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Amazon’s new “Personalized Assumptions” page, which displays inferred traits about shoppers based on their purchase history, has prompted surprise and concern after a user discovered it on the retailer’s website. The shopper, who chose to remain anonymous, posted on the social‑media platform Threads that they found a list of assumptions Amazon had made about them and described the experience as “literally speechless.” TechCrunch reported the incident, noting the post’s viral spread among Amazon’s vast customer base.

The feature is part of Amazon’s broader effort to personalize shopping experiences by using data from users’ past orders, wish lists, and browsing activity. By compiling these signals into concise statements, the company aims to make recommendations feel more relevant and to help shoppers find new products quickly. However, the public presentation of these inferred traits raises questions about how the data is interpreted and whether users are fully aware of the underlying algorithms that generate the content.

Privacy advocates point out that the display of personal assumptions—whether related to lifestyle, preferences, or even physical attributes—could be seen as a form of profiling that users did not explicitly consent to. The fact that the assumptions are visible to the shopper themselves, and potentially to anyone who views the account, adds a layer of transparency that Amazon has not previously offered. Critics argue that the feature could influence purchasing decisions or reinforce stereotypes, and that users should be given clearer information about how