“Visual Perception” of Artificial Intelligence: Recommendation Algorithms and the Viewer’s Freedom of Choice

This article examines the impact of artificial intelligence-based algorithms on the film industry, specifically on film selection. It draws on Martin Scorsese’s thesis that algorithmic recommendations transform viewers into consumers and can lead to the elimination of cinematic masterpieces that do not meet the criteria for “success”. The paper’s novelty lies in its analysis of the limitations of algorithms in relation to the specific nature of visual material, namely its multilayered nature and multilevel interpretation. This analysis goes beyond traditional discussions of the conservatism of artificial intelligence.

The article analyzes the principles of recommendation algorithms in the film industry (collaborative and content-based filtering), including the personalization of posters and trailers. Particular attention is paid to the analysis of images as multilayered objects that can be interpreted at various levels: from visual perception to a deep understanding of meanings based on experience, knowledge, and culture. Examples from psychology (picture diagnostics), art history (Erwin Panofsky’s levels of interpretation), and semiotics (Roland Barthes’s analysis) are cited to illustrate the variability of image perception. The author concludes that artificial intelligence, “trained” at the basic level of object recognition and interpretation, is unable to encompass the full diversity of viewer perceptions and adequately assess the semantic depth of visual content. Using advertising analysis as an example, the limitations of artificial intelligence in semiotic analysis are demonstrated, suggesting that, due to the imperfections of recommendation systems, viewers’ abandonment of independent choice will indeed lead to a loss of meaningful content in film viewing.

Thus, despite advances in algorithms, their capabilities cannot replace human perception, preserving the need for independent film selection by viewers who are susceptible to the superficiality and errors of recommendation technologies. Their limitations create a demand for the preservation of viewer freedom of choice.

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