In this article, we argue that journalism studies, and particularly research focused on automated journalism, has much to learn from Human-Machine Communication (HMC), an emerging conceptual framework and empirically grounded research domain that has formed in response to the growing number of technologies—such as chatbots, social bots, and other communicative agents enabled by developments in artificial intelligence (AI)—that are designed to function as message sources, rather than as message channels. While the underlying, but often unquestioned, theoretical assumption in most communication research is that humans are communicators and machines are mediators, within HMC this assumption is challenged by asking what happens when a machine steps into this formerly human role. More than merely a semantic move, this theoretical reorientation opens up new questions about who or what constitutes a communicator, how social relationships are established through exchange among humans and machines, and what the resulting implications may be for self, society, and communication. In the particular case of automated journalism—in which software assumes a news-writing role that has long been considered a distinctly central, and indeed human, element of journalism—the introduction of HMC offers a generative starting point for theory development, advancing our understanding of humans, machines, and news for an oncoming era of AI technologies.
Lewis, S. C., Guzman, A. L., & Schmidt, T. R. (2019). Automation, Journalism, and Human–Machine Communication: Rethinking Roles and Relationships of Humans and Machines in News. Digital Journalism, 7(4), 409–427. https://doi.org/10.1080/21670811.2019.1577147