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Artificial Intelligence: A Double-Edged Sword for Journalism
Artificial Intelligence (AI) has been making deep inroads into a variety of domains, and journalism is no exception. While many fear the advent of AI spells doom for journalists, an increasing number are viewing it as a catalyst for positive change in the journalism landscape.
Painful but Necessary Transformation
1. Upskilling is Imperative
“By the time I do an AI training for a newsroom,” Pachal explains, “it’s not about ‘look what AI can do’—it’s about ‘here’s how you can integrate it into your workflow so you don’t fall behind the person sitting next to you.’” Journalists who ignore AI do so at their peril. Simple tasks like generating transcripts from interviews, scraping press releases, or obtaining high-level summaries can be streamlined, freeing up hours for more in-depth investigations. Those who learn to harness AI effectively will stand out.
2. Producing Real Journalism
If quick rewrites are taken over by AI, what’s left for human reporters? The good news is that hard, original reporting remains a bulwark against AI-driven commoditization. Neither ChatGPT nor Bard can track down a reluctant source, cultivate relationships, or sense the emotional undercurrents of a local community. Machines excel at data processing, but humans are unmatched in insight and investigation. In the emerging environment, Pachal sees renewed demand for stories that involve new revelations, unique perspectives, or information that is “definitive”—what used to be considered the hallmark of quality journalism.
3. Changing Incentive Structures
In the “search and social” era, many media outlets found themselves chasing viral headlines or “clickbait”—content designed purely to capture audience attention on Facebook or Google. If AI-powered summarization becomes the main conduit to news consumption, the question arises: How do you monetize? Are page views still the gold standard, or do publications shift to subscription models and direct audience engagement? Media leaders may also demand licensing deals from AI platforms that summarize their content. If the distribution is happening via AI chat interfaces, media companies will want a share of the revenue for providing the raw material.
Monetization and the Licensing Conundrum
1. A New Licensing Economy?
As Jordan Wilson points out, major outlets like The New York Times have initiated legal action against AI companies. The crux of these lawsuits often involves unauthorized scraping or “copying” of protected content to train AI models. Initially, these cases focused on plagiarism-like concerns—entire paragraphs reproduced by ChatGPT. Over time, however, the issue has morphed into a question of summarization for search-like features. The emerging consensus: Summaries that replace direct visits to publishers’ sites may need to be licensed.
2. The Role of Marketplaces
In response, new startups are creating platforms to broker deals between smaller publishers and AI companies. Rather than every media outlet negotiating its own contract, a marketplace could centralize content licensing. Smaller publishers might band together, offering specialized niches (e.g., finance, health, local news) at a set price. Pachal sees potential here but underscores how early these initiatives remain. “It’s a dream for smaller publishers to unify and sell their content for summarization, but it’s going to take time to figure out the right marketplace model,” he cautions.
3. User Experience Matters
Outside the licensing battlefield, publishers also wrestle with the “ads vs. paywall” decision. Today’s internet can be a chaotic mess of pop-ups and intrusive ads because everyone is scrambling for diminishing click-based revenue. AI bypasses those annoyances by delivering direct answers. If the user’s interface is an AI chatbot or voice assistant, pages overloaded with ads lose relevance. This shift could give rise to leaner, subscription-focused models and greater adoption of micropayment systems—anything that meets readers’ need for simple, direct content free of excessive ad clutter.
Silver Linings and New Possibilities
1. Enhancing Journalistic Rigor
Generative AI can do more than replicate basic writing tasks. It can process vast data sets, find patterns, and hand journalists fresh leads for stories. Imagine a local investigative reporter quickly analyzing hundreds of public records, with AI surfacing outliers or anomalies worth further human exploration. In this sense, AI becomes less a “job taker” and more an “intelligent assistant,” freeing humans to apply their critical thinking and creativity in deeper ways.
2. Reprofessionalizing the Field
A surprising upside to AI is the possible reduction of low-value content that once plagued digital media. If shallow “hot takes” and tweet compilations are easily automated, large language models can handle that content. The journalists who remain are therefore incentivized to produce work AI cannot replicate: reported features, interviews, context-driven analysis, and community-specific coverage. Readers burned by shallow clickbait might discover a renaissance in higher-quality news, curated and personalized in a thoughtful way by AI systems that reward thoroughness and credibility.
3. Innovating New Business Models
Will there be a standard approach to licensing and summarizing content? Or might newsrooms develop interactive story formats, mixing short video, audio bites, and interactive charts that AI can’t replicate seamlessly? Forward-thinking companies might even create branded AI experiences—like voice assistants specifically tailored to a local city’s politics or sports. Such experiments could lead to novel forms of reader engagement, loyalty, and ultimately monetization.
The Road Ahead for AI and Journalism
Despite the ongoing turmoil—acquisitions, layoffs, lawsuits, and endless new AI features—there are reasons to stay hopeful for the future of journalism. The pain is real, especially for those whose roles revolve around easily automated tasks. Yet the need for human-driven reporting, storytelling, and moral discernment remains.
Jordan Wilson’s parting message is clear: “We’re not robots. Journalists have empathy and a nose for news that machines can’t match.” If reporters, editors, and media organizations embrace AI in a way that uplifts serious journalism and filters out low-value content, they could experience a renewal of the journalistic mission—holding power accountable, documenting community stories, and distributing essential information.
Ultimately, the media’s survival depends on more than algorithmic hacks for the next wave of technology. It rests on good storytelling, solid reporting, and creative adaptation to whatever technical storms blow through. With AI as a partner rather than a threat, journalism can both endure and evolve, delivering the kind of value that keeps audiences informed in a confusing world. The challenge now is to seize that opportunity by recalibrating priorities, business models, and job definitions in a way that ensures humanity stays at the heart of the story.
Topics Covered in This Episode
1. Journalism's Perceptions of AI
2. Evolution of Media and Its Challenges
3. Benefits of AI for Journalism
4. Monetization and Legal Implications
5. Journalists' Pain Points with AI
Podcast Transcript
Jordan Wilson [00:00:17]:
I'm not a robot. I don't know why. Sometimes a lot of people, accuse me of being AI and say, oh, you're a robot. I'm not. Right? I'm a real boy. And and when I was a real boy, like, quite literally, I I was a teenager, I was a journalist. I spent, about the first seven or so years of my career in journalism. And now as someone that literally talks about and covers AI every single day, I'm always torn.
Jordan Wilson [00:00:47]:
Right? Because I feel, for the journalism industry and a lot of the ups and downs that I think artificial intelligence in large language models puts the journalism industry and journalists through. But there's also probably some huge bright sides. So I'm excited to tap into one of my old, professions and to bring on a real professional to help guide us all through it. And we're gonna talk today about how AI is painful for journalists, but maybe good for journalism. Alright. I hope you're excited for this one. I am. And if you're new here, welcome.
Jordan Wilson [00:01:24]:
This is Everyday AI. So this is your daily livestream podcast and free daily newsletter helping everyday people make sense of the mess of AI. Right? It moves so quickly. What does it mean? How does it impact us all? That's what we do here. So welcome. This is your home, and your second home is, well, youreverydayAI.com. While you're there, you can go sign up for our free daily newsletter. We're gonna be recapping today's conversation and a whole lot more.
Jordan Wilson [00:01:50]:
We always keep up to date with the latest AI news, tips, tutorials, all that good stuff, but we're gonna be recapping today's show. And while you're on our website, there's more than 400 episodes. You can go listen to them all for free, watch them all, read about them, all on our website, sorted by category. No matter what you care about, it is there. It's like a free AI university. Alright. And if you are tuning in, we normally go over the AI news. Technically, this is prerecorded one, debuting it live.
Jordan Wilson [00:02:17]:
So, make sure to go check out the newsletter for that info. Alright. Enough chitchat from me. Let's bring on the real experts, shall we? So, hey, live stream audience, I'll I'll still be in the comments. So, you know, leave leave us questions. I'm sure me and our our guest today will go through and answer them. So, happy to have on the show and help me welcome. There we have him, Pete Paschal, the, founder of, the media copilot.
Jordan Wilson [00:02:43]:
So thank you so much, Pete, for joining the show.
Pete Pachal [00:02:45]:
Hey, Jordan. Thank you. Pleasure to be here.
Jordan Wilson [00:02:48]:
Alright. I'm excited for this one. Get to bring my old world, but tell everyone about your current world. What do you do, at the Media Copilot?
Pete Pachal [00:02:55]:
Cool. Yeah. Well, the Media Copilot, I founded it about a year and a bit ago, and, it started out as a newsletter. I challenged myself to learn everything I could about how AI is changing media and journalism and pass on that knowledge to my readers. And soon after that, some folks started reaching out to me and said, hey. Can you come by to my team and, like, explain this AI stuff? And I was like, I could do that. And so I did that once or twice, and that turned out to be really, a really good experience. And that's why I sort of launched formally, AI training in, 2024, and I've been teaching journalists, PR teams, creative teams, some people far afield of that even, about how to use AI in their work and, do a little consulting on top of that.
Pete Pachal [00:03:41]:
So, yeah, it's been good times.
Jordan Wilson [00:03:43]:
Love it. So, you know, walk walk me through some of the, some of your early trainings maybe. So you walk into a a room full of journalists who, you know, if if if you're not from the journalism industry, the whole job loss thing has been around for many decades. Right? Like, when I started in February what year was it? 02/2002 or something like that, everyone was scared of the Internet and, you know, it's gonna take away jobs, and it did, I think, in the advent of the Internet and the availability of information. But, Pete, walk us through. When you walk into these newsrooms needing to teach AI to a bunch of journalists, what what are their questions? Are they excited? Are they scared to death? What's it like?
Pete Pachal [00:04:19]:
So I'll say this. About a year ago, it was much easier to blow people's minds. You know, you could walk into a class and show sort of some basic prompting with ChatGPT and a little bit of advanced stuff with how it could manipulate data and things like that, and everyone would walk out with you know, I'd see the light bulbs going off, and they would just be like, oh, I really wanna apply this and do that. That over the past year has has definitely waned. People are like, okay. I get it. You know? This thing can create content out of whole cloth. I could create videos, images, text.
Pete Pachal [00:04:49]:
I've actually prompted a bit. You know? Show me something better. So I've had to gradually raise my game, throughout the throughout 2024 and, you know, had to essentially, really upgrade things with advanced techniques on, you know, using the AI for PR and media monitoring, in in a newsroom. It tends to be partly about the journalists, but also about the operations. You know, how do you get this stuff in applied in a systemic way, particularly if you don't have a ton of money to invest in, like, a new CMS. Right? Because no one wants to, like, migrate and that sort of thing. And that sometimes involves showing some more advanced stuff. There's a lot of, like, no code platforms, for example.
Pete Pachal [00:05:33]:
So if you wanna go beyond just copying and pasting from a chatbot, it's actually relatively easy to design your own automations to connect with the the chat experience or the AI experience. Right? So that, you can basically have a trigger like an RSS feed, for example, and then the content goes to the LLM and comes back to you in some form, and you can do that for multiple workflows. So that's that's kind of where things have gone from, like, okay. It's cool that we can do content. Awesome. And to, like, oh, like, how do I do that to actually save time and, you know, redirect the way I work? And that's been probably the biggest shift.
Jordan Wilson [00:06:11]:
So, you know, could could you maybe walk us through more from so, you know, you kind of just, explained some of the thought process and the working relationship, you know, between you and people you're trying to teach. How would you say the industry in general, and I know this is a hard, right, to to speak for an entire industry, but how would you say the journalism industry, in their perception of AI has changed even in the last year?
Pete Pachal [00:06:39]:
Yeah. Really good question. So I would definitely say that there's a lot of inherent skepticism about AI from journalists, probably more so than a lot of other professions. While everyone's excited to unlock sort of the the efficiencies and, you know, everything from the low hanging fruit to advanced stuff, there's sort of an existential quality to journalists and and writers broadly. Right? Because it's, well, this this AI can now essentially do at least a simulation of my job, like the the writing and the editing. And, you know, there's a there's an uncanny valley aspect to it, certainly, but it's it's like, oh, I don't know if I like this. And I think that's you know, while simultaneously having your mind blown, it's kind of seeing sort of your job replicated in this robot way is very unsettling. So I think that still exists to a large extent.
Pete Pachal [00:07:31]:
I think it's waned a bit as the reality of AI set in. I think, you know, there was a lot of talk, and there still is, to some extent, some skepticism about whether this is a bubble. Right? Well, it it might be in some business senses, but like the Internet, which, yes, was a bubble, but also was a super long term important trend. I think even even if the bubble bursts on AI, AI is not going anywhere, and there's a reality that it's it's just gonna change the world, journalism, included and perhaps especially. So, unfortunately, AI is coming at a time when media is challenged for other reasons. There's a sort of natural cycle to add, ad markets, and we were definitely on the downside of one of those for a while. But, also, just in the the the larger time scale of the media itself, Like, the twenty tens were filled with a lot of what I call scale media. Right? So so search and social rose up as these amazing refers.
Pete Pachal [00:08:30]:
Like, Facebook traffic was off the hook for so many publishers for so many years,
Jordan Wilson [00:08:35]:
and
Pete Pachal [00:08:35]:
searches, you know, grew into something that everyone sort of depended on and still is to a large extent. But that wasn't really that great for journalism. You know? There was a lot of, like, not great stuff written. And, you know, they're I used to work at Mashable for a long time, and one of the more popular go to formats for quick hits and, by the way, the whole idea of quick hits is a symptom of this era. Mhmm. It it but one of them was, like, a go to format of, let's do let's see what people on Twitter are saying about this thing in pop culture or in business or in tech or whatever. And you just get a bunch of tweets and compile them and call it journalism. And it's like, I'm sorry.
Pete Pachal [00:09:16]:
I hate to break it to everyone, including myself. I've been guilty of writing those things. That wasn't journalism. That was not great. A robot can do that just as well now, and a robot might as well do that. So, you know, like, so so there's there's a certain weeding out of content and maybe people who who were doing that content. But at the same time, there's a broader, like, let's get leaner kind of ethos. And this is, again, this is not restricted to media and journalism, but because it's coming at a time when I think people were expecting a pendulum swing back to, like, oh, the ad market's better now, and maybe people start hiring again.
Pete Pachal [00:09:56]:
Instead, most companies are like, wait a second. Let's maybe not start hiring again, and let's just make sure we're using AI, to the utmost before we get a bunch of heads that we might have to, say goodbye to in a few years when when things swing back again. So, that's kind of like the the in a nutshell, what I see as the the pain in the journalism industry. But what remains so, like, I, you know, I still think and I'm optimistic about journalism itself in the AI era because because we're starting to throw out those incentives of search and social, which, like, as I just sort of explained, we're probably not that good. These dopamine spikes you get from traffic spikes, not good even though, again, they still exist to some extent. But AI now adds this ingredient of summarization. And so there's these disintermediary sort of interfaces. So ChatGPT is one of them.
Pete Pachal [00:10:58]:
Perplexity is one of them. You know, there's there's honestly like, even news organizations themselves are starting to put bullets at the top of their stories that are generated, by by AI. And, you know, Amazon's gonna start having Alexa summarize the news for you, etcetera. Like, you know, there's this layer of summary. This is how a lot of people are gonna start getting information, which means that you're gonna have to start optimizing for that experience. So what is that experience looking for? Kinda, you know, is what the question is. And, honestly, like, I'm gonna, you know, lay my cards in the table. I don't have pocket aces.
Pete Pachal [00:11:33]:
Like, I don't know either. All I see is patterns from what I see these things doing and what people in the industry tell me, and their impressions of it. This is being studied, by the way, obviously. Like, SEO for chatbots will be a thing even with its different incentives. But so far, I can see AI, again, assuming it's, designed well, which is a big caveat. You know? It's gonna prioritize, thoughtfulness. It's gonna prioritize stuff being comprehensive, stuff being unique, and stuff being what I sorta this is my term, really, but it's, like, definitive. Like, something that if you left it out of the summary, you would be wrong to do that.
Pete Pachal [00:12:16]:
Right? So that's kind of the content people are gonna wanna produce. And I would say that's what we used to call good journalism. Yeah. You know?
Jordan Wilson [00:12:24]:
And so one thing my mind always goes to is the monetization of this all. Right? Like, it's it's it's always been in any, you know, especially I came from newspapers. I'm sure it's different, you know, depending on, if if you're at a online publication or, you you know, media, broadcast media, whatever. Right? But everyone's always worried about, right, the clicks, You know? Especially in the early days of online ads, it was the clicks. You know? You talked about your experience in Mashable. It's the clicks. It's the time on-site because that brings in ad revenue, right, which pays said journalists. What happens next? Because what I'm seeing and what I've been saying for a while is it seems like the Internet's getting, harder to use because publishers and big content companies are losing clicks.
Jordan Wilson [00:13:16]:
So they gotta double down on their, you know, on their display ads, and it gets hard to read that news story. Right? Like, I'm taking screenshots, Pete. I I kid you not on big, big websites, and I'm like, the entire screen is ads. And I I, like, I can't even see the story anymore. Right? So what what happens? Because these media companies need to keep feeding the beast. Right? The the the big tech companies, big AI companies that are essentially just scraping copyrighted information, putting it in a bowl of spaghetti, spinning it around, and saying, oh, it's it's an Italian dish now. It's something else. Right? How's this thing gonna keep going?
Pete Pachal [00:13:50]:
Yeah. Wow. You're really stoking a lot of, like, directions I wanna go in, but, like, focusing just on the monetization. Way to, like, kick at the bad knee of the media that has been Yeah.
Jordan Wilson [00:14:02]:
Hey. I have to call a spade a spade here. I I I have
Pete Pachal [00:14:04]:
You're right.
Jordan Wilson [00:14:05]:
I have. I'm I'm cheering for both teams, though, Pete. I am.
Pete Pachal [00:14:08]:
No. That's totally right, and this is really important to talk about. Yeah. They're like, a lot of the phenomenon you're describing is, encapsulated in, you know, this is this mega viral post from, I think it's about a year ago now. The, Corey Doctorow's in shitification of the Internet, and I hope I I'm not sure if I could say that you have to bleep that out maybe for the long term. But, it's totally right because all of these incentives around content, which I'm gonna be clear and point the finger, like, Google created, essentially. Not solely Google, but it is the biggest player in this in terms of doing things like forcing, recipes to have a whole bunch of text that is kinda meaningless and then Yep. Then that jump to recipe, thing.
Pete Pachal [00:14:56]:
You know, for a long time, I remember we used to play the game, this was more than ten years ago now, of galleries. You would just click through galleries to create more ad impressions. People eventually got wise to that and learned it was a trick. But, the overall sort of CPM Internet is still exists to a large extent. So the quick the big question is, like, what does AI do to this? Right? And so far again, let's be clear. It's early days for AI and and the monetization systems. Google has only just recently, in the last couple of months, started putting ads in their AI overviews, their summaries. And, that and that's probably just the first move.
Pete Pachal [00:15:37]:
Right? Like, because that's just like an ad strip that they put everywhere. And the the idea of having placement within the summary in a different way in the same way that, they do for search results. Right? All the sponsored links, something like that is probably coming. That said, they gotta tread a lot more carefully because you have these cleaner interfaces over at, ChatGPT and Perplexity. That said, you know, ads are coming to that. They already have. Like, Perplexity's finally done its ad platform. Sam Alton speaking openly about ads being an ultimate model, but they're well funded right now.
Pete Pachal [00:16:10]:
So they can sort of keep things clean and, sort of bring users in. So, hopefully, that could be preserved to some extent. But if it does stay preserved, then it's like, well, how do you monetize? So far, the, the the answer seems to be, at least from the publishing side, licensing. Mhmm. So you're not getting clicks anymore because now you're getting summarized. You're getting substituted by this AI summary on some platform somewhere. That platform is going to have to pay you some amount for the privilege of doing that. Now right now, that is a big legal gray area, because for the longest time, these big datasets that Google was using to crawl the web and others were using for research, you know, it was basically fair use.
Pete Pachal [00:16:58]:
It was like we're indexing your site. Therefore, you're gonna get traffic, and this is a grand bargain. Well, now that bargain has been severed, very much on one side, and it's kinda like, well, wait a minute. Now we don't want you using that content. In fact, it's funny. There was a this is reported in Wired. Common crawl, one of these big datasets, had not had anyone really, like, ask for their data to be removed from their dataset until the last couple of years, until everyone suddenly woke up and was like, oh, AI is doing this, and they're not giving me anything in return. You know? So there's obviously been all these lawsuits.
Pete Pachal [00:17:38]:
You know, The New York Times is suing OpenAI, News Corp suing perplexity. And, you you know, the, the I the idea at the when The New York Times sued OpenAI was mostly about training data. And these search engines were you know, perplexally, it was still pretty nascent and touch d p t. While it could access the web, it was very clumsy, and it wasn't really a search engine. Well, that's a different world now. And now I think AI for a lot of people today as opposed to a year ago is now more about doing something with data or, you know, in search results or or or data as opposed to just like, I want something from your knowledge base, from your training data, and give it to me hallucinations and all. So, because of that evolution, that lawsuit looks a little obsolete now. Mhmm.
Pete Pachal [00:18:26]:
You know, that that old one because it was more about, the training data and outright plagiarism, of OpenAI. But the point is, the consensus of the industry with all these media companies signing deals with OpenAI and others, is pointing towards the use of, AI to summarize media content, is becoming much more akin to syndication than it is about fair use or aggregation. You know? And maybe we'll get a ruling on this. Maybe we won't. We'll see. I think some of these court cases might be settled. I used to think the New York Times case wouldn't be settled. I thought they would be on principle, and they'd go right to the end.
Pete Pachal [00:19:16]:
But because of that I just mentioned, that it really folks like, if you look at that filing they did, it focuses so much on people bypassing the paywall of The New York Times with this duplicate of content. That's just not a use case anymore. It never really was, but it was like they've kind of weeded out the plagiarism thing mostly from these engines. I I just never hear about it anymore. So I feel like unless they radically change their argument and there are other arguments in the lawsuit. It's just they focus a lot on, like, oh, this article was completely copied. But unless they do it, I I I think they'll probably some kind of settlement, which is too bad because I do I do think there should be some kind of ruling. Yeah.
Pete Pachal [00:19:55]:
And the simplest one would be to say, like, okay. Training your AI on publicly available data is okay. Like, that's fair use. But using AI on someone's data in a in a sort of essentially a rag way or, like, summarizing news way, that requires a business deal, and that's not okay. So I think I think that's the simplest way to break it down, if I were, you know, if I were a a judge trying to speak to the future and not overcomplicate things.
Jordan Wilson [00:20:28]:
So, you know, it's interesting. I'm glad you brought up the the New York Times versus OpenAI case. I'm gonna try not to go on a random rant because I did, like, an hour long podcast on that, when it first came out. What was that? December 2023, I think it was. But, you know, even before that, at the time, I said this is early twenty twenty three. I said, big big media corporations, big big news organizations, they're either going to have to sign into partnerships within, you know, OpenAI, Google, whatever. They're either gonna sue them. So you either partner with them, sue them, or you maybe just go out of business.
Jordan Wilson [00:21:06]:
Is that too harsh or could that be a reality for journalism of the future? You choose one of the two paths. If not, good luck to you. Are you still running in circles trying to figure out how to actually grow your business with AI? Maybe your company has been tinkering with large language models for a year or more, but can't really get traction to find ROI on Jenna AI. Hey, this is Jordan Wilson, host of this very podcast. Companies like Adobe, Microsoft, and NVIDIA have partnered with us because they trust our expertise in educating the masses around generative AI to get ahead. And some of the most innovative companies in the country hire us to help with their AI strategy and to train hundreds of their employees on how to use GenAI. So whether you're looking for ChatGPT training for thousands or just need help building your front end AI strategy, you can partner with us too, just like some of the biggest companies in the world do. Go to your everydayai.com/partner to get in contact with our team, or you can just click on the partner section of our website.
Jordan Wilson [00:22:12]:
We'll help you stop running in those AI circles and help get your team ahead and build a straight path to ROI on GenAI.
Pete Pachal [00:22:24]:
Yeah. I hope not. I do think there's some some hope, in that AI isn't the be all and end all on on all information. I do I do think even in using AI search, as useful as it is, and I I talk to ChatGPT all the time now on my iPhone, I still want that page of blue legs. Sometimes, not all the time. But I'm also a power user of the Internet, and I sort of have a rhythm of, like, you know, the processing that an AI often does on a search to give you the answer, I can actually do in my head a little quicker by looking at that page. You know what I mean? And I kinda want those links because sometimes the correct link doesn't always come up first as quickly when you do a search, but that's me. But I I think for the media and and audience broadly, it's it's a matter of, like, if you wanna be in an AI search, right, like I sort of was articulating that earlier, I would say the question to answer you is, like, why would you want to in the first place? Mhmm.
Pete Pachal [00:23:28]:
And if you have either a a a a plan to get licensing, around that, idea basically, is there an ROI for you on being in that search? Then great. Do it. And if not, maybe not. But then you really have to think about what's your growth strategy, what's your audience strategy, which is important anyway because AI is the only thing. But it's it's a it's just a matter of, like, are those vectors, those other vectors gonna perform for you? You know, that's a that's a tough call on on a lot of, media companies, but I think it comes down to how differentiated is your content, how in demand is it, how can you, how much can you force the AI companies to come to you? Now if you're you know, currently, they're not interested in smaller publishers. There are a whole bunch of startups that are trying to solve this problem by creating marketplaces so that the smaller publisher will go to the marketplace, put their content up there for a price. And then on the other side, a AI engine, like, perplexity could go as, like, I want, I don't know, crypto content. And so there's, oh, we have a dozen people publishers putting it on here, and and you can maybe pick and choose depending on the price you wanna set.
Pete Pachal [00:24:45]:
That's the I that's the dream. That's a scalable thing that, everyone can sort of, sort of probably get behind if it works. But at the same time, you know, it's it's, it's very early days, and there's so many of these things now. There's, like, about about a half dozen of them, at least. One of them, I think, Tollbit, is sort of starting to come out ahead because they have some real some deals with real publishers, and they've gotten some decent funding. Mhmm. But we'll see. There's there's a bunch of them out there that are trying to do this thing.
Jordan Wilson [00:25:15]:
Yeah. I like I like that future. Right? Like, the the the Uber for, you know, personalized media publishing or personalized media consumption. I love it. So so so far, we've gone in-depth on a lot of things, and there's so many things that I haven't covered that I wanna talk to you about. So without turning this into a accidental, you know, Lex Fridman three hour podcast, I'm gonna see if we can go kinda quick bullet point here. So let's let's see. So, Pete, I'm gonna ask you a couple of questions, and let's just go kinda rapid fire.
Jordan Wilson [00:25:43]:
Right?
Pete Pachal [00:25:43]:
Speed round. Love it.
Jordan Wilson [00:25:44]:
Let's see. Let's see. Let's end up with a speed round. So, when we talk about AI's impact on journalists, right, we said there's pain. What are those biggest pain points? Give me that that bullet point top of the page. What are the biggest pain points for journalists when it comes to AI?
Pete Pachal [00:26:02]:
I would say it's basically, you you need to, one, upskill yourself, you know, because there's there's the person in the desk next to you who's going to be the AI qualified person who's actually using it for research to get reports emailed to them first thing, to scrape sites, and to do a lot of summarization for their story building, that you might not have. So, you know, you kind of need to embrace it just to kind of, like, keep pace. Mhmm. And like I said, if you are in one of those positions, probably a junior role, where you might be doing sort of content where you're not really adding much. You're more summarizing something that happened and getting a rote comment from an official. That sounds like a job destined at least 80 to 90% of it for to be done by a robot, and then you're gonna be tasked with just kind of, like, putting stuff around the robot's work. This is a real hard problem because there's a, the pipeline issue with AI of, like, what do the interns do? What do the junior people do when AI can probably do their job a little better? And it's kinda like, well, then how do you get senior people if you don't if you let the robots do their work? Right? So this, in the long term, is a is a real existential problem, not just for media, but I think, essentially, a lot of these jobs are gonna have to be reimagined either a bit or or completely to make sure the human work, mostly in journalism, it's sourcing and putting things together in an insightful way, that that is emphasized throughout from top to bottom, all from interns all the way to the editor in chief.
Jordan Wilson [00:27:44]:
Alright. And then on the flip side, give me the bullet point summarization. Why can AI or how can AI be good for journalism?
Pete Pachal [00:27:53]:
The bullet point summarization of that is that AI will the the essentially change the incentive. So it's it's again, the the other side of the coin I was just talking about, which is that okay. So we're we're prizing unique content, insights, the original sourcing, the new information. Well, if AI if an AI mediated ecosystem rewards that, you've gotta do that as a journalist. And like I say, that's what good journalism is. Go out there and call people. Go out there and make sure you're getting, stuff that hasn't been reported before, stuff that someone doesn't want published. Someone told me that was a great definition for journalism.
Pete Pachal [00:28:32]:
I I completely agree. And, you know, did you basically bring that hard work? This is hard. This is the hard work of journalism. Right? Again, this is why I'm very critical of the search social era. It was so easy just to do a hot take on something and post it on some network and get watch all the, Facebook traffic roll in, especially if you gave it a provocative headline that was sure to debate someone. Right? Now I I I again, assuming the AI is designed properly and doesn't reward that that bad stuff and rewards the the good information, that's what you're gonna have to produce. And it's, you know, it's harder, but it's a good hard. You know? Choose your hard is sometimes is a sort of a viral thing in in social media.
Pete Pachal [00:29:17]:
It's hard to build a career on, just social junk because it's a house of cards, but it's also hard to do a real journalism. I would choose that hard because you're gonna have a much more solid foundation.
Jordan Wilson [00:29:32]:
Yeah. Great takeaways. Love that we were able to look at both sides of the coin, today, Pete, on a topic that's very near and dear to my heart. So thank you so much for taking time out of your day to join us on the Everyday AI Show. We really appreciate it.
Pete Pachal [00:29:47]:
Oh, it's my pleasure, Jordan. Thanks so much for the stimulating conversation.
Jordan Wilson [00:29:50]:
Alright. And, hey, that was a lot, y'all. Maybe maybe you missed some of those golden nuggets that Pete was dropping on our virtual heads. Don't worry. We're gonna be me, a human, recapping it all. I'm gonna put these fat fingers on the keyboard. Type this up in our newsletter as well as everything else that you need to not just keep up with everything happening in the world of AI, but how you can get ahead and be that smartest person in your company when it comes to AI. So thank you for tuning in.
Jordan Wilson [00:30:15]:
Make sure you go check that newsletter out at youreverydayai.com. If you're listening on the podcast, thank you as always. Make sure to please, subscribe to the show. Tell your friends, don't just keep this as your secret cheat code. That's rude. Don't be a jerk. Share it with others. Thank you for tuning in.
Jordan Wilson [00:30:28]:
Hope to see you back tomorrow and every day for more everyday AI. Thanks, y'all.