The case of Omni further underscores the fact that the journalistic practice in the social media age cannot be reduced to making the news “algorithm ready,” blindly following the dictations of Facebook. Here, it becomes apparent that algorithms also problematize the practice and meaning of doing journalism. In contrast to previous research on journalists’ responses to new technologies in the newsroom, which is “nearly unanimous in concluding that journalists react defensively in the face of such boundary intrusions on their professional turf” (Lewis & Usher, 2016: 15), many of the editors working at Omni see new technologies as part of the atraction of working there in the first place. Although, of all the organizations studied, Omni has, perhaps, gone furthest in making the algorithm an essential component of the editorial workflow itself, we can conclude that the algorithm by no means deskills the workforce, as critics often worry. Instead, the inclusion of an algorithm into the workflow repositions and displaces the work in new ways. As the notion of problematization is meant to highlight, one cannot look at algorithms as something new and detachable that has been added to a preexisting journalistic domain. Such a notion falsely presupposes that algorithms and journalism are discrete and freestanding domains that suddenly have been forced to interact. Conceived instead as “eventful,” algorithms are defined by their capacity to produce new environments. This alternative view is much more nuanced analytically, providing greater explanatory force to the cases I have been considering in this chapter. As a consequence, it renders the question of whether algorithms are responsible for deskilling the workforce superfluous. Instead, it urges us to ask how forms of algorithmic interventions are productive of new journalistic realities, and to what efect. Simply claiming that algorithms make people redundant will not do. While it seems safe to say that algorithms do something that, in some cases, may imply reducing the need for human labor, we should be wary of claims that simply end there.
What, then, do algorithms problematize? In the remainder of this chapter, I will focus on two possible answers, aware of there being no exhaustive explanation for a question like this. First, algorithms contest and transform how journalism is performed. As the interviews suggest, algorithms do not eliminate the need for human judgment and know-how in news work; they displace, redistribute, and shape new ways of being a news worker. Similarly, seeing machines as lacking instincts and, therefore, ill-suited to replace journalists and their “gut feelings” is a too simple a view. What journalists may have a “gut feeling” about expands and transforms as well. The field observations and conversations I had with staf at Omni revealed how editors in particular have developed an instinct for how the machine works. As “Clare” tellingly suggests, it is not just a mater of having an instinct for news at Omni, it is also about “developing a feeling for the algorithm” (Interview 11, March 2015). In contrast to much recent discourse on computational journalism, which hinges on the notion of “computational thinking,” the case of Omni suggests that not all “computational thinking” requires journalists to learn to think more like computer scientists. Whereas the notion of “computational thinking,” as originally conceived, refers to an approach to problem solving that draws on concepts fundamental to computer science such as abstraction, automation, and recursivity (Wing, 2006), editors at Omni do not necessarily think of their work in computational terms. Rather, they think like journalists who have learned to optimize their product and practice not just for an outside reader but also with an algorithm in mind. In contesting existing professional boundaries, the algorithm contributes to the emergence of diferent readers, diferent journalists, and, ultimately, diferent news.15
Programming the News
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