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)

A theoretical physicist and feminist theorist, Karen Barad elaborates her theory of agential realism, a schema that is at once a new epistemology, ontology, and ethics.

Web-based platforms play an increasingly important role in managing and sharing research data of all types and sizes. This article presents a case study of the data storage, sharing, and management platform Figshare. We argue that such platforms are displacing and reconfiguring the infrastructure of norms, technologies, and institutions that underlies traditional scholarly communication. Using a theoretical framework that combines infrastructure studies with platform studies, we show that Figshare leverages the platform logic of core and complementary components to re-integrate a (...) presently splintered scholarly infrastructure. By means of this logic, platforms may provide the path to bring data inside a scholarly communication system still optimized mainly for text publications. Yet the platform strategy also risks turning over critical scientific functions to private firms whose longevity, openness, and corporate goals remain uncertain. It may amplify the existing trend of splintering infrastructures, with attendant effects on equity of service. (shrink)

It has become increasingly common to talk about “digital traces”. The idea that we leak, drop and leave traces wherever we go has given rise to a culture of traceability, and this culture of traceability, I argue, is intimately entangled with a socio-economics of data disposability and recycling. While the culture of traceability has often been theorised in terms of, and in relation to, privacy, I offer another approach, framing digital traces instead as a question of waste. This perspective, I (...) argue, allows us to connect to, extend and nuance existing discussions of digital traces. It shows us that data traces raise questions about not only how data capitalism tracks individual and multiple data behaviours, but also how it links to social and environmental toxicities in the form of abuse and environmental pollution, which follow gendered and colonial structures of violence. (shrink)

Data science is not simply a method but an organising idea. Commitment to the new paradigm overrides concerns caused by collateral damage, and only a counterculture can constitute an effective critique. Understanding data science requires an appreciation of what algorithms actually do; in particular, how machine learning learns. The resulting ‘insight through opacity’ drives the observable problems of algorithmic discrimination and the evasion of due process. But attempts to stem the tide have not grasped the nature of data science as (...) both metaphysical and machinic. Data science strongly echoes the neoplatonism that informed the early science of Copernicus and Galileo. It appears to reveal a hidden mathematical order in the world that is superior to our direct experience. The new symmetry of these orderings is more compelling than the actual results. Data science does not only make possible a new way of knowing but acts directly on it; by converting predictions to pre-emptions, it becomes a machinic metaphysics. The people enrolled in this apparatus risk an abstraction of accountability and the production of ‘thoughtlessness’. Susceptibility to data science can be contested through critiques of science, especially standpoint theory, which opposes the ‘view from nowhere’ without abandoning the empirical methods. But a counterculture of data science must be material as well as discursive. Karen Barad’s idea of agential realism can reconfigure data science to produce both non-dualistic philosophy and participatory agency. An example of relevant praxis points to the real possibility of ‘machine learning for the people’. (shrink)

The increasing pervasiveness of datafication across social life is significantly challenging the scope and meanings of visibility. How do new modes of data capture compel us to rethink the notion of visibility, no longer understood as an ocular-based perceptual field, but as a multifaceted site of power? Focusing in particular on technologies of algorithmic recognition, the article argues that in order to understand the broad stakes of visibility under algorithmic life, the intersection between algorithmic recognition and the notion of social (...) recognizability needs to be further theorized. In dialogue with the work of Sondra Perry, and drawing on contributions from feminist and critical race theories, the article revisits theoretical debates on racialized visibility within photography and film to show how racializing processes are inscribed in digital and algorithmic technologies. In reading through these debates, the article suggests that visibility, as a racial formation, is always already subjected to an algorithmic logic. Through the analysis of Sondra Perry’s work, the article sketches out a political ontology of the image premised on the intersection between computation and the markings of the flesh as a possible way to think through the stakes of visibility under algorithmic life. (shrink)