Trustworthy journalism through AI

Opdahl, Andreas L; Tessem, Bjørnar; Dang-Nguyen, Duc-Tien; Motta, Enrico; Setty, Vinay; Throndsen, Eivind; Tverberg, Are and Trattner, Christoph (2023). Trustworthy journalism through AI. Data & Knowledge Engineering, 146, article no. 102182.

DOI: https://doi.org/10.1016/j.datak.2023.102182

Abstract

Quality journalism has become more important than ever due to the need for quality and trustworthy media outlets that can provide accurate information to the public and help to address and counterbalance the wide and rapid spread of disinformation. At the same time, quality journalism is under pressure due to loss of revenue and competition from alternative information providers. This vision paper discusses how recent advances in Artificial Intelligence (AI), and in Machine Learning (ML) in particular, can be harnessed to support efficient production of high-quality journalism. From a news consumer perspective, the key parameter here concerns the degree of trust that is engendered by quality news production. For this reason, the paper will discuss how AI techniques can be applied to all aspects of news, at all stages of its production cycle, to increase trust.

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