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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.

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