Henriette Cramer

Henriette Cramer’s work is focused on the safety and quality of data and machine learning decisions, and potential algorithmic risks in recommendation and content moderation. This includes translating abstract calls to action into concrete interventions and tooling, organizational support structure, as well as data-informed product direction.

Her product and research work has spanned voice and conversational platforms, quality of personalized recommendations and advertising, content moderation, location data, and human-robot interaction. She combines organizational work with quantitative, large-scale data and in-depth, qualitative research to understand both what is happening – and why. This includes the feedback loop between products and their users, the gap between people’s experiences and machine data, and how to create and iterate organizational infrastructure to ensure consistent data and scaled execution.

She prior was Spotify’s Head of Algorithmic Impact as a Director in the Trust & Safety team, where she built multiple teams and company-wide algorithmic safety and policy. Prior she was a data and research scientist at Yahoo working on news and search quality evaluation, and a researcher at SICS working on location data and human-robot interaction. Beyond product impact, her work has resulted in multiple awards, 10 patent filings. She is a well-cited expert with 60+ publications and holds a PhD from the University of Amsterdam on people’s interaction with systems that learn.