Q: How can I do evals when traces contain sensitive data?
There is no replacement for looking at real interactions. This situation is not ideal, but there are some things you can do. Here are some options, in order of preference:
Try to find real data you are allowed to inspect. A customer may agree to share a subset of traces, or test users may let you review their interactions. Even limited access gives you examples of how people use the product.
If you cannot inspect the data yourself, work with domain experts who are allowed to see it. Make your product easier for them to verify as part of their normal work. For example, a medical research assistant could show a clinician the evidence behind each claim and flag conflicting sources for review. The clinician can correct a specific claim or resolve a conflict while using the product. Those decisions can provide additional data for evals, subject to the same restrictions on what you can store and share.
To design this well, learn how the experts check an answer. Give them links to the supporting evidence and smaller pieces of work they can review. Asking whether the final answer was helpful often tells you too little about what went wrong. I discuss this approach in this post.
Redact or edit traces so they can be shared. If sensitive information cannot be stored, redact it before logging. Redaction tools can miss sensitive information, so check their output. When edited traces can be shared, removing personal information and changing sensitive details can make real examples usable for review. Check that those edits preserve the behavior you need to evaluate.
If none of the above options are possible, synthetic data should be your last resort. Synthetic data can help you find initial problems but has the downside that it only gives you limited evidence about how real users will behave. Read more about when synthetic data may be unreliable.
This article is part of our AI Evals FAQ, a collection of common questions (and answers) about LLM evaluation. View all FAQs or return to the homepage.