Understanding Google’s EEAT: Evaluating Content without Explicit AI Tags

Google launches Bard AI. Google search bar on a phone in hand with release information on background. Google Bard AI vs OpenAI ChatGPT. Warsaw, Poland - February 8, 2023.

Google’s approach to AI-generated content evaluation aligns with its E-E-A-T concept, as explained by Japanese search marketing expert Kenichi Suzuki during Google Search Central Live Tokyo 2023. By prioritizing the quality and relevance of content, Google assesses factors like experience, expertise, authoritativeness, and trustworthiness to deliver the best user experience. While AI-generated content faces challenges in meeting EEAT criteria, such as establishing expertise and trustworthiness, Google avoids explicitly tagging AI content. Instead, it focuses on evaluating the nature and quality of the content itself, regardless of its origin.

According to Japanese search marketing expert Kenichi Suzuki’s statement during the Google Search Central Live Tokyo 2023, Google does not find it necessary to explicitly label AI-generated content as such. Instead, Google evaluates the nature of the content itself. This approach aligns with Google’s focus on the EEAT concept, which emphasizes experience, expertise, authoritativeness, and trustworthiness.

The decision to avoid tagging AI content can be attributed to a few reasons. Firstly, Google aims to prioritize the quality and relevance of content regardless of its origin. Whether the content is AI-generated or human-created, Google assesses it based on factors like experience, expertise, authoritativeness, and trustworthiness to provide the best user experience.

From the perspective of the concept, AI-generated content faces challenges in meeting the criteria. Expertise and authoritativeness may be difficult to establish without clear attribution or a track record of reliable sources. Trustworthiness can also be compromised due to potential inaccuracies or lack of fact-checking in AI-generated content.

By evaluating the nature and quality of the content itself, Google can assess its factors and determine its relevance and reliability without relying on explicit AI tags. The focus remains on ensuring that the content meets the criteria for expertise, authoritativeness, and trustworthiness, regardless of whether it was generated by AI or created by humans. This approach allows Google to prioritize delivering valuable and reliable information to users while promoting high-quality content in search results.

What is EEAT?

Google’s EEAT concept stands for Experience, Expertise, Authoritativeness, and Trustworthiness. It is a set of criteria that Google uses to assess the quality and reliability of web content when ranking search results. Here’s a breakdown of each component:

  1. Experience: This is associated with how the content creator can adequately prove experience, e.g. a restaurant review written by someone who has never eaten
    at the restaurant versus customer who has visited the place often.
  2. Expertise: This refers to the knowledge and expertise demonstrated by the content creator or website. Google looks for content that is created by individuals or organizations with expertise in the subject matter. This expertise can be demonstrated through qualifications, credentials, experience, or a track record of producing high-quality content.
  3. Authoritativeness: Authoritativeness is closely related to expertise but focuses more on the reputation and authority of the content creator or website. Google considers content from authoritative sources as more reliable and trustworthy. Factors such as backlinks from other reputable websites, mentions by industry experts, or being recognized as a leader in the field contribute to establishing authoritativeness.
  4. Trustworthiness: Trustworthiness refers to the reliability and credibility of the content itself and the website hosting it. Google evaluates various signals to determine trustworthiness, including accurate information, transparency, and a lack of deceptive practices. Websites that provide accurate and up-to-date information, protect user privacy, have clear policies, and avoid misleading or spammy tactics are considered more trustworthy.

Google uses these E-A-T factors to assess the overall quality and relevance of web content, particularly for topics that require expertise or may impact users’ well-being, such as medical advice, financial information, or news. Websites that demonstrate high levels of expertise, authoritativeness, and trustworthiness are more likely to rank higher in search results and provide users with valuable and reliable information.

EEAT and AI: Does it have a negative effect?

The E-E-A-T concept employed by Google may have a negative impact on AI-generated content. AI-generated content often lacks the depth of expertise and knowledge that human experts possess. While AI models can generate text based on patterns and data, they may not have the same level of understanding or contextual awareness as human experts. As a result, AI-generated content may struggle to meet Google’s criteria for expertise. Furthermore, establishing authoritativeness becomes challenging as AI-generated content is typically not associated with specific individuals or organizations. Google places importance on content from reputable sources, which may hinder the ranking of AI-generated content. Additionally, trustworthiness is a critical aspect of the concept. AI-generated content may be prone to inaccuracies or lack proper fact-checking, potentially undermining its trustworthiness. Human oversight is crucial in ensuring the accuracy, quality, and compliance of content, which AI-generated content often lacks. To align with Google’s standards, AI-generated content would need to undergo rigorous review, fact-checking, and be associated with reputable sources or experts to establish expertise, authoritativeness, and trustworthiness. The fact is that AI can generate content at a speed never before seen. But the reality is that it has no experience with the topic, for the AI engine it is just a series of words. 

If AI content will be judged based on the merit of EEAT the production method is irrelevant. The questions and the objective of the article are the main golas. This is good for content, maybe less time writing and more time thinking about what to write.