I direct Spotify’s algorithmic impact & responsibility effort.
My research background revolves around the human side of data and machine learning. I am particularly interested in the impact that teams’ design, data and metrics decisions have on algorithmic outcomes. This includes the feedback loop between products and their users, the gap between people’s experiences and machines’ data interpretation, and recommendations’ societal impact.
I combine quantitative, large-scale data approaches with in-depth, qualitative research to understand both what is happening and why. This also means translating research outcomes into policy, tooling and pragmatic business and product direction.
My work has spanned voice and conversational platforms, quality of personalized recommendations, ad moderation, location data interpretation, and human-robot interaction.