We are currently witnessing a sharp rise in the use of algorithmic decision-making tools. In these instances, a new wave of policy concerns is set forth. This article strives to map out these issues, separating the wheat from the chaff. It aims to provide policy makers and scholars with a comprehensive framework for approaching these thorny issues in their various capacities. To achieve this objective, this article focuses its attention on a general analytical framework, which will be applied to a (...) specific subset of the overall discussion. The analytical framework will reduce the discussion to two dimensions, every one of which addressing two central elements. These four factors call for a distinct discussion, which is at times absent in the existing literature. The two dimensions are the specific and novel problems the process assumedly generates and the specific attributes which exacerbate them. While the problems are articulated in a variety of ways, they most likely could be reduced to two broad categories: efficiency and fairness-based concerns. In the context of this discussion, such problems are usually linked to two salient attributes the algorithmic processes feature—its opaque and automated nature. (shrink)

According to Ernst Cassirer, the transition from the concept of substance to that of mathematical function as a guide of knowledge coincided with the end of ancient and the beginning of modern theoretical thought. In the first part of this article we argue that a similar transition has also taken place in the practical sphere, where mathematical function occurs in one of its specific forms, which is that of the algorithm concept. In the second part we argue that with the (...) rise of modernity the idea of substance and the related concepts of category and classification, which are deeply embedded in western culture, have not been totally supplanted by that of function. The intertwining of the concepts of substance and function has generated contradictory hybrids. These hybrids are used as a key for the understanding of the different repercussions of algorithmic logic on society in terms of social integration. (shrink)

This article responds to recent debates in critical algorithm studies about the significance of the term “algorithm.” Where some have suggested that critical scholars should align their use of the term with its common definition in professional computer science, I argue that we should instead approach algorithms as “multiples”—unstable objects that are enacted through the varied practices that people use to engage with them, including the practices of “outsider” researchers. This approach builds on the work of Laura Devendorf, Elizabeth Goodman, (...) and Annemarie Mol. Different ways of enacting algorithms foreground certain issues while occluding others: computer scientists enact algorithms as conceptual objects indifferent to implementation details, while calls for accountability enact algorithms as closed boxes to be opened. I propose that critical researchers might seek to enact algorithms ethnographically, seeing them as heterogeneous and diffuse sociotechnical systems, rather than rigidly constrained and procedural formulas. To do so, I suggest thinking of algorithms not “in” culture, as the event occasioning this essay was titled, but “as” culture: part of broad patterns of meaning and practice that can be engaged with empirically. I offer a set of practical tactics for the ethnographic enactment of algorithmic systems, which do not depend on pinning down a singular “algorithm” or achieving “access,” but which rather work from the partial and mobile position of an outsider. (shrink)

We argue that some algorithms are value-laden, and that two or more persons who accept different value-judgments may have a rational reason to design such algorithms differently. We exemplify our claim by discussing a set of algorithms used in medical image analysis: In these algorithms it is often necessary to set certain thresholds for whether e.g. a cell should count as diseased or not, and the chosen threshold will partly depend on the software designer’s preference between avoiding false positives and (...) false negatives. This preference ultimately depends on a number of value-judgments. In the last section of the paper we discuss some general principles for dealing with ethical issues in algorithm-design. (shrink)

Self-driving cars hold out the promise of being safer than manually driven cars. Yet they cannot be a 100 % safe. Collisions are sometimes unavoidable. So self-driving cars need to be programmed for how they should respond to scenarios where collisions are highly likely or unavoidable. The accident-scenarios self-driving cars might face have recently been likened to the key examples and dilemmas associated with the trolley problem. In this article, we critically examine this tempting analogy. We identify three important ways (...) in which the ethics of accident-algorithms for self-driving cars and the philosophy of the trolley problem differ from each other. These concern: the basic decision-making situation faced by those who decide how self-driving cars should be programmed to deal with accidents; moral and legal responsibility; and decision-making in the face of risks and uncertainty. In discussing these three areas of disanalogy, we isolate and identify a number of basic issues and complexities that arise within the ethics of the programming of self-driving cars. (shrink)

This paper explores how accountability might make otherwise obscure and inaccessible algorithms available for governance. The potential import and difficulty of accountability is made clear in the compelling narrative reproduced across recent popular and academic reports. Through this narrative we are told that algorithms trap us and control our lives, undermine our privacy, have power and an independent agential impact, at the same time as being inaccessible, reducing our opportunities for critical engagement. The paper suggests that STS sensibilities can provide (...) a basis for scrutinizing the terms of the compelling narrative, disturbing the notion that algorithms have a single, essential characteristic and a predictable power or agency. In place of taking for granted the terms of the compelling narrative, ethnomethodological work on sense-making accounts is drawn together with more conventional approaches to accountability focused on openness and transparency. The paper uses empirical material from a study of the development of an “ethical,” “smart” algorithmic videosurveillance system. The paper introduces the “ethical” algorithmic surveillance system, the approach to accountability developed, and some of the challenges of attempting algorithmic accountability in action. The paper concludes with reflections on future questions of algorithms and accountability. (shrink)

The process of translation has both an excluding and including character. The analysis of actor networks, the process of mobilizing alliances, and constructing networks is a common and worthwhile focus. However, the simultaneous betrayals, dissidences, and controversies are often only implied in network construction stories. We aim to nuance the construction aspect of actor–network theory by shining the analytical searchlight elsewhere, where the theoretical tools of ANT have not yet systematically ventured. We argue that we need to understand every process (...) of translation in relation to its simultaneous process of treason, and to add antonyms for Callon’s problematization, intressement, enrollment, and mobilization. This enables us to describe powerlessness not as a state but as a process. Our case focuses on the network building around measures for disabled people in the construction of the Athens Metro, during the period 1991-1993. The discussion highlights the efforts of disability organizations to intervene in the initial construction works of the metro project and the simultaneous actions of the Greek government to exclude disability organizations from the design process and to disrupt the accessibility-metro actor network. (shrink)

This article examines how the availability of Big Data, coupled with new data analytics, challenges established epistemologies across the sciences, social sciences and humanities, and assesses the extent to which they are engendering paradigm shifts across multiple disciplines. In particular, it critically explores new forms of empiricism that declare ‘the end of theory’, the creation of data-driven rather than knowledge-driven science, and the development of digital humanities and computational social sciences that propose radically different ways to make sense of culture, (...) history, economy and society. It is argued that: Big Data and new data analytics are disruptive innovations which are reconfiguring in many instances how research is conducted; and there is an urgent need for wider critical reflection within the academy on the epistemological implications of the unfolding data revolution, a task that has barely begun to be tackled despite the rapid changes in research practices presently taking place. After critically reviewing emerging epistemological positions, it is contended that a potentially fruitful approach would be the development of a situated, reflexive and contextually nuanced epistemology. (shrink)

Scholars and practitioners across domains are increasingly concerned with algorithmic transparency and opacity, interrogating the values and assumptions embedded in automated, black-boxed systems, particularly in user-generated content platforms. I report from an ethnography of infrastructure in Wikipedia to discuss an often understudied aspect of this topic: the local, contextual, learned expertise involved in participating in a highly automated social–technical environment. Today, the organizational culture of Wikipedia is deeply intertwined with various data-driven algorithmic systems, which Wikipedians rely on to help manage (...) and govern the “anyone can edit” encyclopedia at a massive scale. These bots, scripts, tools, plugins, and dashboards make Wikipedia more efficient for those who know how to work with them, but like all organizational culture, newcomers must learn them if they want to fully participate. I illustrate how cultural and organizational expertise is enacted around algorithmic agents by discussing two autoethnographic vignettes, which relate my personal experience as a veteran in Wikipedia. I present thick descriptions of how governance and gatekeeping practices are articulated through and in alignment with these automated infrastructures. Over the past 15 years, Wikipedian veterans and administrators have made specific decisions to support administrative and editorial workflows with automation in particular ways and not others. I use these cases of Wikipedia’s bot-supported bureaucracy to discuss several issues in the fields of critical algorithms studies; critical data studies; and fairness, accountability, and transparency in machine learning—most principally arguing that scholarship and practice must go beyond trying to “open up the black box” of such systems and also examine sociocultural processes like newcomer socialization. (shrink)

Algorithms, once obscure objects of technical art, have lately been subject to considerable popular and scholarly scrutiny. What does it mean to adopt the algorithm as an object of analytic attention? What is in view, and out of view, when we focus on the algorithm? Using Niklaus Wirth's 1975 formulation that “algorithms + data structures = programs” as a launching-off point, this paper examines how an algorithmic lens shapes the way in which we might inquire into contemporary digital culture.

This article considers the issue of opacity as a problem for socially consequential mechanisms of classification and ranking, such as spam filters, credit card fraud detection, search engines, news trends, market segmentation and advertising, insurance or loan qualification, and credit scoring. These mechanisms of classification all frequently rely on computational algorithms, and in many cases on machine learning algorithms to do this work. In this article, I draw a distinction between three forms of opacity: opacity as intentional corporate or state (...) secrecy, opacity as technical illiteracy, and an opacity that arises from the characteristics of machine learning algorithms and the scale required to apply them usefully. The analysis in this article gets inside the algorithms themselves. I cite existing literatures in computer science, known industry practices, and do some testing and manipulation of code as a form of lightweight code audit. I argue that recognizing the distinct forms of opacity that may be coming into play in a given application is a key to determining which of a variety of technical and non-technical solutions could help to prevent harm. (shrink)

The commentary raises political questions about the ways in which data has been constituted as an object vested with certain powers, influence, and rationalities. We place the emergence and transformation of professional practices such as ‘data science’, ‘data journalism’, ‘data brokerage’, ‘data mining’, ‘data storage’, and ‘data analysis’ as part of the reconfiguration of a series of fields of power and knowledge in the public and private accumulation of data. Data politics asks questions about the ways in which data has (...) become such an object of power and explores how to critically intervene in its deployment as an object of knowledge. It is concerned with the conditions of possibility of data that involve things, language, and people that together create new worlds. We define ‘data politics’ as both the articulation of political questions about these worlds and the ways in which they provoke subjects to govern themselves and others by making rights claims. We contend that without understanding these conditions of possibility – of worlds, subjects and rights – it would be difficult to intervene in or shape data politics if by that it is meant the transformation of data subjects into data citizens. (shrink)

In this book Bruno Latour brings together these different approaches to provide a lively and challenging analysis of science, demonstrating how social context..

In controversies about technology and society, there is no idea more pro vocative than the notion that technical things have political qualities. At issue is the claim that the machines, structures, and systems of modern material culture can be accurately judged not only for their contributions of efficiency and pro-ductivity, not merely for their positive and negative environmental side effects, but also for the ways in which they can embody specific forms of power and authority. Since ideas of this kind (...) have a persistent and troubling presence in discussions about the meaning of technology, they deserve explicit attention... (shrink)