  Extensive recent media focus has been directed towards the dark side of
intelligent systems, how algorithms can influence society negatively. Often,
transparency is proposed as a solution or step in the right direction.
Unfortunately, research is mixed on the impact of transparency on the user
experience. We examine transparency in the context an interactive system that
predicts positive/negative emotion from a users' written text. We unify
seemingly this contradictory research under a single model. We show that
transparency can negatively affect accuracy perceptions for users whose
expectations were not violated by the system's prediction; however,
transparency also limits the damage done when users' expectations are violated
by system predictions.
