Mike Atherton: Serious AI Insights from a Whimsical News Show – Episode 22

Mike Atherton Mike Atherton is well-known in the content world for his work at institutions like the BBC and Facebook and for his co-authorship of the influential book Designing Connected Content. His latest content project appears at first to be less serious. Newsbang is a daily AI-produced satirical news show. Its content is based on real historical news but delivered by AI-created stereotypical newscasters. The result is fun, but the process of creating the show has added real-world technical skills to Mike's professional toolkit. We talked about: his work as a UX writer and content designer his experiments with AI tools, including the suite of generative tools he's using to create Newsbang, a completely artificial daily news program how he accomplished his goal of creating an ensemble sketch comedy vibe his workflow for the daily production of the "news" show some of the surprising traits of his news characters that emerged as AI generated them lessons learned about the cost of producing AI programming, like the costs of prompting the variety of models he uses to build the show, including open-source models that have more lenient guard rails to permit more edgy comedic content how he creates his own guardrails to achieve the effect he's looking for in the show while still creating a family-friendly show how he developed the technical skills it takes to create Newsbang how his work with Newsbang helps in his day job his hope that more content professionals will follow him into the AI playground Mike's bio Mike Atherton brings years of experience to the UX, IA, and Content Design field, having tackled content challenges at big names like Meta and the BBC. Now, he's focused on developing UX writing systems, exploring the use of AI to do big things with tiny teams. As well as the day job, Mike is the creative mind behind Newsbang, a daily satirical news podcast that's both written and produced using AI technology. With Carrie Hane, he also wrote the book ‘Designing Connected Content’, sharing strategies for seamless digital experiences. Mike lives in the British countryside and loves working from home. Connect with Mike online LinkedIn Newsbang Video Here’s the video version of our conversation: https://youtu.be/lpDa8szujWo Podcast intro transcript This is the Content and AI podcast, episode number 22. Most of the news coverage and social-media conversations around AI and content feel urgent and important. This is serious business, but you can have fun with this technology, too. Mike Atherton has done content work at places like the BBC and Facebook, and he still does proper content design in his day job. Newsbang, his daily, AI-produced satirical news show, has given him both an outlet for his inner comedian and a venue in which to hone important new work skills. Interview transcript Larry: Hi, everyone. Welcome to episode number 22 of the Content and AI podcast. I am really delighted today to welcome to the show Mike Atherton. You might know Mike, he's probably best known as the... Well, he's best known for a lot of things, but he's worked at the BBC and a lot of other interesting stuff he's done. He co-wrote the book Designing Connected Content with Carrie Hane, which a lot of people in my world appreciate. But he's now a content designer and creative technologist based in the UK. Welcome, Mike. Tell the folks a little bit more about what you're up to these days. Mike: Well, hey, Larry, thanks for having me on. It's great to be back. Yeah, I'm a UX writer and content designer by day. I work with various product teams in different kind of companies to write everything from the microcopy, the words on the buttons, through to taxonomy and control vocabulary and all the good stuff that we UX writers like to do. And as part of that, for the last few years, I've been dabbling with these wicked AI tools that have come our way and seeing what I could do with them to try and make them generate content in a particular voice and tone or in a particular way to fit in with a brand voice or a product voice. And that's really got me interested in the styles of writing and the styles of content that models can generate if you give them the right push. Larry: Yeah, well that's why, I mean, I'm always looking for an excuse to talk to you. But most recently in December, you launched this news site called Newsbang, which is entirely AI generated. And I mean, there's a number of taglines I've heard in it, but one of them is "a taste of truth served with a side of satire,"" and it seems like there's a lot of... But anyhow, there's always to what you were just saying, well, there's so much about this project I want to ask you about. But one of the first things is there's a distinctive tone to it throughout. There's a bunch of different personalities in there, a bunch of different topics covered, but you know you're listening to Newsbang, so maybe is that a good place to start with the- Mike: Yeah, absolutely. I mean, the characters are perhaps my favorite part of it. So Newsbang, for the uninitiated, is a daily news podcast, very much modeled around a kind of nightly news bulletin. But in the kind of silly way that you might find in Saturday Night Live's weekend update or old sketch shows, like Not the Nine O'Clock News or particularly my favorite one, The Day Today, which was a BBC comedy show that just turned 30 years old this year. Mike: And a lot of these shows, the joke is the kind of bombastic self-important reportage if you like. And that happens on our show through different archetypes that one might emulate in 1980s BBC science presenter and the other with a kind of hard-hitting investigative journalist and another with a kind of self-satisfied middle-aged sports presenter. And together that gives the show a kind of ensemble sketch comedy vibe, which was really sort of what I was going for and influenced, I think, a lot by these kind of news parodies. I say the shows I mentioned previously, but what if they were actually a real show and had to sustain their length and had to really go out every day like the news does? Larry: And the setup of it is, like you just said, it sort of has these conventions around it. And if you just listened to it and weren't really paying attention, to the extent you were paying attention, you'd get that it's a parody site. But just the tone, the flow, the structure, everything about it evokes that. How did that come together? Because we were talking before we went on just a little bit about, you said, nowadays if you can imagine it, you can do it with AI. Talk me through the steps from that, imagining it and the first episode. Mike: Well, sure. I mean, like many men of a certain age, I started to fancy having a podcast. I even bought this big stupid microphone, but never really got around to doing, kind of put that away. And then I was getting into AI, which was my latest all-consuming hobby. And through that I found a now abandoned project, sadly called Crowdcast. It was a GitHub piping script where it would take a feed of Reddit posts and turned them into some chatty podcast segments and then send them to the Eleven Labs API to turn it into kind of text. I go, "Oh, this is kind of interesting," this sort of scratches is that podcast itch, but with the added bonus of not actually having to talk to anyone or do anything. Mike: So I started to kind of play around with it now. I mean, six months ago, six, seven months ago when this started, I was in no way any kind of developer. I couldn't make head or tail of Python and what have you. But about the same time or GPT-4 came out and ChatGPT was running the kind of full-fat GPT-4. And it was fantastic as a coding co-pilot to be able to make sense of these scripts that I found and didn't really understand and get them running. And whenever I have an error message, I could paste that into ChatGPT and it would debug the error. And then through a lot of baby steps and trial and error, I managed to get a prototype together, and that's a prototype, it was called Relationships on Reddit. And don't look for it, it's not there anymore, because it's kind of an embarrassing now. Mike: But basically I cloned a voice, a celebrity voice, Stephen Fry, and I was pulling in real actual live Reddit posts from a subreddit, and then it would generate a sort of Agony Aunt segment, Agony Aunt show about these problems in the Stephen Fry. And I ran that for about three days and I'd listened to it in the morning and try and figure out, am I even interested in this? Is this content sort of worth hearing? And it was on day three that I realized that there was a bug in my code that was stopping the Reddit events from passing through to the LLM. And so it was happily making up its own stories that unbeknownst to me, and that was a really kind of strange feeling that a bug in code rather than just crashing the script, crashing the computer, would fail in less noticeable ways. Mike: So it also sort of brought me to my senses a bit, and I realized that deep faking a celebrity voice, offering artificial advice to real people's problems was not okay at all. But it did, I don't know, it gave me that aha moment that you could basically turn code into a piece of media with no intervention, recording steps, no editing steps or anything really. End-to-end, you could run a script or a set of scripts that would take information from some external data feed and at the other end spit out an MP3 of a radio show. I mean, what a time to be alive. Larry: You make that sound very simple and it probably is quite doable and easy nowadays, like you said with ChatGPT. Can you just walk me through your tech stack of that? How deep down are you training the model with these Python scripts? Or is this for prompt generation? Mike: Sure. Well,