Model Card
A standardized technical document outlining the performance benchmarks, limitations, and intended use cases of an AI model.

THE TECHNICAL LANGUAGE OF DIGITAL B2B INFRASTRUCTURE
A set of qualities used in Google's search-quality guidance to assess whether content and its creator appear helpful and trustworthy.
E-E-A-T describes what Google's raters look for in helpful content, so it guides how businesses show real experience, author credentials and trust signals, especially on health, finance and other high-stakes topics.
A financial advice site adds author bios with qualifications, cites primary sources, shows review dates, publishes its editorial policy and adds first-hand product testing notes to its 50 most visited comparison articles.
E-E-A-T is not a single ranking factor or score, and raters do not directly change rankings. Adding author boxes or badges without real expertise or useful content rarely helps, and trust matters most among the four aspects.
E-E-A-T comes from Google's Search Quality Rater Guidelines, where human raters assess sample results so Google can evaluate its ranking systems. Experience is first-hand involvement, expertise is relevant knowledge or skill, authoritativeness is recognition as a go-to source and trustworthiness is accuracy, honesty and safety. Raters apply higher standards to pages that could affect health, finances or safety.
AI Governance, Experience Design
Google Search Central — Creating helpful, reliable, people-first content — https://developers.google.com/search/docs/fundamentals/creating-helpful-content; Google Search Central Blog — Our latest update to the quality rater guidelines: E-A-T gets an extra E for Experience — https://developers.google.com/search/blog/2022/12/google-raters-guidelines-e-e-a-t
A standardized technical document outlining the performance benchmarks, limitations, and intended use cases of an AI model.
A software design property ensuring that repeating an operation, such as an API request, has the same intended effect as running it once.
Deliberate activity generating invalid impressions, clicks, or conversions to extract illicit financial or competitive advantage.
Embeddings convert words, documents or images into lists of numbers that capture meaning, enabling semantic search, clustering, recommendations and RAG.
A unified collection of repeatable UI components, guidelines, tokens, and design standards ensuring digital product consistency.