 Yet in practice, the function of hidden platform algorithms can defeat this diversity. Trained on user behavior to optimize for engagement and other metrics that advertisers and platform companies associate with their profit, these algorithms can ensure that I experience only a pale shadow of the true diversity of my social network, seeing at the top of my feed only those posts that I am most likely to find subjectively rewarding to engage with. If, for example, I support the Black Lives Matter movement, and tend to close the app in frustration and disappointment whenever I see BLM denigrated by someone I consider a friend, the platform algorithm can easily learn this association and optimize my experience for one that is more conducive to retaining my presence. It is important to note, however, that in this case the effect is an interaction between the algorithm and my own behavior. How much responsibility for echo chambers and resulting polarization or insularity falls upon users, and how much on the designers of algorithms that track and amplify our expressed preferences?