AI and Machine Learning in Broadcast Media

News gathering, production, verification, and distribution have been reshaped—sometimes profoundly, sometimes quietly—by the growing presence of artificial intelligence and machine learning in broadcast operations. This chapter surveys the main areas where these technologies operate: automated news production, deepfake detection, audience analytics, recommender systems, and voice synthesis. It also examines ethical questions emerging in each domain. Drawing on recent scholarship across journalism studies, computer science, media ethics, and communication research, the chapter explores tensions between operational efficiency and journalistic integrity, between personalization and information diversity, and between AI-assisted verification and its vulnerability to synthetic content. A key theme is that productivity gains, though real, are not self-sustaining. Responsible deployment requires editorial oversight, effective governance, and transparent disclosure to audiences. The chapter concludes by outlining a research agenda for an information environment increasingly shaped by AI.

Hali tarjima qilinmagan