This paper argues that social media companies’ power to regulate communication in the public sphere illustrates a novel type of domination. The idea is that, since social media companies can partially dictate the terms of citizens’ political participation in the public sphere, they can arbitrarily interfere with the choices individuals make qua citizens. I contend that social media companies dominate citizens in two different ways. First, I focus on the cases in which social media companies exercise direct control over political (...) speech. They exercise quasi-public power over citizens because their regulation of speech on social media platforms implies the capacity to arbitrarily interfere with citizens’ democratic contestation in the political system. Second, companies’ algorithmic governance entails the capacity to interfere with citizens’ choices about what mode of discursive engagement they endorse in their relationships with fellow citizens. By raising the cost of deliberative engagement, companies narrow citizens’ choice menu. (shrink)

The last decade has seen rise in technologies that allow humans to send and receive intimate touch across long distances. Drawing together platform studies, digital intimacy studies, phenomenology of touch, and ethics of technology, we argue that these new haptic communication devices require specific ethical consideration of consent. The paper describes several technologies, including Kiiroo teledildonics, the Kissenger, the Apple Watch, and Hey Bracelet, highlighting how the sense of touch is used in marketing to evoke a feeling of connection within (...) the digital sphere. We then discuss the ambiguity of skin-to-skin touch and how it is further complicated in digital touch by remediation through platforms, companies, developers, manufacturers, cloud storage sites, the collection and use of data, research, satellites, and the internet. Lastly, we raise concerns about how consent of data collection and physical consent between users will be determined, draw on examples in virtual reality and sex-robotics, and ultimately arguing for further interdisciplinary research into this area. (shrink)

Scholarship on the politics of new media widely assumes that communication functions as a sufficient conceptual paradigm for critically assessing new media politics. This article argues that communication-centric analyses fail to engage the politics of information itself, limiting information only to its consequences for communication, and neglecting information as it reaches into our selves, lives, and actions beyond the confines of communication. Furthering recent new media historiography on the “information theory” of Shannon and Wiener, the article reveals both the primacy (...) of communication in midcentury information theory, and also a striking resonance between these postwar communication theories and Habermas’s more recent communicative theory of democracy. To achieve a critical perspective beyond communication, the article proposes a media genealogy of the politics of subjects as a methodology for developing an analysis of how information formats us as subjects of data. (shrink)

The payments industry – the business of transferring value through public and corporate infrastructures – is undergoing rapid transformation. New business models and regulatory environments disrupt more traditional fee-based strategies, and new entrants seek to displace legacy players by leveraging new mobile platforms and new sources of data. In this increasingly diversified industry landscape, start-ups and established players are attempting to embed payment in ‘social’ experience through novel technologies of accounting for trust. This imagination of the social, however, is being (...) materialized in gated platforms for payment, accounting, and exchange. This paper explores the ambiguous politics of such experiments, specifically those, like Bitcoin or the on-demand sharing economy, that delineate an economic imaginary of ‘just us’ – a closed and closely guarded community of peers operating under the illusion that there are no mediating institutions undergirding that community. This provokes questions about the intersection of payment and publics. Payment innovators’ attenuated understanding of the social may, we suggest, evacuate the nitty-gritty of politics. (shrink)

In information societies, operations, decisions and choices previously left to humans are increasingly delegated to algorithms, which may advise, if not decide, about how data should be interpreted and what actions should be taken as a result. More and more often, algorithms mediate social processes, business transactions, governmental decisions, and how we perceive, understand, and interact among ourselves and with the environment. Gaps between the design and operation of algorithms and our understanding of their ethical implications can have severe consequences (...) affecting individuals as well as groups and whole societies. This paper makes three contributions to clarify the ethical importance of algorithmic mediation. It provides a prescriptive map to organise the debate. It reviews the current discussion of ethical aspects of algorithms. And it assesses the available literature in order to identify areas requiring further work to develop the ethics of algorithms. (shrink)

The paper explores some normative challenges concerning the integration of Machine Learning (ML) algorithms into anticorruption in public institutions. The challenges emerge from the tensions between an approach treating ML algorithms as allies to an exclusively legalistic conception of anticorruption and an approach seeing them within an institutional ethics of office accountability. We explore two main challenges. One concerns the variable opacity of some ML algorithms, which may affect public officeholders’ capacity to account for institutional processes relying upon ML techniques. (...) The other pinpoints the risk that automating certain institutional processes may weaken officeholders’ direct engagement to take forward-looking responsibility for the working of their institution. We discuss why both challenges matter to see how ML algorithms may enhance (and not hinder) institutional answerability practices. (shrink)

Recent technological and methodological changes in farming have led to an emerging set of claims about the role of digital technology in food production. Known as precision agriculture, the integration of digital management and surveillance technologies in farming is normatively presented as a revolutionary transformation. Proponents contend that machine learning, Big Data, and automation will create more accurate, efficient, transparent, and environmentally friendly food production, staving off both food insecurity and ecological ruin. This article contributes a critique of these rhetorical (...) and discursive claims to a growing body of critical literature on precision agriculture. It argues precision agriculture is less a revolution than an evolution, an effort to shore up and intensify the conventional farming system responsible for generating many of the social and environmental problems precision agriculture is presented as solving. While precision agriculture advocates portray it as a radical, even democratic epistemological break with the past, this paper locates truth claims surrounding datafication and algorithmic control in farming within deeper historical contexts of the capitalist rationalization of production and efforts to quantify and automate physical and mental labor. Abjuring the growing cultural tendency to treat algorithmic systems as revolutionary in favor of social and historical dimensions of precision agriculture, can help re-frame the discussion about its design and use around real, socially and ecologically oriented change in farming, and so ensure that the possibilities and benefits of precision agriculture are as evenly and effectively shared as possible. (shrink)

While organizations today make extensive use of complex algorithms, the notion of algorithmic accountability remains an elusive ideal due to the opacity and fluidity of algorithms. In this article, we develop a framework for managing algorithmic accountability that highlights three interrelated dimensions: reputational concerns, engagement strategies, and discourse principles. The framework clarifies that accountability processes for algorithms are driven by reputational concerns about the epistemic setup, opacity, and outcomes of algorithms; that the way in which organizations practically engage with emergent (...) expectations about algorithms may be manipulative, adaptive, or moral; and that when accountability relationships are heavily burdened by the opacity and fluidity of complex algorithmic systems, the emphasis of engagement should shift to a rational communication process through which a continuous and tentative assessment of the development, workings, and consequences of algorithms can be achieved over time. The degree to which such engagement is, in fact, rational can be assessed based on four discourse-ethical principles of participation, comprehension, multivocality, and responsiveness. We conclude that the framework may help organizations and their environments to jointly work toward greater accountability for complex algorithms. It may further help organizations in reputational positioning surrounding accountability issues. The discourse-ethical principles introduced in this article are meant to elevate these positioning contests to extend beyond mere adaption or compliance and help guide organizations to find moral and forward-looking solutions to accountability issues. (shrink)

Algorithms have developed into somewhat of a modern myth. On the one hand, they have been depicted as powerful entities that rule, sort, govern, shape, or otherwise control our lives. On the other hand, their alleged obscurity and inscrutability make it difficult to understand what exactly is at stake. What sustains their image as powerful yet inscrutable entities? And how to think about the politics and governance of something that is so difficult to grasp? This editorial essay provides a critical (...) backdrop for the special issue, treating algorithms not only as computational artifacts but also as sensitizing devices that can help us rethink some entrenched assumptions about agency, transparency, and normativity. (shrink)

As government pressure on major technology companies builds, both firms and legislators are searching for technical solutions to difficult platform governance puzzles such as hate speech and misinformation. Automated hash-matching and predictive machine learning tools – what we define here as algorithmic moderation systems – are increasingly being deployed to conduct content moderation at scale by major platforms for user-generated content such as Facebook, YouTube and Twitter. This article provides an accessible technical primer on how algorithmic moderation works; examines some (...) of the existing automated tools used by major platforms to handle copyright infringement, terrorism and toxic speech; and identifies key political and ethical issues for these systems as the reliance on them grows. Recent events suggest that algorithmic moderation has become necessary to manage growing public expectations for increased platform responsibility, safety and security on the global stage; however, as we demonstrate, these systems remain opaque, unaccountable and poorly understood. Despite the potential promise of algorithms or ‘AI’, we show that even ‘well optimized’ moderation systems could exacerbate, rather than relieve, many existing problems with content policy as enacted by platforms for three main reasons: automated moderation threatens to further increase opacity, making a famously non-transparent set of practices even more difficult to understand or audit, further complicate outstanding issues of fairness and justice in large-scale sociotechnical systems and re-obscure the fundamentally political nature of speech decisions being executed at scale. (shrink)

As the use of AI systems continues to increase, so do concerns over their lack of fairness, legitimacy and accountability. Such harmful automated decision-making can be guarded against by ensuring AI systems are contestable by design: responsive to human intervention throughout the system lifecycle. Contestable AI by design is a small but growing field of research. However, most available knowledge requires a significant amount of translation to be applicable in practice. A proven way of conveying intermediate-level, generative design knowledge is (...) in the form of frameworks. In this article we use qualitative-interpretative methods and visual mapping techniques to extract from the literature sociotechnical features and practices that contribute to contestable AI, and synthesize these into a design framework. (shrink)

Organizations increasingly rely on algorithm-based HR decision-making to monitor their employees. This trend is reinforced by the technology industry claiming that its decision-making tools are efficient and objective, downplaying their potential biases. In our manuscript, we identify an important challenge arising from the efficiency-driven logic of algorithm-based HR decision-making, namely that it may shift the delicate balance between employees’ personal integrity and compliance more in the direction of compliance. We suggest that critical data literacy, ethical awareness, the use of participatory (...) design methods, and private regulatory regimes within civil society can help overcome these challenges. Our paper contributes to literature on workplace monitoring, critical data studies, personal integrity, and literature at the intersection between HR management and corporate responsibility. (shrink)

Artificial intelligence (AI) is increasingly relied upon by clinicians for making diagnostic and treatment decisions, playing an important role in imaging, diagnosis, risk analysis, lifestyle monitoring, and health information management. While research has identified biases in healthcare AI systems and proposed technical solutions to address these, we argue that effective solutions require human engagement. Furthermore, there is a lack of research on how to motivate the adoption of these solutions and promote investment in designing AI systems that align with values (...) such as transparency and fairness from the outset. Drawing on insights from psychological theories, we assert the need to understand the values that underlie decisions made by individuals involved in creating and deploying AI systems. We describe how this understanding can be leveraged to increase engagement with de-biasing and fairness-enhancing practices within the AI healthcare industry, ultimately leading to sustained behavioral change via autonomy-supportive communication strategies rooted in motivational and social psychology theories. In developing these pathways to engagement, we consider the norms and needs that govern the AI healthcare domain, and we evaluate incentives for maintaining the status quo against economic, legal, and social incentives for behavior change in line with transparency and fairness values. (shrink)

The growing presence of smart devices in our lives turns all of society into something largely unknown to us. The strategy of demanding transparency stems from the desire to reduce the ignorance to which this automated society seems to condemn us. An evaluation of this strategy first requires that we distinguish the different types of non-transparency. Once we reveal the limits of the transparency needed to confront these devices, the article examines the alternative strategy of explainable artificial intelligence and concludes (...) with the idea that these types of complex realities exceed individual capacities and are only comprehensible in a collective fashion. (shrink)

Information security governance has become an elusive goal and a murky concept. This paper problematizes both information security governance and the broader concept of governance. What does it mean to govern information security, or for that matter, anything? Why have information technologies proven difficult to govern? And what assurances can governance provide for the billions of people who rely on information technologies every day? Drawing together several distinct bodies of literature—including multiple strands of governance theory, actor–network theory, and scholarship on (...) sociotechnical regimes—this paper conceptualizes networked action on a spectrum from uncertain governance to governing uncertainty. I advance a twofold argument. First, I argue that networks can better govern uncertainty as they become more able not only to enroll actors in a collective agenda, but also to cut ties with those who seek to undermine that agenda. And second, I argue that the dominant conception of information security governance, which emphasizes governing uncertainty through risk management, in practice devolves to uncertain governance. This is largely because information technologies have evolved toward greater connectedness—and with it, greater vulnerability—creating a regime of insecurity. This evolution is illustrated using the history of the US government’s efforts to govern information security. (shrink)

Many actors mobilize the cognitive, legal and technical tool-box of data protection when they discuss and address controversial issues such as digital mass surveillance. Yet, critical approaches to the digital only barely explore the politics of data protection in relation to data-driven governance. Building on governmentality studies and Actor-Network-Theory, this article analyses the potential and limits of using data protection to critique the ‘digital age’. Using the conceptual tool of dispositifs, it sketches an analytics of data protection and the emergence (...) of its configuration as ‘data protection by design and by default’. This exploration reminds us that governing through data implies, first and foremost, governing digital data. (shrink)

The purpose of this paper is to examine how the shifting conceptualization of the democratizing potential of digital technology can be more comprehensively understood by bringing in science and technology studies (STS) perspectives to communication scholarship. The synthesis and discussion are aiming at providing an interdisciplinary theoretical framework for comprehensively understand the democratizing potential of digital technology, and urging researchers to be conscious of assumptions underpinning epistemological positions they take when examining the issue of democratizing potential of digital technology.,The paper (...) is a constructive literature review that synthesizes and integrates existed literature from communication and STS on the democratizing potential of digital technology. The author attempts to bridge theoretical perspectives from communication and STS by identifying core arguments and debates around key concepts and discussing potential implications of different epistemological positions.,Tracing the evolving analytical perspectives of technological determinism, the social construction of technology and actor-network theory, the author argues that researchers should be aware of their underlying epistemological assumptions embedded in relationships among users, technological systems and social factors. Analyzing the contested notion of power in the democratizing potential of digital technology from two contrasting perspectives, the author argues that researchers should recognize both the front end and the back end of digital technology in their analysis. In addition, new challenges of algorithm opacity and accountability in impacting the democratizing potential of digital technology are further discussed.,This study provides an original interdisciplinary theoretical framework by reviewing and bridging scholarship from communication and STS in examining the democratizing potential of digital technology. Adopting this interdisciplinary theoretical framework helps researchers develop a more nuanced and comprehensive understanding of the democratizing potential of digital technology. (shrink)

Much bioethical literature and policy guidances for big data analytics in biomedical research emphasize the importance of trust. It is essential that potential participants trust so they will allow their data to be used to further research. However, comparatively, little guidance is offered as to what trustworthy oversight mechanisms are, or how policy should support them, as data are collected, shared, and used. Generally, “trust” is not characterized well enough, or meaningfully enough, for the term to be systematically applied in (...) policy development. Yet points made in the philosophical literature on trust can help. They allow us, not only to better distinguish the different ways the term “trust” may be interpreted, but also to better determine how different approaches to trust can align with policy and governance—in what ways they may relate to key bioethical concepts and related laws, and in what ways they can help to balance individual and group interests in data sharing. This article draws from the philosophical literature on trust to identify a relationship among consent, trust, and justice. Specifically, parallels are drawn between “character-trustworthiness” and “natural justice,” a set of widely held legal safeguards intended to ensure decision-makers follow a pattern of procedural fairness which protects the rights of the individual and thereby maintains public confidence in the decision-making process. Relevance to traditional bioethical principles, established laws, and consent procedures are addressed throughout. In conclusion, policy actions are suggested. (shrink)