Overview
Caveat
Contextual warnings and disclaimers for AI-generated content
warningdisclaimertrust
Docs
Caveats are contextual warnings and disclaimers that set appropriate expectations for AI-generated content. They acknowledge the inherent limitations of AI systems — potential inaccuracies, biases, or knowledge cutoffs — and empower users to approach outputs with informed skepticism. Unlike generic legal disclaimers, well-designed caveats are specific, timely, and proportional to the risk level of the content.
Variants
- Banner caveat — A prominent alert displayed above or below AI output, suitable for important warnings that apply to the entire response.
- Inline caveat — A subtle text annotation within the content flow, appropriate for low-severity notes that shouldn't interrupt reading.
- Tooltip caveat — A hover-triggered explanation attached to specific claims or data points, providing context on demand.
Use Cases
- Medical or legal AI tools where accuracy is critical
- Financial analysis tools with data freshness concerns
- Creative AI tools where outputs may contain unintended biases
- Research assistants working with potentially outdated information
- Any AI tool where outputs could be mistaken for authoritative facts
Best Practices
- Match caveat severity to actual risk — don't cry wolf with warnings on low-stakes content.
- Be specific about what might be wrong rather than using generic 'AI may make mistakes' disclaimers.
- Place caveats near the content they apply to, not buried in footers or separate pages.
- Make caveats dismissible for repeat users who have acknowledged the limitations.
- Include a 'Learn more' link for users who want to understand the specific limitation.