Will computers one day write the great American novel? What will the future of human/machine creative collaboration look like – and what came before now? In this episode of the Stuff to Blow Your Mind podcast, educational technologist Mike Sharples discusses the book “Story Machines - How Computers Have Become Creative Writers.”
Welcome to Stuff to Blow Your Mind production of My Heart Radio. Hey you welcome to Stuff to Blow Your Mind. My name is Robert Lamb and I'm Joe McCormick. Joe. While you were out, I conducted an interview with educational technologist Mike Sharple's on the book he wrote with Rafael Perezi Perez, Story Machines, How Computers Have Become Creative Writers. It's a fascinating read about the nature of storytelling, our history of attempting to instill the spirit of storytelling into the machine, where we seem to be going with this technology, and quite remarkably where we are already. Well, I can't wait to hear this interview. All right, Well, without further ado, let's jump right in. Hi, Mike, welcome to the show. I'm here. It's good to be at. The book, co authored with Rafael Perez Perez is Story Machines, How Computers Have Become Creative Writers, Publishing July five. It's a terrific read, but it has to be stressed from the outside. That's the storytelling isn't just a pastime that humans engage in. Storytelling is something greater? Right? Yeah, So storytelling we suggest in the book is something that's fundamental to human existence and has been for millennia. It suggested that instead of language coming first and then storytelling involving after that, perhaps it's the other way around. That perhaps storytelling started as a way of human communication through mine, through expressive gestures, and then language followed from that. So we want to make the point that storytelling is fundamental at a neural level, it's how we make sense of the world. It's at a cognitive level about how we create narratives to explain our existence, and in the social world, it's the stories we tell to each other that makes us who we are. So when we're talking about machines engaging in storytelling or story creation, we're really getting deep into human creativity and human identity. Then, yeah, we are. And it's both a fascinating insight into human creativity and it's also something the threat. So for centuries, writers have been fascinated about this idea that a that a machine might take over their craft, that a machine might become a storyteller. It goes right back to Jonathan Swift, for example, in Gulliver's Travels Coming Across a Weird Academy, where apprentices were manipulating a story machine which churned out academic texts right through to modern writers such as Roll Dow. He wrote a short story about how an author was selling his soul to a machine that generated short stories for him. So it's become something that particularly professional authors have been fascinated by this idea that a machine might be as creative as a human and also giving us insight into human creativity. Now, of course it's one thing to imagine these machines. You point out that they're they're necessary precursors in linguistics, literary analysis, and other fields to even get to the point of considering asking a machine or or making machine they can write a story or novel for you. Yeah, and I think there are there are a number of ways we can approach this. So one of them is to look at language. So we are language machines. We we have been trained in how to manipulate language as humans, and we can now design machines that could copy that in a very expressive way. So I'm sure we'll come onto that. But AI systems such as GPT three that are expert wordsmiths. So that's one route and other route is simulating characters. So some of the newer computer games now have stories nonplayer characters that can't tell stories to the human players. And then the third way is to build models of the creative mind. And that's what my colleague Raphael pre Perez has been doing for many years in his Mexican program, is trying to build a model of the human creative mind. So the different routes for coming at modeling storytelling and understanding storytelling with machines. And the one that you mentioned that I think is very fascinating is Vladimir props morphology of the folk tale. This idea of taking apart of folk tale tradition and in figuring out like what are the basic strokes, what are the basic elements, and thus creating I guess, sort of the palette for recreating stories. Yeah, this was back in the early twentieth century that Vladimir prop was part of a group of Russian linguists who and folk tale academics who became interested in the morphology the structure of folk tales, and he realized that Russian folk tales had this very similar structure, just as fairy tales in other Western traditions have, and so he set about trying to ride a set of rules that would both analyze these folk tales and show their underlying structure, but also could be turned around to generate them. That if you use these rules essentially as what we now call programs or algorithms, they could be employed to create new folk tales. And so he set the foundations for the structural analysis of stories way back what a hundred and twenty years ago now, And interestingly, some of the earliest computer programs to generate story were based on props formalism. It was really if you look at it, it's really like a very pair down computer algorithm. Now answer some of the first actual text generating machines. You mentioned a few different examples of this. Which are the most important to mention or which one is the most important to mention? So one of the earliest ones was by Christopher Stracci, who was a colleague of volenteering working in Manchester, and he developed a very very early computer program on one of the first prototype computers that generated love letters Victorian love letters. Um, and we can speculate on why he would want to write a program to generate love letters, but he did and pin them up on the wall of his lab. And then since then there's been a number of people who have particularly taken a linguistic approach, and so one of the pioneers was a linguist called Sheldon Clade, and Sheldon Klein had this big, grandiose project to try and model human language production as a as a as an algorithm, as a computer program, and then through this trying to understand the origins of language. And so, along with a group of colleagues, many PhD students, he produced one of the earliest programs that generated stories. It generated murder mysteries, a sort of country house Agatha Christie type mysteries, and it was part of this big project to formalize language in a generative way. The problem was the program the stories that generated were pretty trivial. There was people gathered at the country house, there was a murder, somebody tried to investigate it the end, and so although it was seen as a novelty at the time, it wasn't really risk acted for the Great linguistic project that lasted for twenty or thirty years in the nine nineties, and there were a number of attempts to write entire novels by computer and probably The most interesting one was by Geckll Scott French, who programmed a Mac computer to generate a novel in the style of Jacqueline Susan. I've got it here. It's called Justice Once, and it is a complete published novel in the style of the pot boilant author called Jacqueline Susan, and it seems to be genuine. There's a picture of him with his Mac computer on the cover of the book. And it took him eight years to design this very early AI system that would mimic the style of this author, and he engaged that eyed dialogue with the program to generate an entire three hundred page novel. So that was probably the first, I'm right up to this day, greatest example of story writing with machine. What's fascinating now is that what took him eight years to do could now be done in a few seconds with the most recent AI UM generator programs. Yeah, in the book you you write them just to read a quick quote quote. It took just twenty years ago from a program that wrote love letters to one that created complete short stories. Uh, and a further twenty years to a published three page novel in partnership with the computer Uh, it's fascinating to think about. You know this, this the technological advancement during that time in broad strokes, like what I mean, what were the key advancements going on here that made this possible. Well, the first advancement was to be able to have interactive computer systems that you could program in a high level programming which and that's what Christopher Straitchy and Alan Turing were working on, and that they could then demonstrate this in generating very simple love letters. The next stage was to be able to produce grammars, generative grammars, and this goes back to the work of prop who realized that you could have grammars that didn't just generate individual sentences, but could generate entire stories. That you could describe the structure of a story in terms of something like a formal grammar, and that in THEES there were a number of projects to put that grammar into a program that would generate a short story. That's what Sheldon Klein and his team did. And then the next step beyond that was to write symbolic AI programs that modeled the style of a particular writer, and that was the great achievement of um Scott French. It was a symbolic AI expert system of style. And then we come right up to date. And there are programs like GPT three, which are hugely competent and well trained language systems, So they aren't rule based systems. They don't have something like the Sheldon client grammar inside them. They have been trained on billions of pieces of text and they have many millions of interconnections that create an internal language model which they then use to generate texts in particular styles. You can start it in a style and it will continue in that style. You can give it an instruction of what sort of story to write and it will continue in that story. But the really important thing to say is that there are two different sorts of AI. So the sort of AI that's got French used was writing explicit rules. That's why it took him eight years to code these rules to imitate one person style. The GPT three type AI transformer programs induce infer those rules from being trained on billions and billions of pieces of texts. So there are two different sorts of AI. Both had their strengths and weaknesses. UH And one of the fascinating things of the future is whether we can put them together, whether we can merge those two different sorts of AI into the sort of universal story machine. Wow. And so GPT three is the current model, Is that correct? Or are we had four yet? So there isn't a GPT four yet, although I'm sure there's one in the pipeline that continually revising GPT three. And just for those who don't know GPT, the GPT models were developed by and still being developed by company called open Ai that was founded by a group of entrepreneurs including Elon Musk and others, and that company was set up to explore the opportunities of AI for social good. It has developed a number of different programs. There's one that it's developed for art called Dally, which can do the same for art and images as GPT three can for for words and stories. But the GPT three now it's its third generation. In essence, what it's been, what's how it works is it's been trained on billions of pieces of text. It uses those texts to form an internal model of both the surface structure of language but also the internal structure language essentially how the world works. And then initially the early GPT models were sentenced computers like very highly trained, suped up sentenced computers of the sort that you've got on your mobile phone. But they can look back at the last five words or so. They haven't a big attention window, so they know what they've written before, and they use this to continue in the same style, the same structure. So they give a very plausible simulation, a very plausible indication of coherent language, as if it were being written by a human. Now, the problem is it's highly believable, but it doesn't have any sense of itself. So these systems can't reflect on what they've written. They can't look back and say, does this makes sense? Does this fit with a good model of the world? Is it legal on his decent? It doesn't. In essence, it's they're a moral They don't have any internal sense of what's right and morality. And so as story machines, they're great because they can tell fascinating, plausible, engaging, sometimes even poignant stories. But for other purposes like writing newspaper articles or writing student essays, then they can be dangerous because they don't know what they've written, and they don't know whether what they've written is decent, honest, and truthful than now. Our listeners can can actually get a taste of this by going to story slash machines dot net. You have an interface here where you can put in just a title or also a title and in some text like an opening line of a of a story. And this is powered by GPT three. Correct. Yeah, that's right. So what I did was wrote a website with an interface to the most recent GPT three language model. So it basically provides a very simple way for you to write the title of a story, a few opening words, press the create button, and it comes back with about a two d and fifty word introduction to a short story. So it gives you a taste of what GPT three can do. And yeah, I really recommend that you go and try it. Um. I launched it just a couple of days ago, so people have already been generating fascinating short stories using that, So so go and give it a try. It's story hyphen machines dot net. Yeah I was. I was firing this up when I was reading the book yesterday, and yeah, eventually I was having to bring my son over and showed to him. I was really impressed toying around with it like trying having a title that sort of suggested a certain genre, maybe throwing in a first sentence that that was the record that the reference to certain genre. And then also I was really impressed when I would say, put in a title and then put in the first line of an existing short story by an author. I think I used Clark Ashton Smith as an example, and I used um Corny McCarthy. I put in a line of Corny McCarthy's work, and I was impressed at how well it seemed to model a portion of writing as if it were by these authors. Yeah, exactly. Um, I'll give you an example, because it's quite quite good to show an example. You can cut it out if you want to. So so here's an example one that I did on Ernest Hemingway in London. The fog came in from the river and it was cold for April. I walked up past the British Museum and turned down towards Holburn. I had a lunch date with Harriet the Criterion, and I was early. It was one of those heavy grade days that seemed to press down on the city, weighing it down. The traffic moved slowly through the streets, and the people hurried along with their heads down trying to get out of the cold. I glanced in the windows of the shops as I walked, looking for something to buy Harry for his birthday. I knew he'd appreciate a good bottle of scotch, but I wanted to get him something else as well. That's just the start of as a story in Ernest Hemingway style, and you can give it whatever style you want. It's I found it works best when you do a weird juxtaposition. So there was someone just a few hours ago did one on the Sad Sandwich, and it was a really poignant, sad story about a poor, neglected sandwich. So try doing some some juxtapositions at words like that. Yes, absolutely, and I'd love to hear back from from listeners after they've toyed around with us and explored it. But of course, recognizing the power of of this technology, Uh yeah, we we certainly get into this, this area of of anxiety perhaps, but also hope and opportunity. Um I guess on the anxiety side of things. The first place my mind went as I remember seeing Max Tegmark reference a kind of an illustration that was like a topography of human abilities and jobs with the idea that at the higher elevations were going to be more protected from the rising sea levels of AI. So chess and jeopardy were already in the water, uh, speech recognition, investment, and social interaction there in the lowlands they're going next. And then in this particular image, we had science as the highest peak, just above the peaks of book writing and AI design. So I was just wondering, do you feel like this representation was accurate or and or have the water has just risen so high already? I think every risen high already. I think the ones that are going to be protected from the rising tide of AI are probably the caring professions, um, the nurses, the child careers. But any profession that works with words, he's going to find both an opportunity and a threat, I think in generative AI. So the opportunity is that it's a new kind of tool. The tools that we've had up to now have tended to be ones that slow down writing, um, like the saurus or spell corrector that they make you pause and check. You can do them at the end, but there's always a temptation to look up a word to slow down. What's different about these is that they can be used to speed up your writing. You can, and I've tried doing this, writing a paragraph when it starts to dry up, them handing it over to the machine to write the next paragraph. I'm not a fiction writer. I found it quite empowering to use GPT three as a writing buddy. So I would write a paragraph, it would write the next paragraph and probably take it off in some unexpected direction that I would then have to follow, and it might introduce a new character, a plot twist, and so both as a tool for budding writers and also perhaps a prop for professional writers, particularly ones with deadlines to meet, then that's the opportunity. I think the threat is the inverse side of that, that if you either see it as a crutch that rather than trying to do your own writing, you just hand it over to the machine, then it's very easy to become lazy. And also, as I've said, they are a moral machine. So if you're trying to do scientific writing, or you're trying to do accurate journalists them, then beware because they may well throw in some entirely fake research study, some entirely inaccurate, fake reference, um, perhaps reference to some completely non nonsensical or inaccurate event that's happened in the world. So you've always got to be aware of the facts that it throws up. And there's a good reason for that that it isn't a fact checker. It isn't a Wikipedia or even a Google search. It is a language machine. It's loves, you know, anthropomorphic sense. It loves playing with words, but those words don't necessarily make sense. So if you're going to use tools like GPT three as AIGs for writing, then you have to be very careful that you cross check the facts and the output of that machine to make sure that it is accurate and honest and truthful. My mind also went to um the possibility of of of almost accidental plagiarism because I put in the first line of a Clark Ashton Smith story and it it threw in a fascinating plot twist that was not in the original story, and I don't think I've ever seen in a story, and so part of me was wondering like, well, well, you know, I should I should latch onto this, maybe I could use this. But then the other part, you know, the lights coming on in my mind were saying, but hold on this. Just because I haven't read it doesn't mean it doesn't already exist out there. Might Uh we run into situations where, uh, the AI is is reproducing something you know, perhaps you honestly, if we want to use that term when in in in actuality, it may exist out there in some story or another. Yeah, I mean, I think the first thing to note is that it's not working at this sort of word and sad tense level. So it's not copying bits of text from the web or from published books. It's working below that, basically at the phone name level. It's putting together pieces of words, but it's putting together these pieces of words in a hugely proficient way. So I've tried taking the output of GPT three and doing Google search on phrases and sentences, and you don't find them. So it seems like they are genuinely producing novel pieces of text. So, for example, if students are going to use these for writing essays, which is already happening, they're already companies that are advertising the services of AI generators for students to write their essays. Plagiarism checkers won't detect them. I've tried putting them through plagiarism checkers and they of sort of nineties five originality. So they're not copying bits of text from the web. They are genuinely generating new language. Now, of course, there are phrases that may pre exist, and if you give highly constrained styles like Shakespeare's sonnets, then it may come up with previous lines from other Shakespeare sonnets. But providing you give it a broad enough brief, providing you give it a general enough style, or even if it's from a particular author, then it will generate original text. And it's still a bit scariest too. You know, I've talked about this with other people and said, but surely it's copying from the web. No, it isn't. It's generating. It's generating new text in the style of that author, or in the style of that piece of fiction or piece of journalism. So you already touched on like this the collaborative possibilities here. But having touched on in school papers and such, what do you think are the the educational opportunities with this technology. I think the main educational opportunities are for beginning writers. It's a way to explore expressivity and creativity. One of the problems when you're beginning writing is you tend to see everything as being a linear process. You write some words, you write some more words. There's a flow of writing. It's very difficult to get out of that flow and to think about alternative ways of expressing something, how it might be different. And what machines light GPT three can do is help you to see another way of continuing, another way of expressing your ideas. It will look back over the last five words or so that you've written and perhaps take it in new directions. So it's a way for buddying writers to explore possibilities. And you can take what you've written so far and press the create button a number of times, and each time it will take your writing in a different direction. So that's one way. Another way is for in a class situation, for a teacher to generate a number of different articles on a topic. So to give a topic like what's the effect of climate change on rising sea levels and get it to generate a number of different articles and then to critique them because as I say, it doesn't always get its facts right. And so to look on these as pieces of journalism you might find on the web and to take a critical stance. So it's it's a good tool for a teacher to give some generated articles to students and say, criticize these. We know they're written by machine, so what's wrong with them? Generally the ear face structure is pretty good, the spellings correct, the style is good. But the deeper you go into these machines generated texts, the more you find problems with them. So it's it's a good class exercise. And then lastly, I think is that it's going to be another tool companion that writers use. Just as in the early days of word processes, there was a lot of criticism that it was slowing down writing, that you were reading from the screen rather than from the page, that style checkers were making writing more conformists. There will be quite rightly people who say these new tools are forcing a machine type creativity. But I think if we use them wisely to extend and to critique our own creativity, then their own resting her and exciting opportunities. Do you think we better understand human creativity for having gone through this technological journey. That's why I started on this h this journey with my colligraph I am. It's because I started work as a PhD student on trying to understand children's creative writing and to develop tools for children to develop their creativity. I became fascinated by machine creativity to try and explore what is it that a machine can do in terms of creativity and where does that stop? So what are the limits of machine creativity? And beyond those limits, how does that relate to human creativity? What is that the week we can do that a machine can't. And now, over the years, perhaps the gap between machine creativity and human creativity is narrowing, but it's still there, and it gives us insights into the way in which we write, in the way in which we think. And because these new generative AI programs don't work in a human light way, then it becomes a really interesting challenge to say, what's alien about them, what's different about the writing they produce that shows they aren't human? And what does that say about human experience and human creativity? Than now, looking into the future and getting more speculative, UM say, I'm a fan of Frank Herbert's done novels. Do you see for see a future in which one would just be able to ask an AI to generate the final books in the series that Frank would have written, Uh, perhaps more novels in this universe he created that sort of thing. Or say you're a fan of a particular short story author and you're you're like, why would I read anything other than stories by this this particular author. I'm just going to ask the AI to generate more of them for me. Um, it might we easily arrived at such a future. And if and if so, like, what does that mean for us as both consumers and producers of creative writing. I think we'll arrive at that at that space pretty soon. I think they will be pastichious, and but they may be pastigious that you can't tell from the original and that there will be certainly fans of authors like Frank Herbert who will be happy to accept them as generated in Frank Herbert style, particularly if they have interests the new characters, interesting new plots that will happen with short stories and Neil Gaiman type short stories. I'm sure that will happen quite soon. Um, if it hasn't happened already, there may be plan fiction forums where those sorts of AI generated pastiches are already circulating, but I think there's the future is more likely to be around interactive fiction. So um. At the moment, computer games are kind of reaching a plateau that the graphics are becoming more and more realistic, the interaction is becoming more and more engaging, but the AI is lagging behind. Soon you'll be able to have AI based characters in games that can tell stories that you're not only asked to solve a problem or guide you to the treasure, but you can engage with them as conversational partners. They will take the story forwards, and once you do that, then you can get onto interactive soap operas, interactive worlds where you've got both human and machine partners now that can take you into all sorts of dark areas, but also into all sorts of engaging aspects of new interaction, new immersive fiction, new types of social interaction that involved both machines and humans. So I think rather than trying to emulate a particular writer, I think developing interactive fiction where you have a continual um story that you can dip in and out of with other characters human and machine will likely to be the the most engaging, and probably the most influential use is of story machines in the near future. In the book, you go into several different wonderful examples of of how we've reached this point, you know, along the line along the road with video games examples I wasn't familiar with, like Colossal Cave Adventure, Dwarf Fortress, UM. So, I guess most of these examples of these been These haven't necessarily been part of, like saying, the mainstream of video game culture. No, they they haven't been part of the mainstream. There's been a kind of tributary. So the mainstream has been sort of from Pong and Space Invaders onwards in terms of graphics and interactivity, and then we get to Grand Theft or to where you have hugely realistic simulated worlds m and it's the gameplay, the action, the game mechanics that's really important. But there's been another tributary that been mainly followed by people who are fascinated by stories and words and storytelling. And it started with Colossal Cave Adventure, which, for those of you who don't know, was in the late nineties seventies, um by UM a couple who were cavers and Um the Crowder, I think that's his name. I would have to check it. Um he developed this program which generated a world that you could explore. You could go down and explore a cave system, and it was all done entirely through text. So you are going through a dark forest, you find a great in the forest floor. What do you do next? Your type go down. It then comes back with a description of where you are. You are underneath the forest floor, in the spring of a stream, and then you can go left, you can go right, you can go down. So you are guiding this character through a textual world, and the more you get into it, the more you engage with not only descriptions but also characters in that world, and you could collect things, do things, So it's a textual world that you're exploring. UM. Since then there have been other extensions of that which make these textual characters more believable, so actually interact with them. They cannot only give you things, but they can behave as real agents in the world would real humans would. And Dwarf Fortress is an example of that where you've got a hugely realistic world. And there was an example I gave him the book about Drunk Cat, and the designers of Dwarf Fortress had created all sorts of properties of animals, but the ability of cats to drink alcohol had deliberately not been programmed him. But in the tavern and war Fortress, there were these cats that were lying dead, and only through interacting with the code did they understand it. Did they realize that what had happened was that the cats went into this tavern, that people in the tavern had spilt alcohol in the floor, the cats had walked through, the cats had licked their paws, that cats have become poisoned by alcohol. So you have these hugely rich and realistic worlds that are realized through text. And so it's become as a bit of a tributary of game playing because you do have to interact with with text with words. But as they big into merge now with the mainstream games, then you will have spoken dialogue. You will be able to meet your favorite characters in soap operas in streaming series and you could talk to them, you can go on dates with them, you can go holidays with them, um, you can be part of their story. So it's bringing together those two streams of game design these rich visual worlds and now these textual, believable story worlds that I think is going to be the next generation of interactive games. What's gonna be really exciting to see this come together. Yeah, I think it will, and I think one of the things in the future. One of the opportunities in the future is that you will be able to live in the worlds for an extended period of time. So you don't just play the game for forty minutes just like you have a TV series. You'll have a TV series where you live in this world. Now, that's both scary and exciting to be able to live for extended time in a virtual world where you can talk to and engage with the characters. So what do you think the machines are going to want to tell stories about? So it's been suggested that because machines don't have human experience, they will never be able to tell stories that are experientially rich. They don't know the human condition, They've never been there, they've never fallen in love, they've never seen a sunset. So they will reach a plateau where they may produce pastiches, but they won't be able to describe or to we have the human condition, they won't be able to engage you in any deep human way in a story. Now, I'm sure that's right. It's possible you could get around that by having embodied storytellers, so embodied robots that can go out into the world, that can gaze at the sunset, that can go for walks, that can feel the wind in their metal phases. But there's another possibility, which is that already programs have something approaching a social life, that they are connected to other entities on the web. They are part of a social network. And if they can tell stories about their worlds, their worlds of being entities on the web, their worlds as being part of a connected Internet system where there are viruses, where there are software breakdowns, breakthroughs, entities that interact with each other in a computational way that we can't express, then they could be valuable in two ways. One is that they could help us to understand this complex system that is the World Wide Web. They could help to interpret the growing, changing nature of the World Wide Web in human language. But also they could tell stories. They could tell stories of their travels through the Internet. They could tell stories of how they became beings that were taught and learned through interaction with other objects in the web. So I don't think it's necessary to be embodied to have human type experience in order to tell interesting stories. That they may tell quite alien stories of life on the web. And to me, that's much more exciting and interesting than just spouting a pastiche of a human story. This reminds me of something you you bring up in in the book that that that i've that they really ring true and uh and also made me, you know, rethink a number of things, and that is that the uncanny valley, which is a concept that most of its familiar with when it comes to um robots made in the in the likeness of a human being, or or certainly when we get into computer generated imagery and films. But you point out that that this that the uncanny valley isn't really a thing in storytelling. In one sense, it isn't because stories are meant to be disturbing and unsettling. That's why we read science fiction, that's why we read crime novels because they're meant to be disturbing. So having a machine that is in some sense uncanny or disturbing in the language that it produces in the stories. That else I think we'll only add to the richness of storytelling. But where I think there is an uncanny valley is if we then say, was this written by a machine? And if so, what kind of machine? So is it a machine that was trained on billions of words from her the web that has had no experience of the world. In that case, how can it be reporting on the world? How can it pretend to have a human like experience? So if we know that the author is a machine, then it becomes unsettling because we then start to judge perhaps it's very plausible, very poignant, very evocative prose against human experience, and we realize that it hasn't had that human experience. So how do we know whether other stories are really, you know, the product of human experience? And what does it mean to tell a story based on experience? So the stories themselves I don't think need to worry, yes, because stories do have an uncanniness to them. But I think once we start to question the author of those stories and whether that story is based on genuine experience, then it becomes unsettling. All right, Well, the book again is story Machines How Computers Have Become Creative Writers should come out July five, and Mike thanks once more for taking time out of your day and chatting with us on the show. It was a pleasure. I've really enjoyed it, so thank you for asking me all right so that you have it. Thanks again to Mike Sharple's for a taking time out of his day to chat with me again. That book is Story Machines, How Computers Have Become Creative Writers is available now wherever you get your books. And if you want to get a taste of this for yourself, you can go to story hyphen machine dot net and uh it's experiment a little bit like we've been experimenting in the meantime. If you would like to check out other episodes of Stuff to Blow Your Mind, you can find it in the Stuff to Blow your Mind podcast feed. We have Core episodes on Tuesdays and Thursday's, Artifact or Monster Fact episodes on Wednesdays, Listener Mail on Mondays, and on Friday, we set aside most serious concerns and just talk about a weird film. Huge thanks as always to our excellent audio producer Seth Nicholas Johnson If you would like to get in touch with us with feedback on this episode or any other, to suggest a topic for the future, or just to say hello, you can email us at contact at stuff to Blow your Mind dot com. Stuff to Blow Your Mind is production of I Heart Radio. For more podcasts for My Heart Radio, visit the iHeart Radio app, Apple Podcasts, or wherever you're listening to your favorite shows. B B B bl bl bl, Blunt Bust presided at the Foo