Exploring Ways of Empowering the User Through the Use of Recommendation Systems

Abstract: This thesis aims to explore how we can empower users through using recommendation systems. Recommendation systems are all around us on the web, however today’s implementation is not necessarily that interactive. Literature argues for interaction designers to learn and get involved in the design of recommender systems and processes where AI technology is implemented. Moreover, designing with Artificial Intelligence as a material is explored and what interaction designers need to keep in mind when designing with it. The design process sets out to explore new ways of interacting with recommendation systems on the web. The process has used various design activities which generated several design proposals. These design proposals have been put through user testing using anonymous participants, in order to find a final design solution. The main conclusions are that informing and including users how the system works are important factors if we want users to interact with the recommender systems. It is not necessarily the most interactive design proposal that is the best solution, but rather one that is likely to interact with.