Google Search Central Live Tokyo 2023 provided a platform for Google’s experts, including Gary Illyes, to shed light on AI-related topics and share valuable insights regarding Google’s stance and recommendations for AI-generated content.
Japanese search marketing expert Kenichi Suzuki summarized the event’s key takeaways in a blog post published in Japanese.
In this article, we will delve into Google’s approach to AI content and its impact on E-E-A-T (Experience, Expertise, Authoritativeness, and Trustworthiness).
We’ll explore Google’s unique perspective on labeling AI content, the importance of natural content. And the challenges surrounding AI-generated content and E-E-A-T, as well as the ongoing discussions within Google regarding AI policies.
Labeling AI Content: Google’s Unique Approach
While it is well-documented that Google prioritizes content quality regardless of whether it is AI-generated or not, there are some less-known aspects worth exploring. Let’s dive into the details!
Unlike the European Union’s request for voluntary labeling of AI-generated content, Google does not require publishers to label it.
Instead, Google puts emphasis on the importance of human review before publishing AI-generated and translated content.
However, while Google doesn’t require explicit labeling of AI-generated text content, they advise publishers to consider the user experience and use their judgment to decide whether labeling is necessary.
Kenichi Suzuki summed it up well by stating, “From Google’s point of view, it is not necessary to explicitly label AI-generated content as AI-generated content, as we evaluate the nature of the content. If you judge that it is necessary from the user’s point of view, you can specify it.
Natural Content and Google’s Ranking Algorithm
One of the key insights shared by Google during the event was their commitment to ranking natural content at the top.
Google’s algorithms and signals heavily rely on content created by humans for humans. This reaffirms the significance of natural, human-generated content in Google’s ranking process.
E-E-A-T and AI Content: The Challenge of Experience and Expertise
The concept of E-E-A-T plays a significant role in content evaluation, emphasizing the importance of expertise and experience. However, AI faces challenges in meeting the quality thresholds associated with experience.
AI models, such as ChatGPT and Bard, cannot claim expertise or experience in any specific field or product. This raises questions about how AI-generated content can satisfy the E-E-A-T criteria.
However, Google experts shared that they are actively engaging in internal discussions regarding this topic and have not yet finalized a policy. They reassure everyone that once a consensus is reached, Google will promptly announce their official stance about this.
In the meantime, Google advises publishers to prioritize content quality and remain vigilant in this AI-driven landscape.
In Conclusion
Google’s approach to AI content and E-E-A-T highlights the importance of natural, human-generated content and the challenges AI presents regarding experience and expertise.
As Google’s policies continue to evolve, publishers should focus on maintaining high-quality content. By keeping a close eye on Google’s recommendations and staying proactive, publishers can adapt to the changing landscape and deliver valuable content to their audiences.