Mind Readings: The Real Danger to the News Industry Isn’t AI

In today's episode, let's talk about the news and the danger to the news industry that AI might or might not uh cause. A lot of people are talking about how the news industry is on death's store, and AI is going to be the final nail in the coffin to put newspapers and other publications out of business. Maybe, but probably not. What's gonna kill the news industry is the garbage that they publish. I was recently looking for um looking for some some news about one of the the shows that I I follow.

I don't have time to watch television, but I read the summaries. And I got to this one site that had this interesting headline, and I'm just scrolling, scrolling, scrolling. Okay, when do you get to the actual news? You know, the headline said one thing, and then there's like 14 paragraphs of filler, just total fluff, saying nothing, and then finally at the very bottom of the last paragraph is the actual news piece. That's a miserable experience.

Now, why would a news website do that? Well, because to scroll past all 14 paragraphs, if you do that in a normal web browser, one that does not have an ad blocker, there's like an ad every paragraph. So they're just showing you ad after ad after ad as you're trying to scroll through this thing, you know, just being boggled by the the lack of content. I would have loved to say that that was all AI generated, but it wasn't. It was just badly written human content.

I actually did a test with one of the many uh AI detection tools, and they all universally agreed the site's not this, you know, the content here is not AI written. It's it doesn't have the telltale statistical indicators that it's AI generated content, which by the way, uh they do exist. It's a technique called perplexity, and we'll talk about that another time. But holy crap, that article was so long and so drawn out for so little benefit that it was just garbage. It was all filler, no meat.

Now, when I fed that article to OpenAI to GPT 4, I said, summarize this and just give me the main points. And it did. It it went straight to the the main point, cut out a lot of the filler, and that was a a huge time saver. That technique is a huge time saver for like, oh my goodness. You know, just piles of drek.

Machines like that and large language models and AI have the ability to summarize, to distill, to extract, to remove information from whatever soup it's in, and boil it down to just the relevant parts. In fact, in terms of what large language models like, like a chat GPT-based uh model, GPT 4 or Llama or any of these other ones, they're really good at that. They're really good at summarization and extraction. They're actually better at that than they are at generation. They're better at extracting and summarizing than they are at writing net new content, and that's one of the great uses of these tools.

It is fairly trivial to envision software that you would have as an app on your phone or whatever, that goes and reads all these poorly written news sites and just says, here's the the two bullet points from this article that are that are relevant, and the rest you know we've we've ignored because it's all filler, it's all fluff. That's what's gonna kill the news industry. That's gonna what's gonna kill a lot of journalism. It is not machines putting writers out of work, it is machines distilling down the garbage that's being written, and in the process, not driving ad revenue, right? Because a machine that goes and parses that page, it's not a human, right?

It's not it is running a browser, so the publisher might get um some views on those pages if it renders it in a in a contained environment, but they're not gonna get clicks on it ever. The ad performance is gonna drop to zero because a machine's not gonna click on those ads. A machine is instead just going to take the text from the page, boil it down to the one bullet point that is actually the news, and there we have it. So that's a pretty bleak picture if you're a publisher, right? Machines are gonna be reading your content and distilling down just the the bits that people want and leaving the rest behind, and you're not gonna get any clicks.

So you may get ad revenue, but you will not be the advertisers will be like it's this is not paying off. We're advertising, we're spending money, and we're getting no results, we're getting no traffic on these ads. So, what's the solution? Well, there's two solutions. One, um, create less crap.

Uh, and two, the model for how publications do business has got to change. And what it might look like is what is being very successfully done now on in places like Substack, where you have individual writers creating their own feeds of things and then having sponsors, right? Have a I can't tell you the number of newsletters I read now that have a sponsor. And yeah, you read it. And ad blockers don't cut it out, right?

Because it's an email. It's an it's an email, and you just scroll past the ad if you're not if you don't care. But if you do care, the ad's right there, and you can read through it and and enjoy it. I look at my friend Ann Handley's newsletter. She's got ads in it for some of her stuff.

I look at uh some like uh what's that guy Rowan in his uh AI rundown newsletter? I can't remember his last name. Um he's got promotional stuff in his newsletter, all these different newsletters that people are subscribing to now. That trend is taken off because A, it allows writers to talk directly to their audience without the constraints imposed by a publisher, and B, they can make money directly from the audience by charging for subscriptions in some cases, by uh running sponsors, things like that. That's the model for publishing that seems to be working right now.

People who are good content creators are creating their own publications, their own platforms, and in doing so, they are able to derive revenue from it. Think about this for your own business. How much of your stuff is so good that summarizing it by with AI wouldn't really save anyone any time because there's a lot to dig into, there's a lot to understand. Or is your content so thin that uh uh an a large language model could simply take it and extract the one bullet point of actual content you have, discard the rest, and there's no need for a machine, there's no need for human to read your content because a machine can do it better and faster and get to the the tiny crumbs of useful information that are in there. As marketers, we have to get better at creating valuable content.

As publishers, we absolutely need to create better content just to keep people's attention, just to hold on to the audience that we have. So if you're on the publishing side and you're publishing stuff that you know is not delivering that frustrates people, now's the time to reevaluate that. Because your revenue model probably has to change really soon as machines become more and more adept at reading the web, extracting content from the web, and presenting distilled versions of it to users. That's it for this show. Thanks for tuning in.

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