Confidentiality
Keeping private material from people who may not see it. Check who can read, store, or share what you put into a tool.
Document stays on the machine. Only people with access to that machine can see it.
Document travels to the company’s servers. What happens next depends on your plan and settings: stored for a while, used for training, or deleted after the answer.
The app looks the same either way. The settings and the contract are where the difference lives.
The fuller definition
Confidentiality concerns restricting access to information to authorized recipients. For AI systems, assess the full path through uploads, processing, storage, logs, and connected tools.
Go deeper
- Your computer
- Model running on it
- Answer stays on it
Confidentiality depends on the machine and anything else connected to it.
- Your computer
- Provider's servers
- Storage, logs, possibly training
- Answer returned
Confidentiality depends on the contract, the account tier, and the settings in force.
Neither route is safe by default. The question is the same for both: who can see the material, where is it kept, and for how long.
A concrete example
A workflow diagram records which provider receives a document and where copies and outputs are retained.
The distinction that matters
Local inference alone does not establish that every connected tool, log, backup, or device is private.
Related terms
Where it is taught
Test an AI workflow on work you can assessSource and further reading
LSO Rules of Professional Conduct — confidentialityThe definition and example are written for this library. The link gives background, official documentation or legal authority as labelled. Legal scope depends on the jurisdiction and current text; product features depend on release and settings.