Neural network perspective of transforming the concept "media"

The article explores the evolving concept of media in the context of neural networks and their growing influence on digital society. The authors aim to refine the definition of media to better align it with the study of neural networks, emphasizing the recursive relationship between technological progress and the conceptual evolution of media. The article argues that breakthroughs in communication technologies, particularly neural networks, have redefined the role of media, transforming it from a mere tool for information transmission to an active participant in the creation and dissemination of cultural meanings. The authors begin by tracing the historical development of media studies, highlighting how the field has evolved in response to technological advancements. They note that the conceptualization of media often lags behind the innovation cycle, yet each new medium provides a lens through which older media can be re-evaluated. This recursive dynamic is particularly evident in the discourse surrounding new media, which has shifted from traditional forms of communication to digital platforms that enable user-generated content and interactive engagement. The article introduces a novel definition of media as physical tools for collaborative meaningmaking, whose complex configurations can generate communication environments that exert a totalizing selection of cultural meanings for individuals. This definition is then applied to neural networks, which are characterized by their ability to learn, adapt, and modify their behavior based on data inputs. The authors argue that neural networks represent a new form of media, one that not only transmits information but also actively shapes the cultural and social environment in which communication occurs. A key contribution of the article is the concept of actant mediality, which refers to the active role of neural networks in transforming and generating meanings. Unlike traditional media, which operate as passive channels for information transmission, neural networks function as dynamic agents that continuously adapt to user interactions. This adaptability allows neural networks to create algorithmic environments that mediate human communication, blurring the boundaries between human and machine agency. The authors also discuss the implications of neural networks for digital society, particularly in terms of their impact on information processing and cultural production. They highlight the growing role of neural networks in generating content, analyzing social networks, and even influencing human perception of reality. However, they caution against the potential risks associated with the unchecked use of neural networks, such as the proliferation of fake news and the ethical dilemmas posed by autonomous decision-making systems. In conclusion, the article argues that neural networks represent a significant shift in the concept of media, transforming it from a static tool for communication to a dynamic, adaptive environment that actively participates in the creation and dissemination of cultural meanings. The authors declare no conflicts of interests.

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