Readers’ perception of computer-generated news: Credibility, expertise, and readability

Abstract

We conducted an online experiment to study people's perception of automated computer-written news. Using a 2 × 2 × 2 design, we varied the article topic (sports, finance; within-subjects) and both the articles' actual and declared source (humanwritten, computer-written; between-subjects). Nine hundred eighty-six subjects rated two articles on credibility, readability, and journalistic expertise. Varying the declared source had small but consistent effects: subjects rated articles declared as human written always more favorably, regardless of the actual source. Varying the actual source had larger effects: subjects rated computer-written articles as more credible and higher in journalistic expertise but less readable. Across topics, subjects' perceptions did not differ. The results provide conservative estimates for the favorability of computerwritten news, which will further increase over time and endorse prior calls for establishing ethics of computer-written news.

Periodismo computacional: evolución, casos y herramientas

“…Los temas abordados son muy variados: -opciones tecnológicas e innovadoras utilizadas (Newman, 2017;Shearer;Gottfried, 2017;Gynnild, 2014); -desafíos éticos y legales que comporta la creación de noticias con algoritmos (Weeks, 2014); -conceptos de autoría y copyright (Montal;Reich, 2016;Carlson, 2015); -necesidad de transparencia de los algoritmos para no cuestionar su manipulación (Diakopoulos, 2015; Hamilton; Turner, 2009) y asegurar la integridad de los datos (Dörr; Hollnbuchner, 2017); -percepción del lector sobre las noticias generadas (Wölker;Powell, 2018;Graefe et al, 2018); -opinión de los periodistas sobre el uso de robots en las redacciones (Thurman;Kunert, 2017;Jung et al, 2017;Lindén, 2017b).…”

Algorithms, Automation, and News

“…While continuing to focus on news gathering, those researching computational journalism have begun to cast their gaze more widely, including toward the use of automation and algorithms to compose news texts (see, e.g., Graefe et al 2016;Montal and Reich 2017;Thurman et al 2017). Initially, the automation of traditional, static news texts was the primary object of study.…”

Artificial Intelligence and Automated Journalism: Contemporary Challenges and New Opportunities

“…The phenomenon of fake news and misinformation is one of the most important challenges, facing journalists at present. Therefore, the use of smart software, in particular, journalistic algorithms has become imperative to identify fake news on the one hand, as well as enhance news quality and accuracy on the other [54]. Software such as Factmata1 is building expert contextual artificial intelligence to reduce misinformation and abusive content online.…”