The Algorithmic Newsroom: Negotiating Journalistic Authority and Human Agency in Broadcast Journalism

Abstract

The paper examines how artificial intelligence and algorithmic systems are transforming journalistic authority and human agency in broadcast journalism. Guided by Gatekeeping Theory, Actor-Network Theory, and Sociotechnical Systems Theory, it adopts a qualitative desk-based approach using secondary data from literature and industry reports published between 2017 and 2026. Thematic analysis shows that algorithmic newsrooms have evolved from basic automation to advanced AI systems integrated throughout news production. Rather than replacing journalists, these technologies redistribute editorial authority within collaborative human–AI environments. Human agency remains essential for verification, ethical decision-making, contextual interpretation, and maintaining audience trust. The study concludes that algorithmic newsrooms represent a socio-technical partnership in which human oversight remains indispensable. It recommends institutionalising human-in-the-loop editorial policies, strengthening journalists' algorithmic literacy, and promoting transparency in AI-assisted news production to enhance accountability, credibility, and public confidence.