This paper sheds light on the role of digital platform labour in the development of today’s artificial intelligence, predicated on data-intensive machine learning algorithms. Focus is on the specific ways in which outsourcing of data tasks to myriad ‘micro-workers’, recruited and managed through specialized platforms, powers virtual assistants, self-driving vehicles and connected objects. Using qualitative data from multiple sources, we show that micro-work performs a variety of functions, between three poles that we label, respectively, ‘artificial intelligence preparation’, ‘artificial intelligence verification’ (...) and ‘artificial intelligence impersonation’. Because of the wide scope of application of micro-work, it is a structural component of contemporary artificial intelligence production processes – not an ephemeral form of support that may vanish once the technology reaches maturity stage. Through the lens of micro-work, we prefigure the policy implications of a future in which data technologies do not replace human workforce but imply its marginalization and precariousness. (shrink)

An AI winter may be defined as the stage when technology, business, and the media come to terms with what AI can or cannot really do as a technology without exaggeration. Through discussion of previous AI winters, this paper examines the hype cycle (which by turn characterises AI as a social panacea or a nightmare of apocalyptic proportions) and argues that AI should be treated as a normal technology, neither as a miracle nor as a plague, but rather as of (...) the many solutions that human ingenuity has managed to devise. (shrink)

This article contributes to the debate on automation and justice by discussing two under-represented concerns: labour justice and equality. Since automation involves both winners and losers, and given that there is no ‘end of work’ on the horizon, it is argued that most normative views on the subject – i.e. the ‘allocative’ view of basic income, and the ‘desirability’ views of post-work and workist ethics – do not provide many resources with which to address unjustly unequal divisions of labour involved (...) in technological innovation. This article problematises these common responses reframing the problem from the perspective of labour justice. While the allocative view assumes that labour justice follows ‘spontaneously’ from income redistribution, the desirability views are chiefly interested in either defining or contesting the meanings of work for individuals, overlooking the interdependent nature of work and concerns of equality other than autonomy. Two conceptions of labour justice are thus applied to the problem: Paul Gomberg’s contributive justice, and Iris Young’s democratic division of labour. Instead of deciding between them, the normative core of ‘contributive parity’ is suggested as a critical standard for assessing unequal labour structures, and for envisaging a future in which technology can be an ally in making social cooperation fair. (shrink)

Recently, following the social and subjective consequences of the neoliberal wave, there seems to be a renewed interest in work as occupying a central place in social and subjective life. For the first time in decades, both sociologists and critical theorists once more again regard work as a major constituent of the subject’s identity and thus as an appropriate object of analysis for those engaged in critique of the social pathologies. The aim of this article is to present a succinct (...) analysis of Axel Honneth’s thoughts on the concept of work and to propose an approach granting it a more substantial role in social theory. To this end, this article will embark upon a reappraisal of the importance of the material and psychological dimensions of the subject’s interactions in the world of work. It aims to demonstrate that the normative demands associated with these dimensions are, like the normative demands of recognition, immanent and universal. In other words, it will argue that the normative ideals related to individuals’ bodily and psychic life (in the workplace and beyond) are not necessarily utopian in the negative sense (abstract and unrealistic). If this is indeed the case, theorists could take these normative demands for emancipation as a guide to analyzing the sociological, political and moral implications of the transition from the ‘Fordist’ to the ‘post-Fordist’ organization of labor. (shrink)

The paper examines some of the processes of the closely knit relationship between Google’s ideologies of neutrality and objectivity and global market dominance. Neutrality construction comprises an important element sustaining the company’s economic position and is reflected in constant updates, estimates and changes to utility and relevance of search results. Providing a purely technical solution to these issues proves to be increasingly difficult without a human hand in steering algorithmic solutions. Search relevance fluctuates and shifts through continuous tinkering and tweaking (...) of the search algorithm. The company also uses third parties to hire human raters for performing quality assessments of algorithmic updates and adaptations in linguistically and culturally diverse global markets. The adaptation process contradicts the technical foundations of the company and calculations based on the initial Page Rank algorithm. Annual market reports, Google’s Search Quality Rating Guidelines, and reports from media specialising in search engine optimisation business are analysed. The Search Quality Rating Guidelines document provides a rare glimpse into the internal architecture of search algorithms and the notions of utility and relevance which are presented and structured as neutral and objective. Intertwined layers of ideology, hidden labour of human raters, advertising revenues, market dominance and control are discussed throughout the paper. (shrink)

STS research has devoted relatively little attention to the promotion and reception of science and technology by non-scientific actors and institutions. One consequence is that the relationship of science and technology to political power has tended to remain undertheorized. This article aims to fill that gap by introducing the concept of sociotechnical imaginaries. Through a comparative examination of the development and regulation of nuclear power in the US and South Korea, the article demonstrates the analytic potential of the imaginaries concept. (...) Although nuclear power and nationhood have long been imagined together in both countries, the nature of those imaginations has remained strikingly different. In the US, the state’s central move was to present itself as a responsible regulator of a potentially runaway technology that demands effective containment. In South Korea, the dominant imaginary was of atoms for development which the state not only imported but incorporated into its scientific, technological and political practices. In turn, these disparate imaginaries have underwritten very different responses to a variety of nuclear shocks and challenges, such as Three Mile Island (TMI), Chernobyl, and the spread of the anti-nuclear movement. (shrink)

This contribution aims at proposing a framework for articulating different kinds of “normativities” that are and can be attributed to “algorithmic systems.” The technical normativity manifests itself through the lineage of technical objects. The norm expresses a technical scheme’s becoming as it mutates through, but also resists, inventions. The genealogy of neural networks shall provide a powerful illustration of this dynamic by engaging with their concrete functioning as well as their unsuspected potentialities. The socio-technical normativity accounts for the manners in (...) which engineers, as actors folded into socio-technical networks, willingly or unwittingly, infuse technical objects with values materialized in the system. Surveillance systems’ design will serve here to instantiate the ongoing mediation through which algorithmic systems are endowed with specific capacities. The behavioral normativity is the normative activity, in which both organic and mechanical behaviors are actively participating, undoing the identification of machines with “norm following,” and organisms with “norminstitution”. This proposition productively accounts for the singularity of machine learning algorithms, explored here through the case of recommender systems. The paper will provide substantial discussions of the notions of “normative” by cutting across history and philosophy of science, legal, and critical theory, as well as “algorithmics,” and by confronting our studies led in engineering laboratories with critical algorithm studies. (shrink)

In recent years, critical scholarship has drawn attention to increasing power differentials between corporations that use data and people whose data is used. A growing number of scholars see digital data and information commons as a way to counteract this asymmetry. In this paper I raise two concerns with this argument: First, because digital data and information can be in more than one place at once, governance models for physical common-pool resources cannot be easily transposed to digital commons. Second, not (...) all data and information commons are suitable to address power differentials. In order to create digital commons that effectively address power asymmetries we must pay more systematic attention to the issue of exclusion from digital data and information commons. Why and how digital data and information commons exclude, and what the consequences of such exclusion are, decide whether commons can change power asymmetries or whether they are more likely to perpetuate them. (shrink)

This article investigates the work of processors who curate and “clean” the data sets that researchers submit to data archives for archiving and further dissemination. Based on ethnographic fieldwork conducted at the data processing unit of a major US social science data archive, I investigate how these data processors work, under which status, and how they contribute to data sharing. This article presents two main results. First, it contributes to the study of invisible technicians in science by showing that the (...) same procedures can make technical work invisible outside and visible inside the archive, to allow peer review and quality control. Second, this article contributes to the social study of scientific data sharing, by showing that the organization of data processing directly stems from the conception that the archive promotes of a valid data set—that is, a data set that must look “pristine” at the end of its processing. After critically interrogating this notion of pristineness, I show how it perpetuates a misleading conception of data as “raw” instead of acknowledging the important contribution of data processors to data sharing and social science. (shrink)

To a greater extent than in other technical domains, research and progress in Artificial Intelligence has always been entwined with the fictional. Its language echoes strongly with other forms of cultural narratives, such as fairytales, myth and religion. In this essay we present varied examples that illustrate how these analogies have guided not only readings of the AI enterprise by commentators outside the community but also inspired AI researchers themselves. Owing to their influence, we pay particular attention to the similarities (...) between religious language and the way in which the potential advent of greater than human intelligence is presented contemporarily. We then move on to the role that fiction, science fiction most of all, has historically played and is still playing in the discussion of AI by influencing researchers and the public, shifting the weights of different scenarios in our collectively perceived probability space. We sum up by arguing that the lore surrounding AI research, ancient and modern, points to the ancestral and shared human motivations that drive researchers in their pursuit and fascinate humanity at large. These points of narrative entanglement where AI meets the wider culture should serve to amplify the call to engage ourselves with the discussion of the potential destination of this technology. (shrink)

Artificial Intelligence in the form of different machine learning models is applied to Big Data as a way to turn data into valuable knowledge. The rhetoric is that ensuing predictions work well—with a high degree of autonomy and automation. We argue that we need to analyze the process of applying machine learning in depth and highlight at what point human knowledge production takes place in seemingly autonomous work. This article reintroduces classification theory as an important framework for understanding such seemingly (...) invisible knowledge production in the machine learning development and design processes. We suggest a framework for studying such classification closely tied to different steps in the work process and exemplify the framework on two experiments with machine learning applied to Facebook data from one of our labs. By doing so we demonstrate ways in which classification and potential discrimination take place in even seemingly unsupervised and autonomous models. Moving away from concepts of non-supervision and autonomy enable us to understand the underlying classificatory dispositifs in the work process and that this form of analysis constitutes a first step towards governance of artificial intelligence. (shrink)