Generative Neural Networks in Regional Mass Media: Usage Proficiency and Ethical Attitudes of Journalists and Students in Nizhny Novgorod

Abstract

This study provides a review of scholarly literature on the ethics of artificial intelligence (AI) usage, editorial standards in mass media, and research on the application of neural networks in journalism. The primary objective is to identify the ethical attitudes and practical experience with neural networks among media studies students at Lobachevsky State University of Nizhny Novgorod and to juxtapose these findings with the demands of the media industry in the Nizhny Novgorod region. The article presents an analysis of an online survey conducted among university media students (N=255) and journalists from 20 media outlets in Nizhny Novgorod (N=81), focusing on their practices and ethical stances regarding the use of neural networks. The findings indicate that a majority of journalists acknowledge the use of neural networks in their newsrooms. It is noted that the initiative to adopt these technologies typically comes from the employees themselves, who integrate them into their workflows alongside other tasks. The study establishes that students are primarily acquiring skills in using neural networks during their university studies, with proficiency levels increasing in their senior years. A key finding emphasizes that, according to journalists, for graduates, technical AI skills are less critical than the ability to editorially assess and fact-check AI-generated content; core professional competencies unrelated to AI remain paramount. No significant gap was identified in the ethical perceptions of students and media practitioners; notably, students often demonstrate greater “ethical caution.”