Exploring Tangible Algorithmic Imaginaries in Movie Recommendations

Abstract

Recommender algorithms play an active role in many everyday activities. However, personalized recommendations often produce negative experiences due to a lack of awareness, control, or transparency. Allowing users to materialize their algorithmic imaginaries exposes how they experience, perceive, and imagine recommender algorithms. Moreover, it can unearth novel and previously unattended design opportunities for tangible interactions with algorithms. Therefore, we explored how 15 users of a famous movie recommender system materialized tangible designs to reflect and discuss their algorithmic imaginaries during co-design workshops and interviews. Using thematic analysis, we identified two forms of algorithmic imaginaries that can inspire tangible interactions with recommender algorithms: metaphoric and datafied representations. Complementary themes exposed the influence of contextual factors and diverse negative attitudes towards personalized movie recommendations. Based on these findings, we suggest design opportunities and suggestions for improving the algorithmic experience of movie recommendations and similar systems through tangible user interfaces.