You Ask, I Answer: The Impact of AI on SEO?

In today's episode, Max asks, your opinion on SEO and the impact of AI in the future. So this is a this is a complicated question. And it's a complicated question because organizations like Google have said, hey, we're going to penalize um content that is generated by a machine that doesn't add any value. So uh there are any number of services out there that will use natural language processing and uh essentially take existing content and reprocess it, remix it. Um is really bad, like really, really bad.

Um there's this one bot that scrapes a number of popular blogs, and it attempts to rewrite those blogs, but it finds the most awkward synonyms, and you can tell pretty easily that it's machine generated, right? However, what makes this question complicated is a question of skill. Let's say a human writer goes from you know face rolling on the keyboard to Pulitzer Prize, right? Those are sort of the the spectrum of writing. Machines right now are kind of out here, right?

So here's face rolling on the keyboard, here's you know, um competent, but not great. Um Google Webmasters guidelines actually has a expression for this. Nothing wrong but nothing special. And then of course up here is Pulitzer Prize. The challenge is this for search engines like Google.

It's easy to spot the stuff down here, right? It's easy to spot the stuff that's barely more than face rolling, that is clearly no value add, um, that machines have generated programmatically using, yes, some machine learning and AI, but the output's not great. The output is pretty inept, actually. Um, but every year the bar of what machines can do goes a little bit higher every single uh year. And we're at a point now where machines can create credible mediocre content, right?

That is indistinguishable from human content. When you look at it, it passes the Turing test. You can't tell by reading it, was this generated by a machine or was this just generated by somebody who doesn't like their job? Right? You read this and go, you know, so-and-so is proud to announce another flexible, scalable, fully integrated turnkey solution for blah, blah, blah.

It's the marketing copy that we all see that we all think is not great. And so the challenge for search engines in terms of the arms race of detecting these things, is going to reach a point. Now, this is my opinion, this is my opinion only, but I think it's going to reach a point where computationally, it doesn't make sense to keep trying to identify AI generated content. Can you do it? Yes.

Is it worth the compute cycles to do it? No. Um, not past a certain point. And that certain point is if a machine writes genuinely helpful, useful original content that I, as a human, can't tell the difference. I don't know for sure if a machine wrote it or a human wrote it, then a search engine's gonna have a real hard time determining that as well, particularly at scale.

One of the things that we forget a lot when it comes to machine learning and AI, when it comes to big tech companies like Facebook and Google, etc., is that they not only have to employ this technology, but they have to do so in a cost efficient manner, in a computationally efficient manner. And that means that the cutting edge techniques in many cases are too computationally expensive to do at scale, right? When you look at something like a T5 transformer, or when you look at a model like uh GPT 3 or DaVinci or any of these really fancy text models, they don't have the same computational constraints that someone like Google does. Google has to ingest billions of pages a day, and to scan any more than a sample of them is computationally infeasible, right? To uh develop extremely complex algorithms to detect and discern did a human write this or did uh a machine write this?

When you consider useful content, again, does it matter who wrote it? Or does it matter if it's helpful or not? And so Google is looking at with its most recent algorithm update, which is this is being recorded in September of 2022, the helpful content update. There's definitely some content out there that is machine generated that does not help anybody. It is just garbage, and that's easy for a search engine to spot.

It's easy for you and I to spot. Where we run into trouble is when we're not sure anymore. Like, duh, so what happened here? Did a machine write this? Did a human write this?

It's it's not bad. And because of that computational disparity between what Google has to process at scale and what an AI model that's very sophisticated can process on its own and not have the same scale constraints, the AI model is gonna win. Eventually the quality gets better so good that Google will not be able to keep up. They may not already be able to keep up for the best stuff. For example, I can download and run any of the Ulithra AI language generation models and run them right on my laptop or run them on Google Colab or run them anywhere.

And they can generate, you know, a couple hundred pages of text pretty quickly. Now it may take an hour or two for my machine to crank out that much, but that's okay. I I can wait, right? I can wait for 200 pages of okay text. But the quality of that output is going to be better than what Google can look for at scale.

So what should you take away from this? The AI writing tools right now are still not great. They can produce really good mediocre quality content. They can produce mediocre content that you couldn't tell if a junior staffer wrote it or a machine wrote it, right? It's it's that good that it's just average, right?

And most of the content in the world is average. Most of the content in the world is mediocre. Read press releases, read corporate blog posts, read thought leadership blogs. I mean it's the same old stuff in a lot of cases. Be customer focused, right?

We've been saying that for what? 80 years, be customer focused. Can a machine write that article as well as the CEO of a Fortune 50 company? Absolutely. Because it you're not going to say anything new.

So the challenge for you as a marketer, for me as a marketer, is not only to create good content that's above mediocre, but to create original stuff, stuff that is truly unique, stuff that is truly has not been seen before and is not a retread that doesn't add value, right? The world doesn't need another blog post on being customer centric. The world doesn't need another blog post on being more human and social media. The world doesn't need you name the marketing trope of your choice. And there is a risk that if you're just cranking out the same old swill, you might actually get flagged by the helpful content update as being machine written.

If what you're writing is so copy and paste, so templated, you might actually be detected as a bot when you're not. So you've got to up your content quality. Machines will continue to improve. What's happening right now with transformers and diffusion models in AI is game changing. Machines are creating better and better content every day.

And for those of us who are creators, we've got to keep upping our skills. We've got to keep becoming better at our craft to stay ahead of the machines. If we don't, the machine's going to do our job or good chunks of our job. And we won't. Right.

And I've, as I've been saying for a while, an AI isn't going to take your entire job. It's just going to take like 60% of it. But if there's 10 of you at a company, the company doesn't need six of you, right? Because you can take that 60% of labor that it's the machine's doing and it can and uh a company can say, yeah, we can we can afford to downsize. So uh you know, machines won't take your entire job, those take big chunks of it, but it'll be enough that it will be a scale issue uh for you.

Flip side, if you are a lean, mean, scrappy startup, you will be able to punch way above your weight with the assistance of machines, right? If you can have a machine generating ad creative, you know, 16, 1800 pieces of ad creative overnight and uh in using a diffusion model. If you could have a machine writing 150, 200 blog posts a day, you know, we're again we're not talking about huge, you know, million piece data sets, we're talking a hundred pieces. But if you're a startup and you're a team of three or five or ten, you can, with the assistance of machines, look like you're a team of 500. You can behave like a team of 500.

So the onus is on us to scale up as individual creators, and the onus is on us to master the use of these machines so that we can scale ourselves, our creativity, and add that final polish that machines inevitably struggle to make. Um that's the future, uh, as I see it right now. And that again this is my opinion this is my opinion but that's the way I see things going where machines are going to create they today they create the first draft they're gonna evolve to create second third draft and yeah depending on the content type they may be doing final drafts in a couple of years so keep an eye on that really good question we could spend a whole lot of time on that but I think that's a good place to stop for today thanks for asking if you like this video go ahead and hit that subscribe button