Sometimes the Best Choice Is Not to Choose

This chapter explores the dynamics of decision-making in the context of digital platforms, focusing on how algorithms shape user behavior, taste formation, and cultural consumption. Starting from the apparent paradox of choiceâ€Â" where users often experience stress and indecision when facing an excess of optionsâ€Â" it examines recommendation systems as technological responses designed to optimize engagement and reduce cognitive load. Through the case of Netflix and other major platforms, the analysis investigates how user data, predictive models, and attention metrics guide the production, distribution, and reception of serial content. Emphasis is placed on the concept of algorithmic technicity and the sociotechnical construction of attention, showing how platforms not only interpret preferences but actively participate in shaping them. By integrating perspectives from media theory, cultural analytics, and platform studies, this chapter interrogates the role of personalization and data-driven design in transforming aesthetic experiences and cultural ontologies. The discussion ultimately argues for a nuanced understanding of algorithmic culture, moving beyond deterministic readings and highlighting the interplay between human agency and machinic mediation in contemporary serial fiction.