When Algorithms Recommend What’s New(s): New Dynamics of Decision-Making and Autonomy in Newsgathering - Cools, Hannes (2021)
Newsroom innovation labs have been created over the last ten years to develop algorithmic news recommenders (ANR) that suggest and summarise what news is. Although these ANRs are still in an early stage and have not yet been implemented in the entire newsroom, they have the potential to change how newsworkers fulfil their daily decisions (gatekeeping) and autonomy in setting the agenda (agenda-setting). First, this study focuses on the new dynamics of the ANR and how it potentially influences the newsworkers’ role of gatekeeping within the newsgathering process. Second, this study investigates how the dynamics of an ANR could influence the autonomy of the newsworkers’ role as media agenda setters. In order to advance our understanding of the changing dynamics of gatekeeping and agenda-setting in the newsroom, this study conducts expert interviews with 16 members of newsroom innovation labs of The Washington Post, The Wall Street Journal, Der Spiegel, the BBC, and the Bayerische Rundfunk (BR) radio station. The results show that when newsworkers interact with ANRs, they rely on suggestions and summaries to evaluate what is newsworthy, especially when there is a “news peak” (elections, a worldwide pandemic, etc.). With regard to the agenda-setting role, the newsworker still has full autonomy, but the ANR creates a “positive acceleration effect” on how certain topics are put on the agenda.