Libel by Algorithm? Automated Journalism and the Threat of Legal Liability

TLDR

Automated journalism converts structured data into news stories, raising legal concerns, notably the unexplored risk that algorithm-generated content could be libelous. The paper aims to identify two critical challenges: determining fault in algorithm-based libel cases and the lack of applicable defenses for news organizations. Using the American libel law framework, the authors analyze these challenges. A review of legal cases shows that news organizations must seriously consider liability when deploying news‑writing bots.

Abstract

The rise of automated journalism—the algorithmically driven conversion of structured data into news stories—presents a range of potentialities and pitfalls for news organizations. Chief among the potential legal hazards is one issue that has yet to be explored in journalism studies: the possibility that algorithms could produce libelous news content. Although the scenario may seem far-fetched, a review of legal cases involving algorithms and libel suggests that news organizations must seriously consider legal liability as they develop and deploy newswriting bots. Drawing on the American libel law framework, we outline two key issues to consider: (a) the complicated matter of determining fault in a case of algorithm-based libel, and (b) the inability of news organizations to adopt defenses similar to those used by Google and other providers of algorithmic content. These concerns are discussed in light of broader trends of automation and artificial intelligence in the media and information environment.