LANDMARK · 5 MIN · ORIENT
Training and use are different
After this landmark, you can separate “the model learning” from “the model answering”, and know which question to actually ask about your data.
Training is the one-time, expensive process that created the model’s abilities. Use is what happens each time you prompt it — the model’s knowledge doesn’t change from your conversation. So “it’ll learn from what I tell it” is a misunderstanding of the running model. The real question isn’t whether the model learns live (it doesn’t); it’s whether the product logs or reuses your inputs to train a future version — and that’s a policy you can look up.
This is the canonical concept. It stays the same across learner lenses so personalization never changes the underlying facts.
◌ EVERYDAY LENS
What this looks like for you
Your chat won’t make the model smarter, but the company might store it. Before sharing anything personal, check whether that product uses your inputs for training — it’s usually a setting or a policy line.
MAKE A DECISION
A colleague says “don’t worry, the AI forgets everything after each chat, so pasting the contract is fine.” Is that reasoning sound?
CARRY THISFor one AI tool you use, find its answer to: “are my inputs used to train your models, and can I opt out?”