From clay tablets to LLMs: Applying communication theory to AI-optimized content ops

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In the second episode of The Uninvited Author podcast series, authors Sarah O’Keefe and Carlos Evia examine how foundational communication theories help structure modern content operations. They unpack how AI adds new intentionality to creating and delivering content, providing the theoretical groundwork creators and leaders need to manage workflow risks and build sustainable AI-optimized content ops.

Sarah O’Keefe: It’s not that you have to go talk to your management or your CEO or whoever you’re dealing with about Umberto Echo, although that might work. It is that this needs to be in the back of your mind so that when somebody pushes back with something that is clearly nonsensical and is just simply not going to work, you can explain why. You have the foundation that allows you to move forward and say, “Okay, so as we’re building out the system, as we’re bringing AI into the equation, here’s where it’s going to do well and here’s where it’s risky.”

Related links:

• Terje Hillesund
• Marshall T Poe
• Umberto Eco
• Daniel Dennett
• Digital sovereignty in the age of AI
• From ad hoc to autonomous: The AI content ops maturity model
• Check out other episodes in The Uninvited Author podcast series

LinkedIn:

• Sarah O’Keefe
• Carlos Evia

Transcript:

Disclaimer: This is a machine-generated transcript with edits.

Introduction with ambient background music

Christine Cuellar: From Scriptorium, this is Content Operations, a show that delivers industry-leading insights for global organizations.

Bill Swallow: In the end, you have a unified experience so that people aren’t relearning how to engage with your content in every context you produce it.

Sarah O’Keefe: Change is perceived as being risky; you have to convince me that making the change is less risky than not making the change.

Alan Pringle: And at some point, you are going to have tools, technology, and processes that no longer support your needs, so if you think about that ahead of time, you’re going to be much better off.

End of introduction

SO: Hey everybody, welcome back. This is Sarah O’Keefe again, and I am here once again with Carlos Evia.

CE: Hello.

SO: And this is part two of our podcast series about the book that we’ve just released called The Uninvited Author. And we want to talk in this episode about some of the core concepts that we used in breaking down how we look at the process of creating, managing, and delivering content and what that looks like. So Carlos, what were some of the key concepts that we that we brought into this discussion?

CE: Well, we were looking at things that were a bit broader than just one type of content. We talk about content a lot in our lives. I mean, you in your work and you do as well in my work from slightly different perspectives, but with a core of what unites our experiences is technical content or enabling content, that content that at the end of the day, you’re gonna read not for entertainment, but when you need assistance, you need information to complete or perform a task. But we wanted this book to be a bit broader than just specific cases about technical or enabling content. So instead of just jumping to the life cycle of technical content, that many versions of that exist. I think you were the one who found this text cycle that came from a professor in Norway. 

SO: Yeah.

CE: And my Norwegian is pretty bad, so I will attempt to pronounce Terje Hillesund. I hope that is correct. We might get some tomatoes thrown at us for mispronouncing this media studies professor’s name. and he does research from where we can tell he’s still active. He does research on digital publishing, especially when it comes to electronic books and EPUBs. So he proposed a text cycle that had some very clear stages. What he calls them stages, right? Or phases? What does he? I think he’s stages.

SO: I’m not actually sure. And also it probably sounded better in the original Norwegian.

CE: We need to do an AI translation of this episode into Norwegian and see how it goes. So those let’s call them stages, this is our adaptation of it, are pretty much life cycle like, but they’re not just specific about one type or one combination of elements of content. So they’re very broad for any type of communication that is particularly being written, but not just delivered in text. We also applied it to multimedia and other digital approaches to text. And we have a whole section in the book saying: what do we mean by text? It’s not just words written on a page, but it can be audio and visual content, anything that is contained in bits and is delivered through electronic channels, even if you at the end of the day get it in a piece of paper that had to come from a file that was printed. So do you want to talk about the stages or should I talk about the stages, whatever you wanna do?

SO: So breaking down the stages. As Carlos is saying, it’s not just text, words on a page per se. and in fact, you could apply the so-called text cycle to spoken communication, which kind of makes me twitch a little bit. 

CE: Mm-hmm.

SO: If you think about this, and of course we’ve got a bunch of images for this in the book, but there are six phases to this text process or cycle. The first one is write, which is really having the idea. Then there’s produce, which is something like writing it down. There’s storing, which, you know, in a digital content world would be parking it in a file or a database. There’s representation. To represent it is to format it and make it look a certain way. And then you distribute it, and finally you read it, or you consume it. Now, most of us, if you’ve ever thought about this, which most regular people don’t have any need to, think about writing and reading. There’s an author; they write some stuff, and then there’s a reader, and they read the stuff. But as you start breaking down this process and thinking about what really goes into that, if you go back to the earliest communication, so now we’re talking about spoken communication. Well, the process of writing, of creating the idea, of packaging that idea of storing it, of representing it, which is to say, to use your words to speak it. And then you use your words also, your voice to distribute. 

And then you’ve got the reader, the consumer, they’re sitting right there listening to you. And so this entire six-phase process is really just two, right? It’s two actions. I speak, you listen. And then all these other pieces that are represented in this text cycle are all embedded in that little two-step process. The minute you introduce actual writing, the process of putting something on a clay tablet or piece of paper, which of course came much, much later, well, now I have an idea in my head, and then I take a pen or a stylus or a chisel or something, and I actually encode that information onto a tablet or we’ll go with paper, right? We put it on a piece of paper. So I’ve now produced it using visible marks, and I’ve stored it on that piece of paper, and I’ve represented it on that piece of paper. But the key thing is that I have not yet distributed it because I haven’t distributed the idea. Now if I hand you the piece of paper and you drive across town and hand it to somebody else, that’s distribution, and then they read it.

SO: And so you can see this process of decoupling the phases starting to happen. And the key thing is when you look at digital content, we decouple more pieces. It gets more and more fragmented, and there are more and more people involved, more and more different roles involved in the process of having an idea, encoding that idea in some way and then representing it in some way and delivering it downstream to the person who finally consumes it. And so that was kind of the fundamental starting point for this book was to look at this text cycle and ask the question of: okay, well, what does it look like to have this text cycle in typically now a digital workflow? 

And now we introduce AI. And when you look at the six phases that we have here, it turns out that you can use AI in different ways at every point in the text cycle. And I think this is why, as authors, as content creators, looking at AI is so difficult because there are lots and lots of different things we can do with it. It’s not just go online, open up a chat bot and ask a question, which is how most people, the vast majority of everybody, that is how they interact with AI. But as an author, there’s a whole bunch of other stuff going on. so did you want to talk a little bit about what it looks like at some of the points in this text cycle to introduce AI.

CE: Yeah, but I think what something that I would like to mention is that we didn’t just use that one lens to analyze how content and communication has evolved based on this life cycle, the the text cycle, to get us to where we are right now working with artificial intelligence. So instead of that one lens, we combine it with other perspectives from different disciplines and particularly from history, we borrow the work of Marshall T. Poe about the ages of human communication. So Poe, who by the way is from Alabama, not from Norway, the develop a framework for studying human communication across history.

So Poe had five ages of communication, which include the age of speech, the age of manuscripts, the age of print, the age of audio and visual media, and the age of the internet. So what we did is to put a Hillison’s text cycle across the ages that Poe documents in his model to expand that and get to propose a new age of human communication that we surprised called the age of human communication with AI. And we were able to I want to say map the stages of the text cycle into what communication looks like now with artificial intelligence. And we start the book in very, I don’t want to say naive, but conservative ways of presenting artificial intelligence as an assistant with a, you know, we understand that people are using AI across the stages of the text cycle as an assistant for writing, as an assistant for producing, storing, and eventually as an assistant for reading, because readers are using AI chatbots and AI agents to consume content. 

And it gets to the point in which as the book progresses and you go to different chapters, and the title of the book I will remind the listeners is The Uninvited Author, because it’s precisely based on the idea that we have the tech cycle with humans, and humans have traditionally been the developers and readers of the tech cycle using machines and tools at different stages of the text cycle, but at the ends, here comes the little cart again outside.

SO: Yeah. Is this what this is? The uninvited cart.

CE: Buy a little cart. It’s the uninvited little cart. So at the end and at the beginning of the tech cycle across all of the ages of human communication in history, there’s a human being and a human being. But now it’s a human being and/or a machine. It’s a fancy silicon machine and not just a mechanical machine, but they are machines. And that has really modified the approaches for developing and interpreting content in this new age of human communication with artificial intelligence. And that’s why we took the liberty of proposing our new age following the model of Marshall T Poe. And a funny anecdote is that I’m gonna reveal all the dirty laundry. When we were writing the book, I heard a rumor that we forgot to include one of the listed stages of the tech cycle, and also one of our very effective and kind reviewers noticed that one of our invented stages of the era, the age of human communication with AI was wrong and we had to rewrite it. But I promise you that the version that was published incorporates all those comments and if you identify any other gaps. We blame it on the AI. 

SO: The worst part about all of this is that because we really limited our use of AI in writing this book, we don’t get to blame the AI for anything. So we’d like to, but sadly it’s all us. So the text cycle, and then we’ve got Marshall Poe. And then, you know, the third thing is because like Norway and Alabama I mean, what’s the average of Norway and Alabama? It’s Italy, obviously. And so we brought in Umberto Echo, who well, most of us probably know about him because he wrote a bunch of very literary detective novels that involved medieval friars, and that was super fun. But he also wrote about communication and fundamentally that as a writer, I am trying to communicate. I have a certain intent in what I’m trying to do. And the reader has maybe a different intent in using a document or in using the content that I wrote. And then the work itself, the document, the podcast, the thing, the article of communication has its own intent. And of course, what we’re finding now is that you add to that the fourth intention, which is the AI, the algorithm sitting inside the AI. Now, AI is not people.

CE: Not people.

SO: AI is perhaps made of people or made of people’s ideas, but AI is not is not people. And it doesn’t have intent in the same way that a human has motivation and some other things. But algorithms have input, and they have processing, and that leads to certain kinds of outputs and outcomes. And so an algorithm can have its own intent in the sense that there’s a certain kind of result that it is pushing towards.

CE: Yeah. And one of the components that I want to mention, and the book is kind of a geeky book because we write about topics related to technology, and that’s true. But it has a very strong humanities core. And humanity is not just…

SO: And really bad puns.

CE: And really bad jokes about people with weird names, but that’s a topic for another episode. I’m gonna completely go in that direction in another episode, I promise you, because at one point the book started as a love story. There are going to be two characters, Margarita and Cosmo, who fall in love, but then we went in a different direction because it was not a fiction book. Anywho, the humanities base of what we analyze in the book, and this is where I want to really emphasize: this is not an AI slop book that was written by AI. It was written by people and incorporating traditions across different disciplines. So we have the historical component; we have the history from Poe, we have the media studies component from Hillesund. And we’re gonna get, and Sarah already talked about it to the semiotic component from Umberto Echo. But from a philosophical perspective, Daniel Dennett, who died a couple of years ago, was a philosopher from Massachusetts. And one of the many things that Dennett wrote in his career was a theory of interpretation that says that we as human beings, when we encounter a phenomenon that we don’t understand, we tend to treat it as if it were a being that has intentions, that has intent. 

So combining the perspectives of Dennett with what Echo wrote about the limits of interpretation and how readers have their intentions when they encounter a text, and here again we go back to text being not just words, that come with intentions from the human authors. Echo was very against the idea of the school of deconstruction; I’m getting super geeky on this. I promise you, I’m not gonna continue on this path. Was a very strange school of thinking that said that anything goes. And if you take a book, you can interpret it to be whatever it is that you want it. If you find a poem, you can interpret it to be a recipe for making cake. And I’m making very stupid examples here. I apologize. 

Echo was very against that. And Echo said, yes, go ahead and interpret things in different ways, but there is a point in which your interpretation of a text is going to be silly and nonsensical. So that’s why he proposed the text itself has its intentions that have the primary purpose of avoiding or preventing that people are going to interpret a chicken recipe to be a love letter. So that’s nonsensical. We don’t go there. If you read the chicken recipe, it has steps. It has ingredients, it has prerequisites, and it has pictures of a chicken that is not a love letter unless you love chickens. But we’re not getting into that by any means. 

SO: Too late.

CE: And that’s what we came up with our contribution of the fourth layer of intentions, which, like we said, if you take a look at how the text cycle in the age of human communication with AI now includes AI agents, AI tools as readers and as authors, they come with their own intentions. And their intentions, not human intentions, are a hodgepodge combination of the training materials that the agents came from, the version of the model that you’re using. If your model is allowed to go out and perform web searches on the fly. If it keeps any record of interactions with the reader. So those are intentions that get imprinted into the text cycle in the age of human communication with AI. And that’s where we really created this prism of different approaches coming from the work that we do in technical communication, but also based on bigger conversations about history and communication studies and philosophy without making it sound too nerdy. I promise you, if you have read the book, you will see that there’s some nerdy elements, no doubt. But we try to make it accessible for our peers, our colleagues, managers in our industry, and not just in technical communication, but people who work across different sectors of content. And have to acknowledge, or have come to terms that machines are now being authors in the text cycles whether they invited them.

SO: it’s important to understand some of this underlying theoretical work and some of these frameworks, because as you move into this as a content creator or as a leader, as somebody that’s responsible for some sort of content, if you don’t understand how these things interoperate and fundamentally how they break down and how you can and cannot break them down, then you don’t have any possibility of actually bringing your AI-based or AI-enabled content operations under control. So it’s not that you have to go talk to your management or your CEO or whoever you’re dealing with about Umberto Echo, although, depending that might work. It is that this needs to be in the back of your mind so that when somebody pushes back with something that is clearly nonsensical and is just simply not going to work, that you can explain why, that you have that foundation that then allows you to move forward and say, okay, so as we’re building out the system, as we’re bringing AI into the equation, here’s where it’s going to do well and here’s where it’s risky. These are the pieces that it will not do well, and you know why. So fundamentally, we weren’t that interested in the question of what can Claude do today, or what kinds of ridiculous things can you make ChatGPT say if you feel like it.

CE: Mm-hmm.

SO: The fundamental question is much more how are large language models put together. And what kinds of things are they going to be good at and bad at? And how do you bring that into a workflow? And how do you understand the risks that you’re introducing and the benefits? So what’s the cost-benefit analysis of having an LLM in your in your process? And, you know, we touched on this at the very top of the podcast when we made some joke about it’s the AI’s fault, right? You know, if there’s a mistake, it’s the AI’s fault. Well, so first of all, it’s not because we didn’t really use much AI, but fundamentally and secondly, we don’t get to disclaim responsibility. if you’re in techcomm or e-learning or anything else and you put out a document and it was 100% AI-generated and then it’s wrong, the organization, I mean you may get to say, well, you made me use AI, it’s not my fault.

CE: Mm-hmm.

SO: But the organization doesn’t get to disclaim responsibility for the document because it was AI-generated. They’re going to have significant product liability. And I believe, on no evidence whatsoever, but I believe that when the product liability lawsuits come, and they will, right? The organization that goes up in front of a jury and says it’s the AI’s fault is going to lose. And I think they’re going to lose more than they would if they said, well, our humans did our we tried our best and we made a mistake, as opposed to, yeah, we offloaded it onto the AI. We didn’t read the results. We fired all the people that are creating content. And we’re sorry that you were horrifically injured in some way. But we weren’t sorry enough to do the work to prevent it, right? So there’s going to be huge product liability. And I think the jury sitting there is going to say, well you tried to save money, you tried to cut corners, and this is the result. And so I believe that ultimately the legal outcomes of excessive AI use are going to be you know, problematic enough to kind of reel people in. 

CE: Mm-hmm.

SO: Now that’s a very US-centric perspective because in Europe there are different regulatory issues. But even in the US with our current general lack of regulation, I think you’re going to see that product liability lever applied to force organizations to do better.

CE: I remember that when we were writing the book, we were in very early stages of the book, you posted to LinkedIn that we were writing the book, and you kinda opened it to people to propose if you were writing a book about AI and content, what would you want to see? And a few of the people who responded to that post were expecting concrete formulas, concrete prompts or recipes for creating agentic AI workflows or what should I ask my chatbot to have good content. And that’s not the book that we wanted to write. We wanted to write a book that will make people we hope think and consider those implications of using AI for creativity, for productivity, and like you said, for legal consequences of delegating everything to the artificial intelligence agents and expecting magic. 

And that’s what I keep going to. I keep saying that the problem is when people see AI as this oracle that is going to just magically solve all the problems without understanding how it works. And it is a monster. AI is applied to mean many different things. And we write about this in the book too. But also, it’s how what are the consequences of bringing AI as an invited component into our professional tech cycles. And by the way, going back to your LinkedIn activity, I think a couple of days ago you published something that said we are not anti-AI, we are anti-slop. And I think that’s something that is reflected in this book. We are not anti-AI. We have a whole section in the book that I think it presents in very good and honest detail how we use different tools that include artificial intelligence in the production of the book, but we were very cautious about avoiding perspectives of presenting AI slop, passing it as human products. There are so many books. If we go back to our main corner of technical communication, there are many books that have appeared on Amazon in the past few months about the DITA standard.

That you can see that no humans were involved in the writing of those books. Somebody just prompted a chatbot and said, go fetch information about DITA. And that’s not the book that we wanted to create. This is not a book with concrete recipes on how to use things with AI. And it is not a book that we delegated to AI. It’s a book written by humans coming from different workplace, practitioners, and academic disciplines, asking questions about what does this mean and how do we go to the next stage and learn to live with these synthetic authors without losing our humanity and without getting in trouble.

SO: And I hope that this book is valuable to the people that are going to read it because it was painful to write. I mean, it hurt. So I, you know, if I’m gonna go through this pain and suffering, then I wish for it to be useful. And if people look at it and say, you know, you could have prompted your way to this with AI, then I’m probably just gonna like curl up in the corner and cry.

CE: Yeah.

SO: So all right, on that cheery note, we will leave it there for this episode, and we will return and talk a little less about theory and a little more about fun things you can do with synthetic content and what that means to our operations. So thank you, Carlos, and I’ll see you on the next one. Bye.

CE: Thank you. Bye bye.