We propose an experimental design based on a browser extension. In our ongoing study, we explore the long-term effects of personalization on content consumption on youtube.com. Participants, upon installing the extension, are randomly assigned to Treatment or Control groups. The Control group sees default personalized recommendations, with the extension collecting and sending their usage data to our server. For the Treatment group, some recommendations are replaced with generic, non-personalized ones, akin to the experience of an unlogged user. With 500 U.S. participants using the extension for three months, our study aims to address questions like: ”Does personalization increase platform engagement?”, ”Does it reduce content diversity?”, and ”Do generic recommendations introduce a popularity bias?”. Our methodology allows us to gauge outcomes in relation to the strength of the de-personalization intervention, as we document both personalizedand un-personalized recommendations for every user interaction.