Explainability
How well a system can show why it reached a decision. It matters most where the decision affects somebody — a loan, a diagnosis, a job application — and “the model said so” is not an answer.
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How well a system can show why it reached a decision. It matters most where the decision affects somebody — a loan, a diagnosis, a job application — and “the model said so” is not an answer.
A map of things and how they relate — this company, its founder, its address, its services. Search engines and AI systems use one to know that two mentions of a name refer to the same business.
The craft of writing instructions that get reliable results from an AI — being specific, giving examples, saying what to avoid. Less mysterious than it sounds, and mostly the same skill as briefing a new colleague well.
A public page stating how a business uses AI and what it does with customer data. Increasingly expected, and cheap to write honestly.
The crawler OpenAI uses to answer live searches in ChatGPT, separate from GPTBot. Blocking one does not block the other, so a site can be absent from ChatGPT search while still being read for training.
The text, images or code a model learned from. It shapes everything the model knows and every bias it carries, and it is why what your website said two years ago may still be what an assistant repeats.
When a search engine surfaces one relevant passage from a long page rather than judging the page as a whole. Clear headings are what make a passage findable in isolation.