TY - JOUR
T1 - In Platforms We Trust?Unlocking the Black-Box of News Algorithms through Interpretable AI
AU - Shin, Donghee
AU - Zaid, Bouziane
AU - Biocca, Frank
AU - Rasul, Azmat
N1 - Publisher Copyright:
© 2022 Broadcast Education Association.
PY - 2022
Y1 - 2022
N2 - 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.
AB - 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.
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U2 - 10.1080/08838151.2022.2057984
DO - 10.1080/08838151.2022.2057984
M3 - Article
AN - SCOPUS:85130051455
SN - 0883-8151
VL - 66
SP - 235
EP - 256
JO - Journal of Broadcasting and Electronic Media
JF - Journal of Broadcasting and Electronic Media
IS - 2
ER -