We often construct AI systems that optimize over specified objectives serving as proxies for human values. Consider recommender systems on social media and entertainment streaming platforms, which maximize the time-on-application or other user-engagement metrics, as a proxy for providing entertaining content to users. The research community has also begun to study how optimizing systems influence human values (e.g., shifts political leanings or predictable induction into specific online communities). We are left with an obvious, yet overlooked framework: Consideration of values and optimizers as a highly intertwined and interactive system; one that constantly feeds into and transforms the other. This perspective is crucial for engineering safe and beneficial AI systems—ones which preserve diverse values across individuals and communities.