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.
Social media have amplified and accelerated the ethical challenges that communicators, professional and otherwise, face worldwide. The work of ethical journalism, with a priority of truthful communication, offers a paradigm case for examining the broader challenges in the global social media network. The evolution of digital technologies and the attendant expansion of the communication network pose ethical difficulties for journalists connected with increased speed and volume of information, a diminished place in the network, and the cross-border nature of information flow. These challenges are exacerbated by intentional manipulation of social media, human-run or automated, in many countries including internal suppression by authoritarian regimes and foreign influence operations to spread misinformation. In addition, structural characteristics of social media platforms’ filtering and recommending algorithms pose ethical challenges for journalism and its role in fostering public discourse on social and political issues, although a number of studies have called aspects of the “filter bubble” hypothesis into question. Research in multiple countries, mostly in North America and Europe, has examined social media practices in journalism, including two issues central to social media ethics—verification and transparency—but ethical implications have seldom been discussed explicitly in the context of ethical theory. Since the 1980s and 1990s, scholarship focused on normative theorizing in relation to journalism has matured and become more multicultural and global. Scholars have articulated a number of ethical frameworks that could deepen analysis of the challenges of social media in the practice of journalism. However, the explicit implications of these frameworks for social media have largely gone unaddressed. A large topic of discussion in media ethics theory has been the possibility of universal or common principles globally, including a broadening of discussion of moral universals or common ground in media ethics beyond Western perspectives that have historically dominated the scholarship. In order to advance media ethics scholarship in the 21st-century environment of globally networked communication, in which journalists work among a host of other actors (well-intentioned, ill-intentioned, and automated), it is important for researchers to apply existing media ethics frameworks to social media practices. This application needs to address the challenges that social media create when crossing cultures, the common difficulties they pose worldwide for journalistic verification practices, and the responsibility of journalists for countering misinformation from malicious actors. It is also important to the further development of media ethics scholarship that future normative theorizing in the field—whether developing new frameworks or redeveloping current ones—consider journalistic responsibilities in relation to social media in the context of both the human and nonhuman actors in the communication network. The developing scholarly literature on the ethics of algorithms bears further attention from media ethics scholars for the ways it may provide perspectives that are complementary to existing media ethics frameworks that have focused on human actors and organizations.
Automated journalism—the use of algorithms to translate data into narrative news content—is enabling all manner of outlets to increase efficiency while scaling up their reporting in areas as diverse as financial earnings and professional baseball. With these technological advancements, however, come serious risks. Algorithms are not good at interpreting or contextualizing complex information, and they are subject to biases and errors that ultimately could produce content that is misleading or false, even libelous. It is imperative, then, to examine how libel law might apply to automated news content that harms the reputation of a person or an organization. Conducting that examination from the perspective of U.S. law, because of its uniquely expansive constitutional protections in the area of libel, it appears that the First Amendment would cover algorithmic speech—meaning that the First Amendment’s full supply of tools and principles, and presumptions would apply to determine if particular automated news content would be protected. In the area of libel, the most significant issues come under the plaintiff’s burden to prove that the libelous content was published by the defendant (with a focus on whether automated journalism would qualify for immunity available to providers of interactive computer services) and that the content was published through the defendant’s fault (with a focus on whether an algorithm could behave with the actual malice or negligence usually required to satisfy this inquiry). There is also a significant issue under the opinion defense, which provides broad constitutional protection for statements of opinion (with a focus on whether an algorithm itself is capable of having beliefs or ideas, which generally inform an opinion).
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.
Ben De Smet
The relevance of music in lesbian, gay, bisexual, transgender, queer, and other sexually nonnormative (LGBTQ+) lives and identities has been extensively established and researched. Studies have focused on queer performances, fandom, night life, and other aspects of music to examine the intimate, social, and political relations between music and LGBTQ+ identities. In a time where music culture is produced, distributed, and consumed increasingly in digital spaces, relations between music and LGBTQ+ identities are meaningfully informed by these spaces. As this is a relatively recent development and offline music practices remain profoundly meaningful and relevant, the amount of research on queer digital music practices remains modest. However, a rich body of literature in the fields of popular music studies, queer studies, and new media studies provides an array of inspiring angles and perspectives to shed light on these matters, and this literature can be situated and critically linked. For over half a century, popular music studies have directed their attention to the relations between the social and the musical. Under the impulse of feminist studies, gender identities soon became a prominent focus within popular music studies, and, driven by LGBTQ+ studies, (non-normative) sexual identities soon followed. As popular music studies developed a rich theoretical basis, and feminist and queer studies evolved over the years into more intersectional and queer directions, popular music studies focusing on gender and/or sexuality gradually stepped away from their initial somewhat rigid, binary perspectives in favor of more open, dynamic, and queer perspectives. Following a similar path, early new media studies struggled to avoid simplistic, naïve, or gloomy deterministic analyses of the Internet and new media. As the field evolved, alongside the technologies that form its focus, a more nuanced, mutual, and agency-based approach emerged. Here, too, scholars have introduced queer perspectives and have applied them to research a range of LGBTQ+-related digital phenomena. Today, popular music, sexual identities, and new media have become meaningful aspects of social life, and much more remains to be explored, in particular on the intersection of these fields. A diverse array of queer fan practices, music video practices, and music streaming practices are waiting to be examined. The theory and the tools are there.
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.