AI docs · Responsible AI
AI and privacy
Handling personal and confidential data responsibly when building with AI tools and models.
What it is
- Privacy in AI is about what data goes into models and tools, where it is processed, and who can see it.
- It intersects with data-protection law (GDPR and others) and with trade-secret protection.
How it works
- Minimize: only send the data a task actually needs.
- Control where data is processed and whether it can be used for training.
- Strip or mask sensitive details before sending to third-party tools where possible.
Trade-offs
- Stronger privacy (self-hosting, masking) can add cost or reduce convenience.
- Convenience-first use of third-party tools can create compliance and confidentiality risk.
When to use it
- Any time personal, regulated, or confidential data is involved.
Common pitfalls
- Pasting confidential or personal data into tools without knowing how it is handled.
- Assuming a vendor does not train on your data without checking.
Related concepts
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