Open Access Journal

ISSN: 2183-2439

Editorial | Open Access

Algorithmic Actants in Practice, Theory, and Method

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Abstract:  What changes as algorithms proliferate within journalism and become more sophisticated? In this essay, we synthesize the articles in this thematic issue, which offer empirical evidence for how algorithms—and especially those designed to automate news production—are being incorporated not only into journalistic activities but also into the logics of journalism itself. They underscore that journalists have neither feared nor rejected such algorithms, as might be expected given the recent history of technological adoption in journalism. Instead, journalists have sought to normalize the technology by negotiating them against existing values and practices, and perhaps even reified some normative ideological constructs by finding unique value in what they offer as humans. These articles also highlight the shortcomings of those algorithms, giving pause to postulations of algorithms as potential solutions to shortcomings of trust in news and market failures. Indeed, such algorithms may end up amplifying the very biases that seed distrust in news all the while appearing less valuable to readers than their human counterparts. We also point to new opportunities for research, including examinations of how algorithms shape other stages in the journalistic workflow, such as interviewing sources, organizing knowledge, and verifying claims. We further point to the need to investigate higher analytic levels and incorporate additional perspectives, both from more diverse contexts (e.g., Global South) and from our sister academic fields (e.g., human–computer interaction). We conclude with optimism about the continued contributions this stream of work is poised to make in the years to come.

Keywords:  actants; algorithmic journalism; algorithms; automated journalism; automation; journalism; journalism studies; robot journalism



© Rodrigo Zamith, Mario Haim. This is an open access article distributed under the terms of the Creative Commons Attribution 4.0 license (, which permits any use, distribution, and reproduction of the work without further permission provided the original author(s) and source are credited.