We Are (Not) The Robots

Welcome to Covering the Spread magazine design for the next age, a monthly discussion of all things related to our favorite medium, magazines. Whether you're a seasoned designer, an aspiring creative, an editor or publisher, or just someone who appreciates the art of storytelling through visuals, this is the place for you. I'm your host, Luanne Welgoss from LTT Creative, a graphic design firm located in Frederick, Maryland, and I've been working on publications for 32 years. You can see our work at LTT Creative.com. And I'm Scott Oldham from Cordo Creative, who's been making magazines for 25 years. You can see my work at CordoCreative.com. And on this podcast, we'll chat with industry experts, designers, editors, and production pros to uncover the secrets of all things magazine. It's time to turn the page and what you thought you knew and reimagine the future of publishing. Welcome to season two of Covering the Spread. We have a really special episode today on a subject that we have talked about almost for the entire first year of this podcast AI. And we have two experts with us. We have Derek Newton, who is the founder of Verify My Writing, which he will explain to us in just a moment. And Michelle Jackson, who is the chief strategy officer for Backpocket Agency, which is a content marketing agency, headquartered here in your Chicago, but we find on Michelle in the wilds of Massachusetts. Welcome, Derek and Michelle. Thank you, great to be here. Thanks, Scott. So Derek, let's start with you if we could. Can you just explain to us what the nature of Verify My Writing is, what it does, and why you started it? As we know, the emerges of AI has upended a lot in the space of writing content creation, as well as publishing editing, you know, the entire universe. Not too long after AI came on board AI detection came along. Maybe six months later, the first ones were out. These early models weren't great. There weren't very many of them. They were okay, but they weren't very reliable. But over the course of the past several years, as the AI has gotten better, the AI detection has also gotten much, much better. Now, a handful of technology platforms are really, really accurate at detecting AI text, accurate to the one in 10,000 or in some cases, one in 25,000 success rate. Being a journalist who covered academic and workplace in credential fraud and a writer, I had a special interest in what was happening with the ability to create content that that may not be what it claimed to be, or how this might be used for nefarious purposes and paid very close attention to that. And it occurred to be pretty early on as the detection technology got better. That, in my opinion, it was being used backwards. That most people wanted to use the technology to be police officers, in a sense, to be traffic cops. They wanted it to sit on their dashboard or have access to it, and whatever came across their intersection as a magazine publisher or a research editor, whatever the case may be, they could check it and start issuing speeding tickets or get off the road tickets. And that works. The problem is that people who have these jobs don't want to do that job. They don't want to be police. They don't want to have difficult conversations with people about questioning the credibility of their work. And we found, we found pretty early on, that they weren't going to do it. Even when the tools were provided, there wasn't a whole lot of motivation incentive for people to use the tools that way. So they don't. What Verify My Writing does is we take these top-end detection tools and we use them sort of backwards. Rather than giving them to publishers or editors to use as radar guns to issue tickets, we encourage writers, people who produce the content who are closer to it, to go get their work scanned ahead of time, get a score from us, and let us certify that the writing is human and authentic and not AI created. As a writer, this made sense to me writing as hard and I was proud to have done it. If anybody wanted me to certify that I bang my head on the keyboard for three straight nights before producing this material, I'd be happy to do it. So just seemed to me to be a more elegant solution to a very, very complicated and big problem. And so that's why we started the company. So a buried in there is that we let writers get work certified by us as being human created and not AI, which we think and has proven so far to help editors, publishers, agents, producers of movies, people who want to know this material, but don't necessarily want to be in the position of holding up a radar gun to every piece of material that crosses their desk. Michelle, can you just give us a little background on what Back Pocket does and how if in any way, generative AI has changed your workflow as an agency? Sure thing. So as you mentioned, the Chief Strategy Officer at Back Pocket Agency, we're a content marketing agency out of Chicago. We serve mostly associations, nonprofits, healthcare organizations and other mission driven B2B organizations. So we establish multi-channel content programs for them, whether it be print, magazine, digital, both paid in organic content programs. I think our clients aren't necessarily bringing to us concerns about AI generated content per se, but I think it's more of an education that we're doing for our clients in terms of where AI can fit more effectively, more strategically and identifying some of the risks that come with fully AI generated content. One of the sort of more intangible risks that we see for clients who are establishing content programs for their audiences are you are certainly not differentiating yourself when you're content that you're pushing out to your audiences fully AI generated. What one brand generates through AI is very similar to another brand's content that they're generating. So I think for us, it's an education for clients as to why this human-led content experience is still really important and how you can stand out as a brand by not, you know, farming out your content team to an AI bot. Derek, there's an interesting history about where AI originated. Let's get their content. Can you tell us that story? The large language models on which these machine learning algorithms sit, because that's what they do. They train algorithms to go into a very, very deep billions of words of material and pick the words that make the most sense to the model and put them out in order. And when they were building their large language models, they started with books that were in English. They started with books that were long and they started with books that they didn't have to pay the rights for, where they were in the public domain or the rights had expired. The biggest corpus of those books was English Victorian writing from the 18th century, early 19th century. And there are still fingerprints of that early training in the models if you know how to look for them. They will occasionally default to British spelling of words like neighborhood or they'll occasionally come up with very predictable, you know, 100-year-old British names for male leads and dramas. And then eventually the AI companies and the large language models realized that this, even this entire library of information wasn't big enough to really get the depth that they needed. So they went to other places. They started taking in online content. They started taking in news content. They started taking a more modern books, which has gotten them in trouble. I'm sure you probably saw Anthropic, one of the big AI providers entered into 1.5 billion the B settlement with authors to pay them for having used their material without permission. So these models are constantly ingesting and absorbing more and more text to get better and better and in some ways faster and faster. Where they are pushing the envelope to ingest more material is in understanding how chemists talk to each other. Very niche, very specific, very technical language, people who use slang because they know it in their profession or the sort of thing. They have to get into the subreddits that are online and they have to get into research papers written by optometrists and chemists. We know now that three of the top referral sources in AI, generated AI are Reddit, LinkedIn and YouTube. Although I'm a glass half full, so I would say if your basis is Victorian novels, at least we started from a good foundation. I don't know what we've done to it since, but there's worse things you could start from, I suppose. So AI is pulling some of their information from Reddit. Marketers are losing their minds over Reddit because it's a true community channel and yeah, Redditers will push you out as if you try to market to it or sell to it, but yet brands understand that what's being said on Reddit is fueling some of these LLMs. So. It was open AI that signed a big deal with Reddit to get their content because Reddit was one of these providers that had uncalculable amount of data that people had contributed over decades of being active on the community. They needed this different sort of way of putting communications together in text and they signed one of the earlier big deals to get access to. Yes. It's interesting because the human in the loop is an important element when you're talking about generated content. Does a human fact check it? Does a human review it? And the big, you know, one of the biggest problems with generative AI content is it may not be truthful, it may not be accurate. And Reddit is not established to be accurate. It's a community. It's conversations happening. It's not s that just brings home the point of, we do need humans involved in this content creation and approval process. We do need to make sure we're doing our third party fact checking because otherwise we risk putting out not just AI slot but just factually incorrect, AI slot. - The favorite parlor game online right now is was this generated by AI and looking for all the fingerprints. You mentioned a couple of them, Derek. What do you, Derek and Michelle see in the writing that you experience and are suspicious of? - The LinkedIn community is taking a death to the M-dash. I would say definitively, I have been overusing M-dashes in my writing for 15 years long before AI was a thought in its parents' head. But M-dashes are the top to me spotted AI tell. The other thing I see is those sort of quippy, one word question mark followed by three words to answer your one word question mark. And then the other last one I'll mention is it's this, not that. So those are sort of the three and they all are a little bit overused in marketing content more so than probably long form thought leadership content. - AI models tend to overuse the M-dash and it isn't, I had to learn this. So when I asked a question to one of the AI engineers about this 'cause I didn't really believe it. I thought it was just made up sort of urban legend about M-dashes. And I said, "Dat it, they don't really come on." But he said, "No, AI models use M-dashes that 230 times more often than normal humans do." It isn't a slight tale. It's a salt and pepper dash of M-dashes in writing. One of the things I look for is subheaders, three paragraphs and a subheader, three paragraphs and a subheader, three paragraphs and a subheader, very sort of blocky writing in that way that visually stands out as being constructed like a building or a house. And then inevitably when I see that, the third or fourth graph has four to five bullet points. So to me, it isn't the words that I'm focusing on. It's the structure of the piece. And when I go to check because we have access to these systems, when I see a piece that is that, four to five subheaded paragraphs with one of them having bullet points, probably 75% of the time I'm right, but it is AI generated. - That's interesting that you should say that that's AI generated because a designer would be thrilled to see content structured in that way. Because for the most part, how often do we get content that is just to see of content without subheaders, without bullet points? And we desperately want that. And now I think people might be afraid of that. Which begs the question, why of all the ticks that generative AI could have come up with, why is it things like M-dashes? And it's not this, it's that kind of patterns. Are there any theories? - The theory that I've heard and subscribed to is the first model, the biggest one, open AI, chat GPT, was not trained to write. Its original objective was to converse. It was built and conceived of as a conversational assistant and so its core functioning is to engage with a user in a conversational style. And when you're writing conversationally, that's M-dashes. You know, that's like short responses. This sort of thing, it's quippy. If you were doing academic writing or serious investigative journalism writing, you wouldn't want that. And it can do that as the models get better. It's very capable, but you have to tell it. This is what I want. If you don't give it the parameters, it defaults to a conversational, very casual, friendly, hey, what's going on sort of demeanor. - So for people who are frightened right now, listen to this, who happen to have those ticks in their writing style. What are the odds of a false positive in a system like yours, Derek? - It depends on the length of the document. The people who build the systems are confident their accuracy is very good on anything 150 words or more. I'm a little uncomfortable at 150 words, just personally. I just don't think there's enough material to test. But anytime you get up over 500 words, the accuracy is astounding. So a book, for example, a novel, a lengthy investigative journalism piece that's several thousand words, the accuracy is going to be one in 20,000 of it making a mistake. But it's important also to say that that is a mistake on the document. That would be a mistake on a sentence or a paragraph. So to completely flag an entire document incorrectly, it would have to make that one in 20,000 error, 20 times a row or 50 times a row, depending on how long the piece is. Statistically, that is possible. It can happen, right? People do win powerball. You can put these numbers together in a way that seems impossible and it can happen. But the odds of it happening with a good system are very, very bad. If you were just to go to Google and look up AI detector, 75, 80% of the ones you find on Google are not good systems. They're bad. They're not accurate. They are, in many cases, designed to mislead you. If you write something yourself and you put it into one of these systems you find on Google, it's very likely to come back and tell you it's 80% AI. And you're going to get upset and frustrated and think that AI detection doesn't work. These systems do that on purpose because they want to sell you what's called humanizing a software. Like, oh, you're just 80% AI. It's going to get fly, you're going to get in trouble. For $5, we can humanize it. And you can avoid the AI detection. These are not honest businesses. And they are selling product, not really advancing a complex conversation. And so presumably that humanizing task is handled by an AI. Correct. So it's an AI making your AI writing not sound like AI. We've got rules out. Correcting robots. Yeah, exactly right. And these are a big problem in academic by that. I mean, school, some where students are taking this traditional five paragraph or seven paragraph essay, having AI write it. Then they're taking it to a humanizer and having a humanizer rewrite it. So is to avoid the detection technology that the school will other professor may be using. If you do go and check your work on your own and you happen to fall into a company that sells a humanizer, these example I use is if you own an apartment or a home or whatever and somebody knocks on your door one day. And so I'll give you a free window inspection. I'll check every window for the seal and everything to make sure it's fine. What are they going to find? There's no chance they're going to come back and say your windows are great. They're going to tell you you need to replace every single one of your windows, but they happen to have a sale today. 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We strive for accuracy, but we make no representations or warranties about the completeness or reliability of any information shared. Thanks for tuning in and enjoy this break. So I learned the other day from one of our developers that at least in WordPress, if you're copying and pasting AI-generated text into, let's say, the blog post format, that there is code attached to that text, that you can't see with your eyes, but you can see in the coded version that essentially it's code that says this is AI-generated content. So it gets me to think what the purpose of that is, what it may be used in the future. Are these AI tools going to prioritize or deprioritize websites that have this code attached to the pages? I don't know, Derek, do you see that? And what do you think about that? I wasn't familiar with that specific application, but yes, I think search engines and general, the tools we use to access the internet are going to start sorting for us, or at least marking for us in some large way. I think that's fraught with peril honestly, because I think a lot of people are going to complain very strenuously if they're AI modified or AI edited or human written content winds up on the dark side of Google, right? We've seen this before. Google delists you, you're out of business, and it almost didn't matter why you were delisted. It could have been a mistake. Somebody had a bad day, but getting it reinstated is exceptionally, exceptionally difficult. The AI makers, all of them can, what they call, watermark their text. They can put signals in the text to make it very clearly identifiable at a 100% accuracy. None of the AI makers have done this, although they're capable of doing it. And this goes back to what I was saying a little bit earlier about how impossible it is to label AI material. There's a reason they're not doing it. And it's because they don't want people to be able to tell AI content from human content so easily. It really diminishes their business model of producing AI. But yes, long answer to short question. Yes, I think search engines might value and score AI create a text differently. I know there are some browsers. extensions in development that will agree or dark out content that is AI created when it comes across it on the internet. I think there is going to be a prioritization of that, but I think it's going to be a while yet and I think it's going to be sloppy and make a lot of people angry at least in the short term, even though I would support it, even though philosophically I think that's a good thing because I'm on the disclosure side of the coin. I just think it's going to be very sloppy for a while. It's interesting because when we were growing up, we didn't have AI, so we all had to research the old fashioned way. In a way, we all kind of still did the same thing that they're doing today and hoped to not keep caught. How many times have you copied the exact sentence or paragraph and then maybe rearranged a few words or swapped out a few words and hoped that the teacher wouldn't catch you just so that you could fill up that seven page double spaced book report that you had to write. Now it's not so easy and it's got to be tempting for a lot of people to run it through all these things so they don't get caught. It's a lot easier to get caught than it was, peck. It's sort of like that there are no new problems. They're just slightly rephrased problems. Students had that challenge before. They're having this challenge now. There's probably no such thing as truly new content either. It's been done. We've been creating content for centuries, but yeah, that's an interesting point. It was just a slightly different risk or temptation. That brings up my next question is as we go on and on and on through this, everything is kind of borrowed from something. Nothing is new. I've thought to myself, "Good God, if they did this with graphic designers for it, check to see if it was originally created by you and if anybody else created something." I'd be terrified because we all kind of borrow from somebody in some way, shape, or form. So how do you prove that something is truly yours? The type of content that we create for our clients or that we encourage our clients to allow us to create for them are more firsthand stories. The only thing that is original that's not influenced by something else that's already been done is your personal story. For example, we work with a lot of associations encouraging member stories to be told through the magazine or through their digital platform. I think that's the one area that just can't be AI generated. Your own story is going to be the only thing that's unique, maybe not the only thing, but truly unique. Something that nobody else would know about. Right. It's not already online. But at the same time, it's the type of stories that we as humans want to hear. That's how we're building connection now in this AI-generated world is through these stories that connect us and we see commonalities. I think there are so many reasons to lean into that type of content in 2026. So Derek, how are your clients, the writers who are using your system and company deploying that certification once they achieve it? What are they doing with it? There are two ways that our certifications get used. One is what I call an internal certification. If you have a work that you are passing along to your agent or editor or you're hoping to find an agent or a movie producer and you know they're going to ask, right? Everybody asks, everybody's reading for how much does this feel like AI? So that's a document that can go along with the material and it has data about it when it was scanned. What the score was, obviously, how many words are in it. So it's a little more linked to the underlying document. The other one we have is a more public-forward, it's more like social media badge, frankly, but it has a QR code, so anybody could hit their QR code and it'll go to the certification for that document where they can see all that other information. But it's shorter and that's meant to be in magazines. It's meant to accompany the material when it's published, whether it's a magazine or an academic journal or even a book. We've had several writers put our certifications, the badge one on either the front or back cover of their books. It's just a way of saying, even if you don't care as a writer, I care. And so I took this extra step to demonstrate that I care and that I, to the standard of the art today, I've got a clean bill of health that I can share with you. Michelle, do you think that your clients at some point down the road might ask for you to verify that the content that you're giving to them is, in fact, verified as your own? Michelle, I'll give you a heck of a deal. I'll take it. I'll take it. You know, I think that eventually that will be a reality. I attended a webinar last week. The topic was, are your contracts with your clients setting you up for risk because of how you are or are not incorporating AI in them? So what I mean by this, as an agency, most contracts are going to state that the content at the end of the day is owned by the client, whether it's going into a magazine or going on a digital platform. And if that content is fully AI generated legally, where does that ownership lie? So there, there was an attorney doing the presentation and she noted that there's a whole lot of gray area there and not a ton of precedents at this point. So I can see this is a great tool for agencies to show, hey, you do retain the ownership. You know, it's clear that we created it for you on your behalf, you know, and you have the ownership of it. So I definitely see a future where potentially there's a clearer need and a clearer demand. I have to wonder if websites or magazines that are published might be putting a seal of approval on their website or their publication to assure readers that this is not AI generated content. Several magazines are going to start doing this. I can't name them yet, but I know it's coming in communication now. There's basically two groups. There's information that is like factually driven like what happened news essentially or the weather or stock market, you know, indices. The audience probably doesn't care much at all, whether it's AI generated. The fact is the fact, you know, there should be a human in the loop to make sure it's not made up or that it is misleading in some way. Newsletters are the best example. If you're receiving a newsletter that says what happened in the stock market today, you probably don't care much that is whether it's AI generated care that it arrived on time and that it's accurate. But for the other bucket of content or magazines or newsletters or any content creator that is based on expertise, voice, context, explaining what happened, maybe providing new insights or connecting things. This sort of content, I think, is going to be a lot more sensitive to AI creation because what I'm getting in that newsletter is I want to know this expert's view of what happened in the market today. That's the value I'm seeking to get out of that. But whether it does or not, that's really the place that we're going to focus on AI content creation because what those creators are promising to deliver is different. That gets back to what Michelle said earlier about member experiences as well. So it could be related right back to the association world. You know, within our space, some of our clients too are in a higher trust type of industry. And I think what you're saying, Derek, means even more for them. You know, when we're thinking about healthcare organizations, you know, the perspective of your doctor is, it's important that that's coming from your doctor's perspective. You know, we talk about like stock market updates, but more financial service advisory. You know, that's another high trust space that I really need to know that the person giving me this information is the person giving me this information. So there's a spectrum, I think, that exists even on that other bucket that you're talking about where there's an even greater need for authenticity and accuracy and expert-led human-led content. It's a phrase human in the loop on AI content creation. I think most people accept is good and necessary and beneficial. The challenge from history, however, doesn't lead us in a good place. For a long time, the biggest example was in banking. The machine started calculating mortgage interest rates and whether you've got a mortgage, and they did it with a very complex formula. And in theory, the mortgage lenders were allowed to override the machines. I'd say, no, I disagree. I'm going to go ahead and give the mortgage. The problem is in a lot of studies going for decades, I never happened. The mortgage lender or the banker deferred to what the machine said because they didn't have the confidence to take the risk and override the algorithm. And there are lots of other examples where simply having a human in the loop unless that human is an expert really confident in their decision making and is not going to be fired for overriding the machine, having a human at the desk, we've seen in a lot of context, probably won't be sufficient in this case because we're talking about AI content to rewrite AI content or to flag it and not publish it. That's tough and I'm not necessarily skeptical. I'm just a little worried that in some ways we've seen this before. I think one of the ways we use generative AI, and this is a little less generative and more data interpretation, but we've got a long form piece of content that we've created. Maybe it's a report, maybe it's a multi source interviewed piece and let's say we want to promote it in social and in email, we might create a closed loop custom bot to say, hey, take this content. and give me a few effective subject lines for my email that I'm going to promote this content in. So asking AI to interpret the data, the data, which is the long form piece of content, rather than saying, write me this 2000 word expert led content featuring these five experts and make up some quotes for them, by the way. - Yeah, totally, totally agree. Maybe it's too late, but I want to try to say, I'm not anti AI, right? I'm really not. I call myself AI agnostic. I recognize that there are lots of places, many places, thousands of places where it is value add, where it can take a lot of the work away from people who previously had to do it, where it can open up things we never even thought about before. I have nothing at all against any of that. - How does Grammarly fit into all of this? If I were to be reviewing, say, an article that somebody wrote in Grammarly is assisting me in fixing basic commas and things like that. But it also sometimes wants to change the tone or it wants to rewrite a sentence, or you had a paragraph. How did that play into all this? - I'm hearing that it's giving more and more of those suggestions that are sort of, almost making it sound more AI driven. And so our team is having to sort of reject more suggestions from Grammarly than it did in the past. I just want to know if there's mistakes, if there's misspellings, if there's grammar issues. I just need you to make sure my content is clean. I don't want you to rewrite it. - I mean, even the emails that you write in Google will offer to rewrite them for you. And it's to a point now where if you were to actually have a live conversation with somebody, I wonder if you were as fluent and elegant as you were in your email. That's a good question. It's probably not. - I read a statistic that I personally at least found alarming the other day, which is that they estimate now that better than 50% of the content that comprises the internet is as of today AI generated, which suggests that these learning language models are now feeding on themselves more than they are on human contributors. And what does that mean for generative AI, at least as a textual tool for the future? - We've seen for a while that large language models are starting to ingest their own content. - The smart people who pay attention to these things are worried about this because it could lead to what they call model collapse where the models stop functioning properly or it gets really over indexed on a very specific sort of response because it gets it over and over and over again, and has a hard time breaking out of that. Those things can be adjusted by the programmers who control those large language models and the AI algorithms that run them. The public is starting to come around a general a sort of filter when we see things. That most consumers now ask themselves at some point while they're engaging with that content, whether it's AI or how much confidence do they have in that. And this is, to me, another part of the problem why are I like our approach because you can't label AI content. There's too much of it. Now the people who are producing it don't want it labeled so they're not going to participate in the system to have it labeled. They want it to look like everything else. Even if you could force them into a labeling system, the economics are to contest that system at every turn. There really isn't a good business model or even plausible approach to label AI content at a mass scale. One piece here, a photo there, a video clip there. Yes, we can do that and we should. But to have some sort of system where half the internet has some sort of designation that it's AI created if that was ever possible, that's called. And that's why I continue to believe that there's going to be a second plane, if you will, for content that is created by a human, represents context and understanding and experience and view and voice and that if we can assure people that that's what this second type of content is, it'll have a very prosperous market because I think there's enough people out there who want that, who will respond to it and reward it with their time and whatever their financial contribution is, whether it's seeing ads or subscribing or however they engage. I don't know that the pendulum is all the way in swinging in the other motion, but it's headed that way. I audiences are wanting that human-led content. Again, the storytelling, the first hand experiences, the true thought leadership perspective with an AI-generated world that is informed by generative AI content, that world sounds like way more AI-slok. Like it's the content that you don't connect with that sounds the same in every channel and every brand that's delivering it. I think that's going to push that pendulum a little further in the direction you're talking about, Derek, which is a good thing for all-involved. Do you either think that the medium has a huge impact or an impact at all on whether people are initially suspicious of the origin of the content? Do things that, for example, are printed out have more veracity, just intrinsically, given to them, deserved or not, versus what people find on social media or other online content. The longer it took to put that together, the higher trust you have, you know, the magazine that went through all the designers and the editors and the writers and the publisher, you know, and the printer, there's a lot that goes into that that's human-driven. I think the shorter form, quicker content, like what you see on social. You know, there's a high distrust of LinkedIn content that the LinkedIn community will tell you about. The level of impact that went into that product, whether it was a social post or a print magazine, affects the trust that people inherently have with it. Certainly, I find myself trusting printed content more for that reason, I think, without, without even really thinking about the reason why I'm feeling that way. I think people generally feel like printed is human, just because it always was, whereas the internet has never been really human, so it's just a mind type of thing. - When a company such as Amazon allows people to publish fully AI-generated books on their book platform, without any sort of designation, you really sort of get into a very confusing space. Quickly, is this a book that I think of as printed and therefore has high trust value, or is it a digital piece of content that was made 20 minutes ago? And I can necessarily have that trust content. Well, it's on Amazon, what does that mean to me now? It's on like Kindle, do I trust that? I think in certain places, even that designation isn't as clear as certainly I would like to think. (laughs) - We've found the future of the game. Is there anything more Derek or Michelle from your perspective on what is next and what people should expect? - Very few things are very black and white and yes or no, or good or bad. I think what we try to encourage our clients to do in the agency setting is if long form AI-generated content isn't the answer, what is? Where are more strategic points that we can work in AI that are going to bring that value that are going to make us more efficient while bringing that additional value? So things like data analysis, like I mentioned, taking long form content and using AI to create some more snippet type short form content from that long form content. So identifying within the content workflow, if we're not going to use it for long form generative AI, in that aspect, where can we use it and sort of mapping that out, documenting it so that it's repeatable, because if we just say no AI and we have a strict no AI policy, we are going to fall behind, but we want to do it responsibly, we want to do it strategically, you know, and I think putting a lot of thought into what that looks like is really where organizations can have success and do it in a way that they can be proud of and own as well. - It's building awareness, building, establishing a brand that people know what it is, know what it means, and that they can put trust in it. That's a lot easier said than done, it takes time. So we're on the long build of doing that. You're talking about the future. Magazine publishing isn't my specific area of expertise, but I have seen many people mention, as it relates to magazine publishing specifically, that the most valuable currency going forward is going to be reader trust, establishing long term relationships with your readers, almost at a one-on-one level, but where they know what they're going to get, where they trust it, where they come to rely on it in some fashion. He's going to be maybe the only thing that survives this AI transition. And if that's true, to me doubles down on everything you can do to amplify the uniqueness of your voice, give it credibility, invest in it, right? How you build reader trust is different than how you build subscriptions. - Yeah, yes. Certainly how you build page views or clicks. The market is undergoing shift, the likes of which probably none of us have ever seen. Maybe not since the internet itself came on as a place. I don't know the AI or anyone knows how this is all going to play out yet, but I certainly think it's fascinating. And maybe more of an optimist than some might think. - Like I'm optimistic too, that that's where we're headed. Hopefully marketers are feeling the same way, that trust that builds that long-term connection, whether you're doing it. your magazine publisher or whether you're an association trying to build more lifelong members and reduce your drop off rate. It's the connections and the trust that you feel with that content and that certainly purely AI-generated content isn't going to give that to you. I'm on your camp. I love that and I think that you said it beautifully. Well, thank you. I clearly overshot the mark. [Laughter] All right. So, Michelle, can you tell folks who are curious how to get in touch with you in Backpocket? Yeah. So, the best way to find me is going to be on LinkedIn. So, I'm on LinkedIn at Michelle Bulls Jackson and you can find Backpocket at BackpocketAgency.com. And Derek, how do people get in touch with Verify My Writing? That one's easy as well. VerifyMyRiding.com. Okay. Thank you. Well, thank you both. Fascinating discussion. I feel like we've just touched the surface, but we would love to have you both back and maybe this kind of form or maybe even more people. That'll be the goal from back and through years. How do this? Yeah. None of us will be here. It'll be our robot versions. That's probably right. It's definitely not. This is really fun. Thank you guys. [Music] Marketing is hard, but I'll tell you a little secret. It doesn't have to be. Let me point something out. You're listening to a podcast right now and it's great. You love the host. You seek it out and download it. You listen to it while driving, working out, cooking, even going to the bathroom. Adcasts are a pretty close companion and this is a podcast ad. 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