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)

In this incisive book, Michel de Certeau considers the uses to which social representation and modes of social behavior are put by individuals and groups, describing the tactics available to the common man for reclaiming his own autonomy from the all-pervasive forces of commerce, politics, and culture. In exploring the public meaning of ingeniously defended private meanings, de Certeau draws brilliantly on an immense theoretical literature to speak of an apposite use of imaginative literature.

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)

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)

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.

The Body Multiple is an extraordinary ethnography of an ordinary disease. Drawing on fieldwork in a Dutch university hospital, Annemarie Mol looks at the day-to-day diagnosis and treatment of atherosclerosis. A patient information leaflet might describe atherosclerosis as the gradual obstruction of the arteries, but in hospital practice this one medical condition appears to be many other things. From one moment, place, apparatus, specialty, or treatment, to the next, a slightly different “atherosclerosis” is being discussed, measured, observed, or stripped away. (...) This multiplicity does not imply fragmentation; instead, the disease is made to cohere through a range of tactics including transporting forms and files, making images, holding case conferences, and conducting doctor-patient conversations. The Body Multiple juxtaposes two distinct texts. Alongside Mol’s analysis of her ethnographic material—interviews with doctors and patients and observations of medical examinations, consultations, and operations—runs a parallel text in which she reflects on the relevant literature. Mol draws on medical anthropology, sociology, feminist theory, philosophy, and science and technology studies to reframe such issues as the disease-illness distinction, subject-object relations, boundaries, difference, situatedness, and ontology. In dialogue with one another, Mol’s two texts meditate on the multiplicity of reality-in-practice. Presenting philosophical reflections on the body and medical practice through vivid storytelling, The Body Multiple will be important to those in medical anthropology, philosophy, and the social study of science, technology, and medicine. (shrink)

The introductory chapter, entitled 'The Subject, Method and Scope of this Enquiry,' details how anthropology is to be pursued as a science and advocates the method of participant observation.

The demarcation of science from other intellectual activities-long an analytic problem for philosophers and sociologists-is here examined as a practical problem for scientists. Construction of a boundary between science and varieties of non-science is useful for scientists' pursuit of professional goals: acquisition of intellectual authority and career opportunities; denial of these resources to "pseudoscientists"; and protection of the autonomy of scientific research from political interference. "Boundary-work" describes an ideological style found in scientists' attempts to create a public image for science (...) by contrasting it favorably to non-scientific intellectual or technical activities. Alternative sets of characteristics available for ideological attribution to science reflect ambivalences or strains within the institution: science can be made to look empirical or theoretical, pure or applied. However, selection of one or another description depends on which characteristics best achieve the demarcation in a way that justifies scientists' claims to authority or resources. Thus, "science" is no single thing: its boundaries are drawn and redrawn inflexible, historically changing and sometimes ambiguous ways. (shrink)