What is Privacy
Control over how personal or sensitive information is collected, used, shared, and protected.
Definition
Privacy is control over how personal or sensitive information is collected, used, shared, and protected. In practical AI work, it helps teams connect a concept to data, model behavior, product choices, evaluation, and risk. The useful question is not only what the term means, but how it affects quality, cost, reliability, and decisions in a real workflow.
Example
A customer support assistant masks phone numbers and avoids using private conversations for model training without permission.
Why it matters
Privacy matters because control over how personal or sensitive information is collected, used, shared, and protected can change how teams build, evaluate, choose, or govern AI systems. It helps teams judge safety, trust, accountability, and the risk of harm before an AI system reaches real users.
How it works
Teams usually define the risk scenario, inspect the data and model behavior, test failure cases, document decisions, and decide who can review or override the system. For Privacy, the key is to connect the definition with inputs, assumptions, measurable outcomes, and deployment limits.
Where it is used
- Used in AI governance, product review, data protection, model audits, policy work, and deployment approvals.
Limitations
The right answer depends on jurisdiction, domain, user group, and the actual system design, so legal and domain review may still be needed.