Ambient Intelligence is a promising research area that opens attractive perspective for improving human-computer interaction. Since AmI systems require knowing user's private information, privacy issues are especially relevant. This paper follows a two-fold approach. Firstly, a privacy framework for AmI systems is introduced. We analyses the elements involved in privacy management and the nature of personal information. Mainly we will focus on control privacy for shortterm information. Secondly, this work presents a privacy management solution, simple enough for the common understanding, but rather flexible to fulfill users and services expectations. This proposal, named as “Fair-Trade” metaphor, relays on trading quality of service for information. This strategy combined with optimistic access control and a logging mechanism, enhances users' confidence in the system while encouraging them to share their information, with the consequent benefit for the community.