Results of a study of background viewing of movies and TV series on online platforms: why we simultaneously watch our phones, and why producers rewrite narratives

This article examines the phenomenon of background viewing of audiovisual content as a persistent practice of divided attention, in which the primary screen (TV/platform) is accompanied by parallel activity on the “second screen” of a smartphone. It demonstrates that background viewing is becoming the dominant configuration of media consumption and is associated with institutional shifts in platform production. Within the framework of national strategies on AI, digital educational environments, and cultural policy, the principles of “responsible AI”, algorithmic transparency, and performance metrics are being translated into management decision-making regulations that influence narrative standards. Two operational metrics are introduced: the exposure index (EI) and the background stability index (BSI), which measure the preservation of comprehension during distraction as a function of EI, lexical editing complexity, and the frequency of “meaning beacons”. Empirical data support the hypothesis that increased background viewing is associated with narrative simplification (increased exposure, reduced implicitness, and normalized repetition) and the optimization of short-term metrics (entry, early retention, and completion) at the risk of reducing the depth of engagement and the cultural capital of works. It is shown that subtitles and repeated landmarks act as compensators for cognitive load, while social co-viewing creates an “attention-balancing” effect, reducing the need for intrusive repetition without compromising complexity. The practical contribution lies in the design of a dual-mode strategy for platforms and studios: a focused perception mode (reduced repetition, enhanced implicit connections) and a background stability mode (a controlled network of landmarks without destroying aesthetics). A measurable framework for auditing the impact of recommendation systems and AI editors on narrative complexity and content diversity within the framework of responsible AI is proposed for regulators. The results are relevant for the development of management models for film production, media studies of attention, and the updating of educational modules on media literacy in the digital environment.