Factors Influencing the Rejection of Automated Journalism: A Systematic Literature Review

Abstract

Purpose: Automation in journalistic processes is increasingly being discussed in media research and practice. Automated journalism (AJ) enables the fast production of numerous articles in real-time and in various languages. However, given the clear economic benefits of the technology, AJ is only adopted in a minority of newsrooms and has still very limited fields of use. This article aims to contribute to the open question why AJ is often rejected by professionals in the newsrooms, especially journalists, and which factors are perceived to be crucial for the rejection.

Methodology: A systematic literature review of peer-reviewed journal articles published between 2016 and 2020 was conducted, which identified 40 rejection factors in the research literature. The factors were then analysed on two dimensions: frequency and intensity.

Findings: The results show that factors such as limited bias detection, credibility concerns and unsolved issues of transparency are perceived as most influential for the rejection of AJ in the newsroom. The study indicated furthermore that soft factors, such as perceived quality or ethical / social issues, are more difficult to overcome than hard factors, such as economic or legal issues.