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A recommender system’s ability to establish trust with users and convince them of its recommendations, such as which camera or PC to purchase, is a crucial design factor especially for e-commerce environments. This observation led us to build a trust model for recommender agents with a focus on the agent’s trustworthiness as derived from the user’s perception of its competence and especially its ability to explain the recommended results. We present in this article new results of our work in developing design principles and algorithms for constructing explanation interfaces. We show the effectiveness of these principles via a significant-scale user study in which we compared an interface developed based on these principles with a traditional one. The new interface, called the organization interface where results are grouped according to their tradeoff properties, is shown to be significantly more effective in building …