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, algorithmic literacy, 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 user 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; and (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 to 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 core courses in media/communication studies, such as Introduction to Communication, Current Issues in Communication, Communication Theory, and Communication Ethics.
"This comprehensive work uses original research to both focus and expand our understanding about the ways that the growing consumption of algorithmic news will impact both the news media business and participatory democracy. It provides sharp new insights at a critical moment in the evolution of journalism."
--Ryan Thornburg, Associate Professor of Journalism, School of Journalism and Media, University of North Carolina at Chapel Hill
"Roselyn Du's book is a roadmap to understanding how the audience of today's news are grappling with tailored communication, information cocoons, algorithmic literacy, and news literacy. This book is timely, insightful, and methodologically rigorous. This is a must read for students and scholars interested in algorithms and journalism."
--Kerk F Kee, Associate Professor of Media & Communication, Texas Tech University
"Guided by key theoretical considerations, this timely text details comprehensive empirical investigation of the effects of algorithmic news recommendations on news appreciation, news literacy, and public agenda priorities. Findings suggest that algorithmic news consumption may not be as dangerous as presumed and warned. A significant contribution of this work is support for the theoretical development of a renewed conception of the active audience and the redefinition of agenda-setting. A compelling case is made for the importance of research on algorithms and artificial intelligence for understanding the future of journalism and civic society."
--Cynthia King, Professor of Communication, California State University, Fullerton
About the Author: Roselyn Du received her PhD from UNC-Chapel Hill. Before joining the faculty at Cal State Fullerton, she spent ten years at Hong Kong Baptist University, where she received the Outstanding Performance Award in Scholarly Work, among other honors. In a previous life, she was an award-winning frontline journalist in China.
