Mobile application (app) stores are a critical source of information about risk in an uncertain environment. App stores ought to assess and communicate the risk associated with an installation so that users are discouraged from installing risky or harmful apps in app stores. However, only a limited number of studies offer designers information about how to communicate risk effectively. We focused on the user’s trust associated with security information stemming from crowd-sourced evaluations compared to those generated from an automated system. Both of these sources of security information are pervasively used to indicate possible risk associated with an app. We investigated whether biases exist for a particular source of information given similar amount of security information being available. We found that participants preferred to install apps rated by automation to those rated by humans despite equivalence in stated risk. Further, we found evidence of a gender difference in trust in automation.