In a special guest post for OJB, Vanessa Fillis speaks to AlgorithmWatch’s Nicolas Kayser-Bril about his work on how online platforms optimise ad delivery, including his recent story on how Facebook draws on gender stereotypes.

Kayser-Bril first became aware of automated discrimination when he read about an experiment done by researchers at North Eastern University in the US. Seeing that the analysis could be replicated in Europe, he decided to take a closer look at Facebook and Google’s distribution systems.

“Automated systems are supposed to bring relevant content to the users,” says Nicolas. “And I use ‘relevant’ because it’s the adjective that Facebook uses — and there is a sense that relevant content is determined based on the actions of the users themselves.”

But in reality, everything Kayser-Bril knows about large scale automated systems like Facebook’s news feed hints that their decisions about what to show to an user is based on many different factors instead. Continue reading →