Batt's experiment involved running the top 3 search results from the top 50 questions asked in the US over the last year through OpenAI's AI detector to assess whether they were likely or possibly AI generated. The results showed that the majority of the content ranked highly by Google was human-generated. However, the experiment found that 15% of the top search results in Google's top 50 questions asked in the US were either unclear, possible, or likely AI-generated. This indicates that Google is not penalizing AI content, as these are competitive keywords that get hundreds of thousands of searches.
Batt's experiment is important because it shows that AI-generated content can still rank highly on Google, provided it is useful and valuable to readers. Google's latest guidelines clearly state that it does not take into account the method of content creation, but only cares about the usefulness of the content in relation to its E-A-T (Expertise, Authoritativeness, Trustworthiness) factors.
Batt's experiment also demonstrates the value of technical and off-page SEO, as well as valuable content. The only likely AI website to appear in the top 3 listings had very high quality off-page SEO and appeared to be following Google's best practices.
Batt's experiment sheds light on the potential of AI-generated content to rank highly on Google and provides useful insights for content creators who want to generate high-quality content. He urges content creators to focus on providing value to readers rather than worrying about whether their content will be flagged as AI-generated.
Batt's full experiment can be found on his blog post and includes a downloadable CSV file of the data used in the experiment. For those who want to check their content for AI-generation, they can use OpenAI's AI detector free of charge at this link or use Originality.ai's AI detector, which is a commercial product that can detect AI content and check for possible plagiarism.
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