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Algorithmic curation is a book category that explores how algorithms and automated systems select, organize, rank and recommend content across media, marketplaces and public spaces. Works in this genre range from technical guides on recommender systems and machine learning to critical analyses of personalization, filter bubbles, bias, transparency and the ethics and governance of automated decision-making. They examine applications in news feeds, streaming services, e-commerce, social media, cultural institutions and archives, and address design patterns, human-in-the-loop practices, measurement of impact, and policy considerations. These books are aimed at technologists, designers, media scholars, policymakers and general readers interested in how algorithmic choices shape what we see, buy, learn and value.

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