Although journalism is often associated with human beings, non-human entities also play an important role in shaping journalism — especially today. We can refer to the material, non-human technologies that make a difference to how news is produced and disseminated as technological actants within the space of journalism. Examples of technological actants in journalism include word processing applications (used to produce news stories), search engine algorithms (used to find news), and smartphones (used to consume news).
While that definition may seem quite abstract, at its heart is a simple truth: Nearly all of today’s journalistic work is shaped in some part by technology. This isn’t a recent development, though. Technological actants have played a major role in the historical development of journalism. For example, the development of the printing press made the mass distribution of journalism theoretically possible, even as it restricted the formats that journalistic products could take on due to the technology’s limitations. Another technological actant, the telegraph, enabled newswire services like The Associated Press to develop and allowed reporters to transmit their reports relatively quickly from afar. Conversely, the proliferation of the telephone allowed more reporting to be done from within the newsroom since reporters could just call their sources instead of having to meet them in person.
Technological actants are important because they both enable, restrict, and shape different forms of journalism in both visible and invisible ways, and they very much impact the social actors (human beings) who interact with technology. Moreover, although technological actants are often described as neutral entities — after all, they’re machines presumably acting in predictable ways — technological actants are very much shaped by the social actors who create them.
In the aforementioned examples of the printing press, the telegraph, and the telephone, technological actants shaped the behaviors of human actors by creating new possibilities and restricting others.
For a more detailed example, consider the following scenario: A news organization uses a content management system to facilitate its workflow, and all reporters at that organization must submit their stories through that system. When a reporter sees that a star athlete announced, via a video on Instagram, that they’re signing a new contract, the reporter quickly writes a news brief for the website and plans to embed the Instagram post so readers may see the athlete’s excitement with their own eyes. However, it turns out that the particular content management system used by the news organization does not have the technical capacity to embed social media posts in a story — perhaps the person who created the system just never thought to add the functionality. Thus, the reporter must either describe the video through the text in the story or send the reader away from the story through a link to the post.
In that example, the technological actant (the content management system) shaped a particular human choice by making it impossible for the reporter to pursue their preferred course of action, which was to embed the post with the video. Instead, it provided the reporter with a limited set of alternative courses of action that the system could accommodate: linking out to Instagram or presenting a written description of the video. Over time, that system may end up discouraging the use of social media in reporting — such as embedding posts that illustrate a point made by the reporter or that include reactions by other people — and thus impact the way the reporters working for that organization relate with their sources and audiences.
It is crucial to note, though, that just because a technological actant is designed to promote a particular way of doing things does not mean that its users will use them in that way — or use that actant at all. Many innovations in journalism are not actually adopted by journalists. And, when they are, those actants are often adopted in ways that allow journalists to continue doing the things they are used to doing, and in the ways they are used to doing them. In that sense, technological actants can take on the values, operational logics, and biases of their users when they are put to particular uses. For example, when mainstream journalistic outlets began adopting the then-novel blogging format in new sections of their websites, its journalists tended to use the new functionalities in very traditional ways — such as by linking primarily to mainstream organizations, limiting audience participation, and using the same journalistic writing style they were already used to.
The relationship between technological actants and human actors is not a one-way street, though. That is, human actors also shape technological actants.
It is easy to think of technological actants as neutral tools due to their mechanical nature. However, they are created and refined by human actors, and thus take on certain cultural norms, politics, and ideological values. These may be intentionally inserted into the technological actant by those humans in order to advance certain commercial, technical, or journalistic objectives. They may also be added unintentionally as a result of the human creator’s biases and ways of thinking.
To illustrate this, consider a scenario wherein a freelance coder is contracted to create a web tool that helps journalists at a news organization quickly produce interactive data visualizations. The coder intuits that most journalists at that organization are not tech-savvy, and thus chooses to limit the range of customization options so as to not overwhelm the journalists. The coder similarly intuits that many of the journalists lack a design background, and thus implements a feature that will quickly inspect the dataset and recommend the chart form that best illustrates the data. Finally, the coder is told to optimize the tool for “a mobile-first experience,” and the coder thus further restricts the customization options to ensure that the journalist can only create visualizations that look good on a smartphone.
In that scenario, the coder — a social actor — has shaped the tool — a technological actant — in different ways. First, their biases and perceptions lead them to promote a restrictive logic of simplicity within the tool. Second, the coder’s background shapes the tool’s suggestion for which kind of chart to use for a given dataset, and those suggestions may be more oriented to scientific visualizations than journalistic ones if the coder’s background lies outside of journalism. Third, the economic logic of the news organization instructs the coder to optimize the tool’s outputs for smartphones; the coder, in turn, programs the tool accordingly.
As these examples show, not only do technological actants take on the biases and logics of their users when they are put to use but they are also infused with the logics and biases of their creators as they are built.
By acting upon one another, technological actants are constantly shaping human actors and human actors are constantly shaping technological actants. This is called mutual shaping and it operates in an iterative manner.
Returning to our data visualization tool scenario, the coder’s choice to have the software recommend pie charts when presented with data about proportions may result in that visual format becoming a popular form in data visualizations created by that organization. However, one of the journalists may find that they want the doughnut chart form (an alternative to pie charts) to be an option, and eventually convince the coder to include that functionality. Over time, the journalist’s peers may try that option and come to prefer it. They thus convince the coder to set the doughnut chart to become the default recommendation, which in turn socializes future hires in the organization to consider the doughnut chart first — even as they continue to stay within that general visual aesthetic initially proposed by the non-journalist coder.
As the scenario now shows, a human actor shaped a technological actant, which shaped the behaviors of other human actors, who in turn used the actant in particular ways and had the coder reshape the actant, which had subsequent impacts on yet more human actors. As such, they were influencing one another over time, with the technological actant taking on the ideas, biases, and logics of different people — even as it influenced those very same people in important ways. While this is a fairly simple example, you can imagine similar mutual shaping processes for more complex technologies (e.g., search algorithms, communication platforms, virtual assistants).
Given that technological actants act and are acted upon human actors (as well as other technological actants), it is unsurprising that those dynamics introduce fluid power relationships. Those relationships are oftentimes asymmetric, meaning that a technological actant may ultimately have more power over the human actor — and vice versa.
For example, Google’s search algorithms may play a major role in determining how many clicks a reporter’s story gets, and the reporter may thus try to optimize the language in their story to get more attention from Google. (This is called search engine optimization, or SEO.) However, Google’s algorithms are hardly influenced by that individual journalist, or perhaps even the journalism industry as a whole. Thus, that algorithm has more power over the reporter than the reporter has over the algorithm, as the reporter must adapt to remain relevant but not the other way around.
Such power relationships are particularly important to examine as particular technologies become more and less central to the profession and to everyday life, and as certain kinds of human actors become more and less central to journalism.
Technological actants refer to material, non-human technologies that make a difference to how journalism is produced and disseminated.
Technological actants shape human actors by structuring their behaviors, both in terms of making it easier to do some things and impossible to do others.
Technological actants are not neutral. They are developed by humans and take on those humans’ values, biases, and preferred ways of accomplishing tasks. Moreover, they are sometimes intentionally employed within organizations (including newsrooms) to address different commercial, technical, and/or journalistic imperatives.
The mutual shaping of human actors and technological actants creates power relationships that are fluid and dynamic, and are of consequence to the development of journalism.