Overview
Consent
Explicit user consent collection for AI data processing
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Consent collects explicit user permission before AI systems process their data. As AI capabilities expand — analyzing personal documents, learning from conversations, sharing usage patterns — users need clear, granular control over what they're agreeing to. This pattern goes beyond a single 'I agree' checkbox by presenting each data processing activity separately, distinguishing required from optional consent, and making the implications transparent.
Variants
- Inline consent — Consent checkboxes embedded directly in the interface, shown at the point where data processing will occur.
- Modal consent — A dedicated overlay that blocks interaction until the user has reviewed and responded to consent items.
- Banner consent — A persistent bar at the top or bottom of the interface summarizing consent requirements with a link to details.
Use Cases
- First-run setup when AI features require data access
- Enabling conversation history storage or learning from user data
- Sharing anonymized usage data for model improvement
- Processing sensitive documents like medical records or financial data
- Activating AI features that access third-party integrations
Best Practices
- Separate required consent (necessary for functionality) from optional consent (nice-to-have features).
- Use plain language that explains what will happen with the user's data, not legal jargon.
- Allow users to change their consent preferences at any time, not just during onboarding.
- Visually distinguish required items so users understand what's mandatory vs. optional.
- Never pre-check optional consent items — informed consent must be an active choice.