Not For You

Not For You is an “automated confusion system” designed to mislead TikTok’s video recommendation algorithm, making it possible to see how TikTok feels when it’s no longer made “For You.” The system navigates the site without intervention, clicking on videos and hashtags and users to find the nooks and crannies TikTok’s algorithm doesn’t show us, to reveal those videos its content moderators suppress, and to surface speech the company hopes to hide. Through its alternative personality-agnostic choices of what to like, who to follow, and which posts to share, Not For You should make the For You page less addictive, and hopefully steer users away from feeling like the best path to platform success is through mimicry and conformity. Perhaps most importantly, Not For You aims to defuse the filter bubbles produced by algorithmic feeds and the risks such feeds pose for targeted disinformation and citizen manipulation. Finally, the work stands in opposition to letting corporations opaquely decide what we see and when we see it, to their intentional crafting of addictive user interfaces, and to the extraction of profit from the residual data left behind by users. Ultimately, Not For You asks us to think about who most benefits from social media’s algorithmic feeds, and who is made most vulnerable.