Recommender Systems as Part of a Choice Architecture for HCI

In this workshop, we are viewing recommender systems as tools for helping people make better choices.1 From this perspective, recommender systems researchers and designers should know something about (a) how people make choices and (b) how the process of choosing can be supported. In this way, they can enable their recommender systems to work together more effectively with (a) the cognitive processes of their human users and (b) other computational tools that can help people make better choices. But in the vast literature from psychology and related fields that look at human choice and decision making, it is surprisingly hard to find coherent answers to either of these two questions. We have therefore introduced two interrelated models (summarized on a high level in Figure 1) that aim to synthesize knowledge about these questions in a coherent and memorable way.