Recent Writing

This chapter interrogates the historical, infrastructural, and epistemic contexts that shaped the establishment of Sweden’s Register of Congenital Malformations in 1964. Instituted in response to the global thalidomide catastrophe, the register emerged with a dual mandate: to detect emergent patterns and upticks in congenital malformations, and to act as a sentinel system for fetal damage. Placing the register within the broader international shift toward pharmaceutical oversight and standardized registries, this chapter underscores the situated nature of its creation. It probes into the classification problems posed by congenital malformations, showing how difficult it is to incorporate such anomalies into the dominant grid of medical classification. In a medical world fixated on standardization, key actors such as Bengt Källén devised novel mechanisms to grapple with the elusive nature of congenital malformations. By foregrounding the complex interplay between surveillance, standardization, and the unknown in medical practice, this chapter attends to some of the inherent contradictions in medical knowledge production.

This paper suggests that STS needs to start attending to what I dub ontological overflows. My argument is that the focus on construction and enactment stories in STS has led to us taking over the matters of concern of our interlocutors. Our informants' concerns and objects, becoming our concerns and objects. I argue that we have taken for granted which objects should be attended to, cared for, and analyzed. Thus, our theories and methods have constituted a particular blindness to those objects that our informants do not care for—the objects at the edges of the network, the smooth rhizomatic spaces, the blank figures, the neglected things, the undiscovered continents, the plasma. The paper thus joins in the ongoing discussion about the ontological politics of invisibility, partial knowledge, and fractionality, and asks how STS can attend to the making of the absent, weak, and invisible. What would happen if we start paying attention to these ontological overflows in practice? By tracing how multiple absences are produced, the paper shows the usefulness of caring for the othered objects, of following the making of alterity and otherness. The argument is that the tracing of ontological overflows opens up for understanding how tangential objects are dis-assembled, and consequently for tracing how absence, alterity, and otherness are made in practice.

The sociological study of knowledge infrastructures and classification has traditionally focused on the politics and practices of classifying things or people. However, actors' work to escape dominant infrastructures and pre-established classification systems has received little attention. In response to this, this article argues that it is crucial to analyze, not only the practices and politics of classification, but also actors' work to escape dominant classification systems. The article has two aims: First, to make a theoretical contribution to the study of classification by proposing to pay analytical attention to practices of escaping classification, what the article dubs classification egress. This concept directs our attention to—not only the practices and politics of classifying things—but also how actors work to escape or resist classification systems in practice. Second, the article aims to increase our understanding of the history of quantified and statistical health surveillance. In this, the article investigates how actors in health surveillance assembled a knowledge infrastructure for surveilling, quantifying, and detecting unknown patterns of congenital malformations in the wake of the Thalidomide disaster in the early 1960s.

The intent with this chapter is dual: First, it aims to add to the vocabulary for analyzing the politics sensing infrastructures. Drawing on post actor-network theory sensibilities, the chapter introduces the concept of style of inference in order to analyze the politics of how different sensing infrastructures apprehend the world (cf. Fujimura & Chou; Hacking). Paraphrasing Adrian Mackenzie: different sensing infrastructures have very different ways of navigating the steadily increasing tidal wave of data—and we need to understand how these differences are integrated with society at large (Mackenzie). An important argument of the chapter is thus that different styles of inference are more or less compatible with a wider political and organizational context. For example, the value of web searches on flu symptoms are not fully trusted as evidence of flu outbreaks in the healthcare system. The style of inferring flu intensity is not stabilized. The chapter therefore contends that there is a need to understand how sensing infrastructures have different styles of inference, and how these are differently compatible with governmental action and politics. Thus, the argument is that different styles of inference are deeply implicated in a politics of sensing.

This article has two objectives: First, the article seeks to make a methodological intervention in the social study of algorithms. Second, the article traces ethnographically how an algorithm was used to enact a pandemic, and how the power to construct this disease outbreak was moved around through an algorithmic assemblage. The article argues that there is a worrying trend to analytically reduce algorithms to coherent and stable objects whose computational logic can be audited for biases to create fairness, accountability, and transparency (FAccT). To counter this reductionist and determinist tendency, the article proposes three methodological rules that allows an analysis of algorithmic power in practice. Empirically, the article traces the assembling of a recent epidemic at the European Centre for Disease Control and Prevention—the Zika outbreak starting in 2015—and shows how an epidemic was put together using an array of computational resources, with very different spaces for intervening. A key argument is that we, as analysts of algorithms, need to attend to how multiple spaces for agency, opacity, and power open and close in different parts of algorithmic assemblages. The crux of the matter is that actors experience different degrees of agency and opacity in different parts of any algorithmic assemblage. Consequently, rather than auditing algorithms for biased logic, the article shows the usefulness of examining algorithmic power as enacted and situated in practice.