SEO Unfiltered is a podcast produced by a leading B2B SEO agency for tech companies, Geeky Tech, and hosted by its content lead, Genny Methot. In the podcast, Genny discusses the leading issues in the world of SEO and digital marketing.
Seeing as how content generated by AI is such big news, it was inevitable that this topic would be brought up—and it was, in its February episode.
The guest on the podcast episode is Jo Priest, who is the head of online authority in the agency. As such, he has extensively studied SEO tools, algorithms, of course, generative AI.
He answers the hot questions that digital marketers are asking about ChatGPT and generative AI tools.
Here are some of the key points discussed in the episode.
AI-Generated Content Should Not Be Used Straight Up
Whilst Jo concurs that using AI as a virtual assistant—for generating ideas, summarising articles, and writing meta-descriptions, for example—is feasible, he states that it is not quite there yet for long-form content.
The argument provided is that Large Language Models (LLMs) aren’t capable of independent thought or unique ideas. They simply “study” information already available, and “predict the next token”.
So, ChatGPT can generate an article on a topic, but it will not have anything new or interesting to say. It will most likely be a rehash of information already available.
Whilst AI-generated long-form content will not necessarily be penalised by Google, the fact is that the search giant prioritises useful content.
As a result, Jo’s recommendation is for writers to use their discretion, as most want their content to be high in quality. Using AI to generate a draft might have errors and wrong information, so it is up to humans to make sure the content they are putting out is accurate and high quality.
AI Detection Tools May Not Be Accurate
According to Jo, relying on AI content detection tools might lead to false positives. As he explains, “[AI detection tools] look at the prediction of the next token.
“The way ChatGPT works is that it kind of splits words, or sentences, into little tokens—about three to four characters. Then, it tries to predict what comes next.”
He goes on to explain that AI detectors look for how predictable the next token is. If the next token is a predictable one, the detectors will flag it. Then, depending on how many predictable tokens they find, they will “pass judgement”.
The more the number of flags, the higher the likelihood of the content being written by a computer.
The problem with this type of testing, Jo says, is that if a writer has a predictable writing style, their content will get flagged, even if it is original, well-researched, and useful.
AI Can Be Used For Certain Types of Content
Even though AI tools aren’t ideal for long-form content, they could be very useful for short-form copy, such as headlines or titles, meta-descriptions, product descriptions, etc.
For large e-commerce websites, the products have their own pages and need original copy. However, that is not always possible, so businesses generally have a template in which they can edit sections to create descriptions for new products.
With AI tools, like ChatGPT, one can generate hundreds of descriptions that are varied enough for search engines to not look at them as plagiarised content.
Similarly, meta-descriptions for hundreds of pages might be a tedious task for digital marketers. However, with AI, one can generate descriptions for multiple pages in a matter of minutes.
Whilst these were two of the main themes in the podcast, there were other issues and opportunities around AI content that were discussed in the podcast.
Overall, though, the conclusion was that, whilst AI can be very useful in planning and large volumes of short-form content, it’s still not ideal for longer, informative content… yet.
The episode—Is AI-Generated Content Ready For the World? — as well as the podcast is available on the Geeky Tech website as well as on most of the popular podcast-streaming platforms, including Spotify and Apple Podcasts.
Parul Mathur has been writing since 2009. That’s when she discovered her love for SEO and how it works. She developed an interest in learning HTML and CSS a couple of years later, and React in 2020. When she’s not writing, she’s either reading, walking her dog, messing up her garden, or doodling.