AI engineering glossary · AI ethics law product
What is privacy budget?
Privacy budget (also called epsilon): In differential privacy, a limit on the total privacy loss allowed across all queries or training steps on a dataset, usually expressed by the parameter epsilon. Each analysis spends part of the budget; when it is used up, no more answers should be released.
Privacy budget: an example
An analytics team sets a budget of epsilon = 2 for a dataset; every released statistic consumes a share, and further queries are blocked once the budget is exhausted.
Related terms
More AI ethics law product terms
- Privacy by design
- Prohibited AI practices
- Protected attribute
- Proxy variable
- Pseudonymization
- Purpose limitation
- Re-identification
- Representation bias
Where you learn it
Privacy budget is part of the AI Engineering Program, which teaches it with notes, a hands-on lab and an exam. The first lesson is free.