Algorithmic Journalism: Navigating Societal Challenges and Promoting Public Interest Accountability
Wenjie Li
School of Art Design and Media, Guangzhou Xinhua University
Dong Wu
School of Art Design and Media, Guangzhou Xinhua University
Xuan Tan
School of Art Design and Media, Guangzhou Xinhua University
Zhirui Chen
School of Art Design and Media, Guangzhou Xinhua University
DOI: https://doi.org/10.59429/pmcs.v6i3.7256
Keywords: News algorithms; Public interest; Societal challenges; Accountability
Abstract
News algorithms are being increasingly incorporated into news production process including newsgathering, production and dissemination with an aim to automate journalistic tasks. To this end, this paper examines the societal challenges that limits the adoption of algorithms. Existing literature have discussed ethical issue related to legal accountability of algorithms in the event of producing stories with inaccurate data and potential solution to release algorithm-related information to public in hope of achieving accountability. In doing so, studies have indicated the importance to understand how audiences may perceive on algorithmbased news production. Regarding potential replacement of journalists with algorithms, scholars have found that due to limited access to structured data, algorithms are still far from replacing journalists. In addition, researchers have highlighted that to avoid existing ethical issues of biases and discriminations from being embedded into algorithms, it is crucial to confront and rectify the hierarchical logic that serves as the root cause of discrimination prior to the development of algorithms. In terms of public interest value, studies have touched on the bad influence of newsroom metrics on news coverage and quality due to editorial news selection process being oriented towards audience preferences over publishing stories with public interest value. Traditionally, public service value is also challenged due to excessive dependence of journalists on reliable official sources with economic or political authority for news leads. This creates patterns of asymmetry in service to public, leading to marginalization of social groups. However, this issue has been somewhat overlooked and with the introduction of news algorithms, it could be the right moment to explore the capacity of algorithm-based news to serve the public interest of diverse social groups.
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