How Google's Quality Raters Evaluate E-E-A-T (And What It Means for AI)
Google employs over 16,000 human quality raters worldwide to evaluate search results using a detailed 170+ page guideline document. These raters don't directly influence rankings, but their feedback helps Google refine its algorithms. Understanding how they assess E-E-A-T helps you create content that meets Google's quality standards—and increasingly, the standards AI search engines use to select sources.
Key Takeaways
- • 16,000+ raters evaluate search quality using official guidelines
- • Raters don't rank pages—they provide feedback to improve algorithms
- • E-E-A-T is central to their evaluation criteria
- • AI systems are trained on similar quality signals
Who Are Google's Quality Raters? #
Quality raters are contractors hired through companies like Appen, Telus International, and Lionbridge. They:
- Work remotely, often part-time
- Follow Google's Search Quality Rater Guidelines
- Evaluate search results, not individual websites
- Provide human judgment on algorithmic outputs
- Represent diverse geographic and demographic backgrounds
How E-E-A-T Evaluation Works #
Raters assess pages on a scale from Lowest to Highest quality. E-E-A-T is evaluated at multiple levels:
Page-Level Assessment #
- Does the content demonstrate first-hand experience?
- Is the author qualified to write about this topic?
- Is the information accurate and well-sourced?
- Is the content transparent about authorship and purpose?
Site-Level Assessment #
- Does the website have a good reputation?
- Is there clear ownership and contact information?
- Are there trust signals (About page, policies)?
- What do external sources say about this site?
Creator-Level Assessment #
- Who is the content creator?
- What are their credentials?
- Do they have relevant experience?
- What is their reputation in this field?
The Quality Rating Scale #
| Rating | E-E-A-T Characteristics |
|---|---|
| Highest | Outstanding E-E-A-T, authoritative source, unique value |
| High | Strong E-E-A-T, clear expertise, trustworthy |
| Medium | Adequate E-E-A-T for the topic, nothing exceptional |
| Low | Lacking E-E-A-T, questionable accuracy or expertise |
| Lowest | Harmful, deceptive, or completely untrustworthy |
Higher Standards for YMYL #
For YMYL (Your Money or Your Life) topics, raters apply stricter E-E-A-T standards:
- Health: Medical credentials expected, accurate information critical
- Finance: Professional qualifications, up-to-date guidance
- Legal: Attorney authorship or expert review
- Safety: Verified accuracy, potential for harm considered
What This Means for AI Search #
AI search engines like Perplexity and Google SGE use similar quality signals to select sources:
- Training data: AI models learn from quality-rated content
- Citation selection: AI prefers sources that demonstrate E-E-A-T
- Trust evaluation: Similar signals used to verify reliability
- YMYL awareness: Higher standards for sensitive topics
Content that would receive high quality ratings from human raters is more likely to be cited by AI systems.
Practical Implications #
To create content that would rate highly:
- 1Demonstrate expertise: Show credentials, explain your background
- 2Show experience: Include first-hand evidence of involvement
- 3Build authority: Cite authoritative sources, earn recognition
- 4Establish trust: Be transparent, accurate, and secure
- 5Consider YMYL: Apply higher standards for sensitive topics
Product Manager at Seenos.ai. Pioneer in AEO research since 2024, exploring the convergence of SEO and GEO (Generative Engine Optimization). Led multiple AI-powered content optimization projects that achieved 300%+ citation increases in ChatGPT and Perplexity.