Internet-based services that build on automated algorithmic selection processes, for example search engines, computational advertising, and recommender systems, are booming and platform companies that provide such services are among the most valuable corporations worldwide. Algorithms on and beyond the Internet are increasingly influencing, aiding, or replacing human decision-making in many life domains. Their far-reaching, multifaceted economic and social impact, which results from the governance by algorithms, is widely acknowledged. However, suitable policy reactions, that is, the governance of algorithms, are the subject of controversy in academia, politics, industry, and civil society. This governance by and of algorithms is to be understood in the wider context of current technical and societal change, and in connection with other emerging trends. In particular, expanding algorithmizing of life domains is closely interrelated with and dependent on growing datafication and big data on the one hand, and rising automation and artificial intelligence in modern, digitized societies on the other. Consequently, the assessments and debates of these central developmental trends in digitized societies overlap extensively. Research on the governance by and of algorithms is highly interdisciplinary. Communication studies contributes to the formation of so-called “critical algorithms studies” with its wide set of sub-fields and approaches and by applying qualitative and quantitative methods. Its contributions focus both on the impact of algorithmic systems on traditional media, journalism, and the public sphere, and also cover effect analyses and risk assessments of algorithmic-selection applications in many domains of everyday life. The latter includes the whole range of public and private governance options to counter or reduce these risks or to safeguard ethical standards and human rights, including communication rights in a digital age.
Michael Latzer and Natascha Just
Algorithms today influence, to some extent, nearly every aspect of journalism, from the initial stages of news production to the latter stages of news consumption. While they may be seen as technical objects with certain material characteristics, algorithms are also social constructions that carry multiple meanings. Algorithms are neither valueless nor do they exist in isolation; they are part of algorithmic assemblages that include myriad actors, actants, activities, and audiences. As such, they are imbued with logics that are only sometimes reflective of journalism’s. Algorithms have played an active role in a broader quantitative turn within journalism that began in the 1970s but rapidly accelerated after the turn of the century. They are already used to produce hundreds of thousands of articles per year through automated journalism and are employed throughout the many stages of human-driven newswork. Additionally, algorithms enable audience analytics, which are used to quantify audiences into measures that are increasingly influencing news production through the abstractions they promote. Traditional theoretical models of newswork like gatekeeping are thus being challenged by the proliferation of algorithms. A trend toward algorithmically enabled personalization is also leading to the development of responsive distribution and curated flows. This is resulting in a marked shift from journalism’s traditional focus on shared importance and toward highly individualized experiences, which has implications for the formation of publics and media effects. In particular, the proliferation of algorithms has been linked to the development of filter bubbles and evolution of algorithmic reality construction that can be gamed to spread misinformation and disinformation. Scholars have also observed important challenges associated with the study of algorithms and in particular the opaque nature of key algorithms that govern a range of news-related processes. The combination of a lack of transparency with the complexity and adaptability of algorithmic mechanisms and systems makes it difficult to promote algorithmic accountability and to evaluate them vis-à-vis ethical models. There is, currently, no widely accepted code of ethics for the use of algorithms in journalism. Finally, while the body of literature at the intersection of algorithms and journalism has grown rapidly in recent years, it is still in its infancy. As such, there are still ample opportunities for typologizing algorithmic phenomena, tracing the lineage of algorithmic processes and the roles of digital intermediaries within systems, and empirically evaluating the prevalence of particular kinds of algorithms in journalistic spaces and the effects they exert on newswork.
Allison J. Steinke and Valerie Belair-Gagnon
In the early 2000s, along with the emergence of social media in journalism, mobile chat applications began to gain significant footing in journalistic work. Interdisciplinary research, particularly in journalism studies, has started to look at apps in journalistic work from producer and user perspectives. Still in its infancy, scholarly research on apps and journalistic work reflects larger trends explored in digital journalism studies, while expanding the understanding of mobile news.
The digital is now an integral part of everyday cultural practices globally. This ubiquity makes studying digital culture both more complex and divergent. Much of the literature on digital culture argues that it is increasingly informed by playful and ludified characteristics. In this phenomenon, there has been a rise of innovative and playful methods to explore identity politics and place-making in an age of datafication. At the core of the interdisciplinary debates underpinning the understanding of digital culture is the ways in which STEM (Science, Technology, Engineering and Mathematics) and HASS (Humanities, Arts and Social Science) approaches have played out in, and through, algorithms and datafication (e.g., the rise of small data [ethnography] to counteract big data). As digital culture becomes all-encompassing, data and its politics become central. To understand digital culture requires us to acknowledge that datafication and algorithmic cultures are now commonplace—that is, where data penetrate, invade, and analyze our daily lives, causing anxiety and seen as potentially inaccurate statistical captures. Alongside the use of big data, the quantified self (QS) movement is amplifying the need to think more about how our data stories are being told and who is doing the telling. Tensions and paradoxes ensure—power and powerless; tactic and strategic; identity and anonymity; statistics and practices; and big data and little data. The ubiquity of digital culture is explored through the lens of play and playful resistance. In the face of algorithms and datafication, the contestation around playing with data takes on important features. In sum, play becomes a series of methods or modes of critique for agency and autonomy. Playfully acting against data as a form of resistance is a key method used by artists, designers, and creative practitioners working in the digital realm, and they are not easily defined.