In Platforms We Trust?Unlocking the Black-Box of News Algorithms through Interpretable AI
Document Type
Article
Publication Date
1-1-2022
Abstract
With the rapid increase in the use and implementation of AI in the journalism industry, the ethical issues of algorithmic journalism have grown rapidly and resulted in a large body of research that applied normative principles such as privacy, information disclosure, and data protection. Understanding how users’ information processing leads to information disclosure in platformized news contexts can be important questions to ask. We examine users’ cognitive routes leading to information disclosure by testing the effect of interpretability on privacy in algorithmic journalism. We discuss algorithmic information processing and show how the process can be utilized to improve user privacy and trust.
Identifier
85130051455 (Scopus)
Publication Title
Journal of Broadcasting and Electronic Media
External Full Text Location
https://doi.org/10.1080/08838151.2022.2057984
e-ISSN
15506878
ISSN
08838151
First Page
235
Last Page
256
Issue
2
Volume
66
Recommended Citation
Shin, Donghee; Zaid, Bouziane; Biocca, Frank; and Rasul, Azmat, "In Platforms We Trust?Unlocking the Black-Box of News Algorithms through Interpretable AI" (2022). Faculty Publications. 3438.
https://digitalcommons.njit.edu/fac_pubs/3438