Understanding algorithmic recommendations. A qualitative study on children’s algorithm literacy in Switzerland
Julian Ernst
Abstract
Algorithmic recommendations are a central phenomenon in children’s media use, having the potential to shape their everyday lives. Therefore, the ability to consciously and critically interact with algorithmic systems – algorithm literacy – can be considered an important requirement especially for young users. How children actually understand algorithmic recommendations marks a blind spot in research. This study explores children’s algorithm literacy by conducting 26 focus groups with primary school children in Switzerland discussing video recommendations on YouTube. The qualitative analyses show that children make sense of algorithmic recommendations in quite complex ways, considering their networked, affective-involving, and economic-commercial character, indicating a general awareness, explanatory knowledge, and the beginnings of a critical stance towards recommendation engines.