ARTIFICIAL INTELLIGENCE IN JOURNALISTIC INTERVIEWS:POSSIBILITIES, RISKS AND ETHICAL ASPECTS OF USE

Modern journalism is undergoing a transformation under the influence of neural networks that automate routine tasks: analyze and transform large amounts of data, generate personalized questions for interviews. This increases the e ciency of work, but raises questions about ethics and the impact on professional culture. The aim of the work is to study the perception and experience of using neural networks in journalistic interviews among various groups of the professional community, to identify the main advantages and challenges of automation of journalistic work, and to discuss the need for ethical regulation of the use of artificial intelligence in modern journalism. The study used general scientific (synthesis, analysis, generalization) and empirical methods (secondary analysis of VTsIOM data, online survey of students, teachers and practicing journalists, targeted sampling (n=175), the survey was conducted in December 2024. Key findings: neural networks transform the process of preparing and conducting interviews, increasing the e ciency of journalists, but at the same time calling into question the preservation of traditional professional skills and ethical standards. Most respondents see neural networks as a tool for increasing the e ciency and speed of work, but doubts and di culties in assessing their benefits were recorded, which indicates the need for additional training and information, including in professional education. The issue of the ethical side of using neural networks remains controversial. There is no doubt that certain work formats are actively used and have a legitimate status - automation of data processing, transcription of interviews and creation of brief summaries of materials will allow journalists to focus on more creative and analytical tasks. Neural networks are perceived in the professional community as an e ective tool for automating routine tasks, accelerating data processing, forming questions and creating brief summaries.