Artificial journalism: the reverse of human-machine communication paradigm. Mapping the field of AI critical media studies

Abstract

The study for the first time endeavours to elucidate the distinct conceptual nuances of AI-driven journalism, exploring how it reshapes the core technological and communicative attributes of the field while influencing societal dynamics. The crisis within AI-driven human-machine interaction in journalism rooted in the essence and processing of information is defined. Despite the paradigm of journalism is rooted in a human-centered approach, its AI-driven paradigm is the same - but in a reversible mode. Journalism involves the translation of personal perspectives and experiences through the filter of memory. Algorithms function without the nuances of personal and social memory, thereby undermining the core principles of the journalistic profession. The loss of genuine, “analog” memory among journalists and their audiences, alongside the digital “memory” of algorithms, jeopardizes the fundamental societal role of journalism-upholding social order. Re-thinking the AI phenomenon as artificial communication, the authors propose the term “artificial journalism”. At the basic technological level it is based on various forms of automation and embedded within digital infrastructures; at the societal level it is designed for the central purpose of journalism and entangled with human practices. Both the levels are reversible. The term could serve as an umbrella term for all the AI-driven journalism activities. Also it removes contradictions not only in human-machine communication but clarify the essence of AI performance in journalism and media studies, and for the users. The emergence of AI-driven media practices opens the basic crisis conceptual contradictions which provokes new realms of research and necessitates the establishment of critical AI media studies.