The Algorithmic Identities project explores the relationship between our identities and the multiple profiling and recommendation systems that pervade our daily lives.
Profiling and recommendation are a part of the online services we use every day. These services suggest things we might like to buy or people we might want to connect with. They recommend songs, books, movies, and television shows that we might want to listen to, read, or watch. Sometimes they get these recommendations right. Sometimes, though, they get these recommendations very wrong, making strange or even comical inferences about who we are from what we do online.
The aim of our project is to investigate how these algorithmic systems work and how they are understood by everyday users in Chile and the United Kingdom, where we’re based. What are recommendation systems? How do they work? How do they shape our online experiences? How do people feel about them? What does it feel like when they get us right? Or when they get us wrong?