Algorithmic Audience in the Age of Artificial Intelligence employs a mix-methods approach to examine and interpret the algorithmic news consumption phenomenon from several inter-related perspectives, including tailored communication, customization, gatekeeping, agenda-resisting, and news literacy. Potential implications for an empowered or rather, (information-) cocooned public are explored. The research aims to illuminate the renewed relationship between media and audience and the effects on users of algorithmic processes. The aim of the book is multifaceted: (1) to describe the phenomenon of AI-based news recommendation; (2) to explore the use experience of consuming recommended news; (3) to analyze the effects that algorithmic news consumption has on the audiences; (4) to raise awareness of the impact of algorithmic news consumption; (5) to inform the public, technocrats, and policy makers of the effects of algorithmic news consumption; (6) to guide debate on ethical decision-making and possible policy change. Through an empirical investigation process, this volume examines algorithmic news consumption from a user perspective and dissects the complex effects caused by such consumption. This book is suitable to be a primary text for undergraduate-level courses relating media literacy issues and graduate-level courses with a particular focus on audience analysis in the age of artificial intelligence. It can also serve as a supplemental text for a core course in media/communication studies, such as Introduction to Communication, Current Issues in Communication, Communication Theory, Communication Ethics, etc. Worldwide.

Algorithmic Audience in the Age of Artificial Intelligence employs a mix-methods approach to examine and interpret the algorithmic news consumption phenomenon from several inter-related perspectives, including tailored communication, customization, gatekeeping, agenda-resisting, and news literacy. Potential implications for an empowered or rather, (information-) cocooned public are explored. The research aims to illuminate the renewed relationship between media and audience and the effects on users of algorithmic processes. The aim of the book is multifaceted: (1) to describe the phenomenon of AI-based news recommendation; (2) to explore the use experience of consuming recommended news; (3) to analyze the effects that algorithmic news consumption has on the audiences; (4) to raise awareness of the impact of algorithmic news consumption; (5) to inform the public, technocrats, and policy makers of the effects of algorithmic news consumption; (6) to guide debate on ethical decision-making and possible policy change. Through an empirical investigation process, this volume examines algorithmic news consumption from a user perspective and dissects the complex effects caused by such consumption. This book is suitable to be a primary text for undergraduate-level courses relating media literacy issues and graduate-level courses with a particular focus on audience analysis in the age of artificial intelligence. It can also serve as a supplemental text for a core course in media/communication studies, such as Introduction to Communication, Current Issues in Communication, Communication Theory, Communication Ethics, etc. Worldwide.