In Platforms We Trust?Unlocking the Black-Box of News Algorithms through Interpretable AI

Author First name, Last name, Institution

Donghee Shin, Zayed University
Bouziane Zaid, University of Sharjah
Frank Biocca, New Jersey Institute of Technology
Azmat Rasul, Zayed UniversityFollow

Document Type

Article

Source of Publication

Journal of Broadcasting & Electronic Media

Publication Date

4-25-2022

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.

DOI Link

10.1080/08838151.2022.2057984

ISSN

0883-8151

Publisher

Informa UK Limited

First Page

1

Last Page

22

Disciplines

Communication

Scopus ID

85130051455

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). All Works. 5028.
https://zuscholars.zu.ac.ae/works/5028

Indexed in Scopus

yes

Open Access

no