Framing datafication as new form of knowledge production has become a trope in both academic and commercial contexts. This special theme examines and ultimately rejects the familiar grand claims of datafication, to instead pay attention to emergent conversations that seek to take a more nuanced stock of the status and nature of datafied knowledge production. The articles in this special theme thus engage with datafied knowledge production through elaborate explorations of how datafied knowledge depends on the contexts of its production (...) and the forms of knowledge production that precede it in those contexts. Our basic argument is that while the resources, material features and analytical operations involved in datafied knowledge production may be different, many fundamental concerns about epistemology, ontology and methods remain relevant to understand what shapes it. We still need to understand and explicate the assumptions, operations and consequences of emergent forms of knowledge production. If datafied knowledge production is neither a clean revolutionary break with past forms of knowledge production nor a balloon of pure hype, the articles in this special theme ask: what does the phenomenon of datafied knowledge production look like? Which digital and datafied infrastructures support its future development? And what potentialities and limits do such forms of analysis and knowledge production contain? (shrink)

It is well known that AI-based language technology—large language models, machine translation systems, multilingual dictionaries, and corpora—is currently limited to three percent of the world’s most widely spoken, financially and politically backed languages. In response, recent efforts have sought to address the “digital language divide” by extending the reach of large language models to “underserved languages.” We show how some of these efforts tend to produce flawed solutions that adhere to a hard-wired representational preference for certain languages, which we call (...) language modeling bias. Language modeling bias is a specific and under-studied form of linguistic bias were language technology by design favors certain languages, dialects, or sociolects with respect to others. We show that language modeling bias can result in systems that, while being precise regarding languages and cultures of dominant powers, are limited in the expression of socio-culturally relevant notions of other communities. We further argue that at the root of this problem lies a systematic tendency of technology developer communities to apply a simplistic understanding of diversity which does not do justice to the more profound differences that languages, and ultimately the communities that speak them, embody. Drawing on the concept of epistemic injustice, we point to the broader ethico-political implications and show how it can lead not only to a disregard for valuable aspects of diversity but also to an under-representation of the needs of marginalized language communities. Finally, we present an alternative socio-technical approach that is designed to tackle some of the analyzed problems. (shrink)

Freezers with biospecimen deposits became biobanks and later were networked at the pan-European level in 2013 under the Biobanking and BioMolecular Resources Research Infrastructure—European Research Infrastructure Consortium (BBMRI-ERIC). Drawing on document analysis about the BBMRI-ERIC and multi-sited fieldwork with biobankers in Spain from a science and technology studies approach, we explore what biobanks are expected to do and become under the BBMRI-ERIC framework, and how infrastructural transitions promote particular transformations in biobanking practices. The primary purpose of biobanks in Europe is (...) presented as being to become mediators in contemporary biomedical research (global sharing nodes) distribution, and distributed nodes of samples and their associated data. We argue that infrastructural transitions are complicated and heterogeneous, giving rise to unattended local concerns on adjusting their practices to fit into the BBMRI-ERIC framework, even for non-members, as the case of Spain illustrates, where “old practices” of collection and storage are questioned. In this article, we aim to encourage qualitative studies to explore the lags between pan-European policies and prospects, different contextual interpretations, and biobanking reconfigurations as an opportunity to explore what that lag is made of (e.g. tensions with “old practices,” unresolved conflicts with the national agendas, reservations on a possible centralization of the biobanking practices by regional biobanks, lack of funding, etc.). Such research could enrich not only policy guidance, but also the understanding of technoscientific infrastructures’ scalability. (shrink)

An emerging discourse about automated agricultural machinery imagines farms as places where farmers and workers do not need to be, but also implicitly frames farms as intolerable places where people do not want to be. Only autonomous machines, this story goes, can relieve farmers and workers of this presumed burden by letting them ‘farm at a distance’. In return for this distanced autonomy, farmers are promised increased control over their work-life balance and greater farm productivity from letting ‘smart’ robots assume (...) control over the operational environment. Drawing upon the ways that these machines are promoted by manufacturers in various media, we trace the nascent contours of what we term a liberatory sociotechnical imaginary for agricultural automation across three cases—automated milking systems, self-driving tractors, and robotic strawberry pickers. We show how promises for new freedoms and autonomy are flexibly deployed to respond to distinct frictions that farmers, workers, and even farm animals experience in different modes of industrial agriculture. However, underlying these promises is the purposefully understated self-interest of manufacturers, who stand to gain further control over farms if automated technologies assume a central role in agriculture. Through the liberatory rhetoric, we contend, the imaginary seeks to enroll farmers into a socio-technical network that creates new relations of dependence upon the companies who design, sell, maintain, and often retain ownership over automated technologies. While potentially powerful, this imaginary may nonetheless fail to coalesce as farmers, workers, and agroecosystems exert their own agency on automated imaginaries and technological futures for agriculture. (shrink)

A profusion of jobs has arisen in contemporary capitalism involving ‘connective labor’, or the work of emotional recognition. Yet the expansion of this interpersonal work occurs at the same time as its systematization, as pressures of efficiency, measurement and automation reshape the work, generating a ‘colliding intensification’. Existing scholarship offers three different ways of understanding the role of emotions in connective labor – as tool, commodity or vulnerability – depending on their view of systematization as useful, inseparable or dehumanizing. Based (...) on 106 in-depth interviews and 300+ hours of observations, I found that vestiges of all three models lurked in the experience of providing connective labor, yet none fully captured the profound meaning practitioners reported finding in their work. Systems varied on three dimensions, reflecting the relative worth of worker, recipient or the work, extracting value from the forged connections, while the meanings workers derived shaped their perspective on its systematization. (shrink)

Over the last decade, the Anthropocene has overrun the discourses of the humanities and social sciences. Remarkably, two of the most astute commentators, the cross-disciplinary theorist Barbara Herrnstein Smith and the unorthodox philosopher Isabelle Stengers, find inspiration for grappling with these issues in the same apparently odd place: the work of the Polish microbiologist and comparative epistemologist Ludwik Fleck. The first part of this essay explores the role of Fleck's radical constructivism in Smith's analyses of perplexing Anthropocene realities and Stengers's (...) arguments for slowing down science and learning to “compose with Gaia.” In conjunction, they generate a pattern of speculative, conceptual, practical, and political motifs for dealing with changing climates. The second half of the essay uses those insights to test a divergent series of proposals for how to conceive science, politics, theory, and environmental relations in the Anthropocene. (shrink)

The object-oriented ontology group of philosophies, and certain strands of posthumanism, overlook important ethical and biological differences, which make a difference. These allied intellectual movements, which have at times found broad popular appeal, attempt to weird life as a rebellion to the forced melting of lifeforms through the artefacts of capitalist realism. They truck, however, in a recursive solipsism resulting in ontological flattening, overlooking that things only show up to us according to our attunement to them. Ecology and biology tend (...) to get lost in the celebration of “thingness,” which puts on par artifacts, trash, and living beings. Such abstractions fail to understand the political, ethical, and ontological implications of eliding the animate/nonanimate distinction, which from the opposite direction (of flattening) reproduce the same violences of historical colonialism (hierarchical humanism). I argue that ontological flattening entails epistemological narcissism, fails to take into account plural (interspecies) perspectives, and propose biosemiotics can address these shortcomings through becoming-with nonhuman knowledge. (shrink)