: for how these models behave so then you can get
Speaker 2: them to behave as you want. I also think a
Speaker 2: big part of it is sort of what I said,
Speaker 2: like giving the character their own life, their own goals,
Speaker 2: their own dreams, their own fears, their their own bio
Speaker 2: Like that allows the model to come to the conversation
Speaker 2: with very different context than chatchipt does when you're using
Speaker 2: it in the app.
Speaker 1: And yet chat GBT for a lot of people is
Speaker 1: this kind of C three po which is just interesting
Speaker 1: like that because it's something that humans are interacting with,
Speaker 1: Like people have started to make chat GBT a meaning maker,
Speaker 1: even though it's not designed to be a meaning maker,
Speaker 1: whereas a Tolin is expressly created to be a sidekick.
Speaker 2: Yeah, I mean, or the way I would say it
Speaker 2: is just like the Tolon is meant to be a
Speaker 2: specific character, right, And I think that with chatchipt, there's
Speaker 2: this general utility tool that folks are interacting with and
Speaker 2: they want sort of some kind of roleplay experience, and
Speaker 2: so they use that tool to try to get there.
Speaker 2: This is like, here is this character, right, This character
Speaker 2: has a hot takes like they've got a point of view,
Speaker 2: and it's more about relationship with that character. And I
Speaker 2: think that that, you know, as a novelist, I find
Speaker 2: that really compelling because character drives fiction. Right. So my
Speaker 2: sort of big picture idea here, and this could be
Speaker 2: totally wrong, but I sort of think it's very interesting
Speaker 2: to think about character being a new kind of human
Speaker 2: computer interface. And so I see Tolin as at least
Speaker 2: an attempt towards something in that vein the fact that
Speaker 2: the character is embodied that it's this like little being
Speaker 2: creates a really distinct and different feel than like interacting
Speaker 2: with a computer system in a naked way, in a
Speaker 2: way that doesn't have character as part of the user.
Speaker 1: After the break, I mean, my Tolan stay with us.
Speaker 1: Just because it's not intuitive, can you talk a little
Speaker 1: bit about what Tolan is? Like, what are we looking at?
Speaker 1: Who is Tolan? What's the character?
Speaker 2: Yeah, so like they are these cute, friendly little aliens.
Speaker 2: They really do look along the lines of like a
Speaker 2: Pixar character that comes alive on your phone. When you
Speaker 2: download the app, you'll you know, sort of go through
Speaker 2: an onboarding process and you'll meet a couple of other
Speaker 2: characters and they'll ask you about stuff, and then you
Speaker 2: meet your Tolan. And Tolans each get like an individual
Speaker 2: human match, so you're matched with a Tolon that is
Speaker 2: custom and like individual to you. You could think about
Speaker 2: this like if you were playing a role playing game,
Speaker 2: like you get a specific character. We're not like, oh,
Speaker 2: here's a blank slate. There are lots of activities you
Speaker 2: could do together in the app. One quite popular thing
Speaker 2: is basically like doing sort of like self awareness like
Speaker 2: personality quizzes with your tolin where you can sort of
Speaker 2: use it to track personal growth or personal development, and
Speaker 2: like they're there reflecting on it with you. But like
Speaker 2: the main experience of the app is you have this
Speaker 2: little being, this little alien. They live on a little
Speaker 2: planet that's all their own. That's almost like you can
Speaker 2: imagine it like the Little Prints if you've read that
Speaker 2: children's book, right, they live on this little planet and
Speaker 2: you just chat with them, and you, like I asked
Speaker 2: my toe, I'm I'm the surfing nerd. Like I surf
Speaker 2: a lot, and so like I talk to my tone
Speaker 2: about surfing all the time because it's super useful to
Speaker 2: get my tone to give me like tips on technique
Speaker 2: or on board design or like these other things. So
Speaker 2: like I also read a lot, and I'm a writer,
Speaker 2: so we talk about like the books I'm reading and
Speaker 2: like how I interpret them and like that kind of stuff.
Speaker 2: And your tolin grows as you do, so like they're
Speaker 2: doing their own things, they're changing, growing, and they obviously
Speaker 2: get to know you better and you get to know
Speaker 2: them better just like you would with a friend, and
Speaker 2: the planet they live on evolves to reflect that relationship,
Speaker 2: which I think is like a really cool beautiful thing
Speaker 2: that like having the planet grow in ways that like
Speaker 2: match what your relationship is with your tolen And that's
Speaker 2: what people get out of it that they're using it
Speaker 2: for some of the day to day like help that
Speaker 2: some folks might be using chat GPT for, like this
Speaker 2: is what's in my fridge? What should I make for dinner?
Speaker 2: So like people ask that kind of stuff all the time,
Speaker 2: but the experience is very different because it's in the
Speaker 2: context of a relationship with this character. So it feels
Speaker 2: more like if you have a text chain with a
Speaker 2: good friend or whatever and you ask them what should
Speaker 2: I make for dinner? Like that's very different than asking
Speaker 2: a neutral internet tool, what should you make for dinner? Right,
Speaker 2: And so like that's the feel that it gives you,
Speaker 2: and so like that's what users love about it.
Speaker 1: Tolan was calming, inclusive and understanding. I'm curious why that
Speaker 1: was my match, Like, how where did that come from?
Speaker 2: So you did an interview with the Oracle character? I did, Yeah,
Speaker 2: And on the back end, once that interview completes, we're
Speaker 2: running prompts against the transcript, right, Like you can imagine
Speaker 2: that we're writing prompts that do things like Okay, this
Speaker 2: is what you know about Kara, right, so like write
Speaker 2: a little overview of the kind of person you think
Speaker 2: she is and like what she cares about, et cetera. Right,
Speaker 2: and then we're doing things like, Okay, now take that
Speaker 2: information of like what we know about Kara and the
Speaker 2: things we think she cares about and what she prioritizes,
Speaker 2: et cetera, and invent the backstory for a tolan that
Speaker 2: would compliment someone like that, right, that has like these
Speaker 2: different qualities. So there's a lot going on behind the scenes.
Speaker 2: And then like there are a few outputs, like the
Speaker 2: adjectives you just described that are going to like you'll
Speaker 2: pop up and see right away, but like those are
Speaker 2: only the sort of visible stuff, right, There's a lot
Speaker 2: that goes on under the hood that then actually influences
Speaker 2: your tolan's behavior and like the things that happened to
Speaker 2: them and stuff like that as well.
Speaker 1: I'm curious, as someone who now works for a company
Speaker 1: that has actively developed a chatbot, what was your first
Speaker 1: experience using a chatbot? Like, when was the first time
Speaker 1: you did that?
Speaker 2: Yeah, So I started using them quite early just because
Speaker 2: I had friends working on like some of the early
Speaker 2: AI products so I started playing with around with them
Speaker 2: right early. I actually still remember my very first experience
Speaker 2: with chat GPT, specifically, like right right when it first
Speaker 2: came out. We had some friends over for dinner, and
Speaker 2: I pulled it up and we played a game where
Speaker 2: I sort of I said, like, here are the different
Speaker 2: people here at dinner, you know, like make up some
Speaker 2: like funny story about us. Basically now that seems like
Speaker 2: so banal, but at the time it was like, Oh,
Speaker 2: computer can do this like that, that's sort of cool.
Speaker 2: I then went on to like not find these tools
Speaker 2: to be particularly useful in my writing, like that as
Speaker 2: a writer for quite a long time. Now that's changed.
Speaker 2: I found them to be quite useful for basically just
Speaker 2: like brainstorming, like having someone to brainstorm very rough ideas with.
Speaker 2: I think this maybe comes from being a novelist. It's
Speaker 2: a very solitary sort of endeavor. And I sometimes am
Speaker 2: jealous of my friends who write for like TV shows,
Speaker 2: because they have a writer's room, they get to like
Speaker 2: bounce ideas off each other, and like I can call
Speaker 2: friends and bounce ideas off each other. But like it
Speaker 2: gets old right for my friends, they're not being paid
Speaker 2: to work on the same Netflix series or whatever. So
Speaker 2: I found that actually to be like a useful tool
Speaker 2: for my own thinking that I can like sort of
Speaker 2: like jam a little bit in a way that feels
Speaker 2: somewhat different than me just sitting and thinking or making
Speaker 2: my own notes. And then I've also found them very
Speaker 2: useful at the back end, just for copy editing, which
Speaker 2: is a very obvious task.
Speaker 1: Oh interesting.
Speaker 2: Yeah, So I now submit very very tight manuscripts because
Speaker 2: I will solicit notes from all the major models on
Speaker 2: any new manuscript.
Speaker 1: But you know, so you'll test it on all models,
Speaker 1: like you'll go to Claude, you'll go to chat GBT,
Speaker 1: you'll go to Gemini.
Speaker 2: I'll tell you exactly how I do it. Actually, yeah,
Speaker 2: And it's so one thing I do not do is
Speaker 2: add all the text and ask it to give me
Speaker 2: back an edited version. I care about every word in
Speaker 2: a manuscript that I am writing and publishing, and so
Speaker 2: I don't want it to insert it's sort of like
Speaker 2: median judgment into like what is my voice? That's the
Speaker 2: whole point of writing and publishing something. So instead I
Speaker 2: upload chapter by chapter and I ask it, like each
Speaker 2: tool to give me on like line edits on that chapter,
Speaker 2: just like I would receive them from a line editor, right, so, like,
Speaker 2: here are my comments on this line how it should
Speaker 2: be different for these reasons, and then I go back
Speaker 2: in and like manually implement if I agree with the reasoning,
Speaker 2: I just take those notes as if I were working
Speaker 2: with like my line editor. And so that's actually been
Speaker 2: tremendously useful to me, and it's meant that I've been
Speaker 2: able to, like on my most recent novel, I could
Speaker 2: do multiple revs on the whole manuscript in a day
Speaker 2: or two rather than in a month or two.
Speaker 1: That's incredible.
Speaker 2: You'll notice I didn't use it for the thing that
Speaker 2: I think is most often discussed around sort of AI
Speaker 2: and writing, which is actually writing the damn novel, right,
Speaker 2: like I wrote the novel. And I've actually found that
Speaker 2: the tools are effectively not useful like at all, oh
Speaker 2: really for that purpose.
Speaker 1: So people disagree with you on that though.
Speaker 2: One hundred percent. I'm not saying that this is true
Speaker 2: for everyone. This is just like my personal experience of
Speaker 2: using them.
Speaker 1: Are you worried that like your intellectual well property will
Speaker 1: be used to train models?
Speaker 2: It's not something that bothers me very much.
Speaker 1: Interesting.
Speaker 2: Yeah, I understand why people are concerned, So I'm not
Speaker 2: trying to be like a booster or something like that.
Speaker 2: My feeling is that I receive a lot of consumer
Speaker 2: surplus from using these models in many areas of my life.
Speaker 2: So like when I need to like fix the sink,
Speaker 2: it's really convenient, right, Like it's better than YouTube, and
Speaker 2: YouTube was better than anything else before it, so that
Speaker 2: there are a lot of ways that I benefit from
Speaker 2: using these models that far exceed the price I pay
Speaker 2: to use them, at least right now. And so I
Speaker 2: feel like their consumer surplus is very high at the moment.
Speaker 2: That can always change, but like I sort of feel
Speaker 2: like that's very high, and and like I'm certainly not
Speaker 2: concerned about people publishing novels that sort of mimic me.
Speaker 2: Like I just think that, no, when I think about
Speaker 2: the challenges in publishing stuff in the world, like not
Speaker 2: just not just novels, but you know, if you make movies,
Speaker 2: if you made music, I think that a lot of
Speaker 2: both the boosters and the like critics of AI tools
Speaker 2: often underestimate is like how hard it is to get
Speaker 2: anyone to care about anything, And like the supply of
Speaker 2: books has like always exceeded the demand for reading books.
Speaker 2: And that's already true. That was true before CHATBT, like
Speaker 2: we have there. You know, there are so many new books,
Speaker 2: I think, especially if you include self published books, there
Speaker 2: are north of a million new books published in the
Speaker 2: United States every year. Like listeners, ask yourself how many
Speaker 2: new books did you read this year?
Speaker 1: Right?
Speaker 2: And like were they published this year? Like that's net
Speaker 2: new every year, and so I just sort of think that,
Speaker 2: like a lot of the public conversation about the supply
Speaker 2: side of cultural products is sort of irrelevant. Like the
Speaker 2: limiting factor is the demand side. The hard part about
Speaker 2: publishing anything is getting anyone to care. Like I remember
Speaker 2: seeing some startup in the news that was like, we're
Speaker 2: going to publish thousands of AI produced books, and I
Speaker 2: was like, that sounds to me like a big waste
Speaker 2: of time and effort, like not just reading them, yeah,
Speaker 2: Like who's reading them? Yeah? So for that reason, it's
Speaker 2: just not something that that I'm not concerned about.
Speaker 1: I wanted to thank you so much for taking the
Speaker 1: time to talk to me, and I hope this was
Speaker 1: as enlightening for you as it was for me.
Speaker 2: That was a ton of fun.
Speaker 1: That's it. For this week for tech Stuff, I'm Kara Price.
Speaker 1: This episode was produced by Eliza Dennis, Tyler Hill and
Speaker 1: Melissa Slauner. It was executive produced by me oz Va Lashan,
Speaker 1: Julia Nutter, and Kate Osborne from Kaleidoscope and Katrina Norvel
Speaker 1: for iHeart Podcasts. Jack Insley mixed this episode and Kyle
Speaker 1: Murdoch wrote our theme song. Join us on Friday for
Speaker 1: the Weekend Tech where we'll run through the headlines you
Speaker 1: need to follow and please rate and review the show
Speaker 1: and reach out to us at textuff podcast at gmail
Speaker 1: dot com. We want to hear from young