Promises and Perils of Automated Journalism: Algorithms, Experimentation, and “Teachers of Machines” in China and the United States

Abstract

ABSTRACT Automated tools for parsing and communicating information have increasingly become associated with the production of journalistic content. To study this phenomenon and to explore the development of automated journalism across two locales at the cutting edge of technology, we leverage insights from in-depth interviews with news technologists from pioneering news organizations and Internet companies specialized in the construction of “news bot” technology in the United States and China, including The Associated Press, The New York Times, The Atlanta Journal-Constitution, BuzzFeed, Quartz, Xinhua Zhiyun, Southern Metropolis Daily, Toutiao, and Tencent. Based on these interviews, we document how the creation of automated journalism products is heavily dependent on the successful assembly of actor networks inside and outside organizations. While metrics for measuring the success of automated journalism are applied differently, they often center around the augmentation of existing reportorial activities and focus on replacing rote and mundane (human) work processes. Some of the biggest challenges in automated journalism lie in curating high-quality datasets and managing the associated high stakes of errors in a business defined by trust. Lastly, automated journalism can be seen as a form of experimentation, helping its protagonists to future-proof their respective organizations.