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.

摘要

随着人工智能在新闻行业的使用和实施的迅速增加，算法新闻的伦理问题迅速增长，并导致了大量应用隐私、信息披露和数据保护等规范原则的研究。了解用户的信息处理如何导致平台化新闻环境中的信息泄露可能是需要提出的重要问题。我们通过测试可解释性对算法新闻中隐私的影响来检查用户导致信息泄露的认知路径。我们讨论算法信息处理并展示如何利用该过程来改善用户隐私和信任。