Algorithmic governmentality is a new form of political governance interconnected with technology and computation. By coining the term “algorithmic governmentality,” Antoinette Rouvroy argues that this mode of governance reduces everything to data, and people are no longer individuals but dividuals (able to be divided) or readable data profiles. Implementing the concept of algorithmic governmentality, the current study analyses Project Itoh’s award-winning novel Harmony in terms of such relevant concepts as “subjectivity,” “infra-individuality” and “control,” as suggested by Rouvroy and colleagues. The (...) analysis further draws on Foucault’s ideas of “governmentality” and “neoliberalism” and Deleuze’s concepts of “dividuality” and “society of control.” In Itoh’s fictional world, the entire society is subject to the new medical government, which replaced the chaotic world with a perfect but harrowing benevolent society, eradicating disease, suicide and crime. As elucidated in this paper, despite the dominant controlling government, there is a hope for humans to regain and reestablish their subjectivity and give meaning to their own personality by defying the nihilistic computational system. (shrink)

Deleuze's Postscript on the Societies of Control has been the most common entry point for interrogating the ways in which contemporary digital technologies have altered the social and the subjective from a Deleuzo-Guattarian perspective. It is, however, in A Thousand Plateaus that we find the most comprehensive set of resources for grappling with the Algocene, the contemporary digitally interconnected world of ubiquitous computing, drones, data mining, smart cities, social media, automated trading and other data-driven technologies that are heavily reliant upon (...) algorithmic processes and deep learning networks. In this broad survey, I argue that in order to grapple with these new technological assemblages and the implications of their deployment across society, we should posit a new major stratum, the algoplastic, and, along with it, new modes of operation of order-words and the regimes of signs they form part of. I conclude by posing some of the new problems that emerge with the Algocene. (shrink)

Decisions based on algorithmic, machine learning models can be unfair, reproducing biases in historical data used to train them. While computational techniques are emerging to address aspects of these concerns through communities such as discrimination-aware data mining and fairness, accountability and transparency machine learning, their practical implementation faces real-world challenges. For legal, institutional or commercial reasons, organisations might not hold the data on sensitive attributes such as gender, ethnicity, sexuality or disability needed to diagnose and mitigate emergent indirect discrimination-by-proxy, such (...) as redlining. Such organisations might also lack the knowledge and capacity to identify and manage fairness issues that are emergent properties of complex sociotechnical systems. This paper presents and discusses three potential approaches to deal with such knowledge and information deficits in the context of fairer machine learning. Trusted third parties could selectively store data necessary for performing discrimination discovery and incorporating fairness constraints into model-building in a privacy-preserving manner. Collaborative online platforms would allow diverse organisations to record, share and access contextual and experiential knowledge to promote fairness in machine learning systems. Finally, unsupervised learning and pedagogically interpretable algorithms might allow fairness hypotheses to be built for further selective testing and exploration. Real-world fairness challenges in machine learning are not abstract, constrained optimisation problems, but are institutionally and contextually grounded. Computational fairness tools are useful, but must be researched and developed in and with the messy contexts that will shape their deployment, rather than just for imagined situations. Not doing so risks real, near-term algorithmic harm. (shrink)

Contemporary infectious disease surveillance systems aim to employ the speed and scope of big data in an attempt to provide global health security. Both shifts - the perception of health problems through the framework of global health security and the corresponding technological approaches – imply epistemological changes, methodological ambivalences as well as manifold societal effects. Bringing current findings from social sciences and public health praxis into a dialogue, this conversation style contribution points out several broader implications of changing disease surveillance. (...) The conversation covers epidemiological issues such as the shift from expert knowledge to algorithmic knowledge, the securitization of global health, and the construction of new kinds of threats. Those developments are detailed and discussed in their impacts for health provision in a broader sense. (shrink)

Who Needs Stories if You Can Get the Data? ISPs in the Era of Big Number Crunching Content Type Journal Article Category Special Issue Pages 371-390 DOI 10.1007/s13347-011-0041-8 Authors Mireille Hildebrandt, Institute of Computer and Information Sciences (ICIS), Radboud University Nijmegen, Nijmegen, the Netherlands Journal Philosophy & Technology Online ISSN 2210-5441 Print ISSN 2210-5433 Journal Volume Volume 24 Journal Issue Volume 24, Number 4.

In this article we expand upon the conceptual framework of Félix Guattari’s 1989 essay, The Three Ecologies. Here Guattari examines changes in subjectivity that have come about due to scientific and technological advances which, as he sees it, brought about an “ecological disequilibrium” ([1989]2000, 27) and deteriorated individual and collective modes of being. In response to this Guattari proposes a kind of holistic therapy or ‘ecosophy’ between three ecological registers: “the environment, social relations and human subjectivity” (ibid., 28). Guattari cautions (...) that we not only take note of these macro determinations, but also heed the libidinal impulses of desire – what captures it, what directs it, and what shuts it down. Since the publication of The Three Ecologies, the rise of digital technologies has dramatically influenced the ways in which people think, live and communicate. Technological infrastructures, for instance, are used to spread disinformation at a vast speed and scale, and because social networks are often homophile many people infrequently encounter critical disagreement and debate. The increase in media and digital communications usage has also led to new forms of social inclusion and exclusion, the most exacerbated form of which is probably the phenomenon known as hikikomori – acute, prolonged social withdrawal. Taking hikikomori as our focus, we describe what we see as a general set of symptoms of society and trace its myriad intersections with an ever-increasing algorithmic ubiquity, which we posit as the new form of hyper-modulation following from Foucault’s disciplinary societies and Deleuze’s control societies. (shrink)

“Privacy as confidentiality” has been the dominant paradigm in computer science privacy research. Privacy Enhancing Technologies (PETs) that guarantee confidentiality of personal data or anonymous communication have resulted from such research. The objective of this paper is to show that such PETs are indispensable but are short of being the privacy solutions they sometimes claim to be given current day circumstances. Using perspectives from surveillance studies we will argue that the computer scientists’ conception of privacy through data or communication confidentiality (...) is techno-centric and displaces end-user perspectives and needs in surveillance societies. We will further show that the perspectives from surveillance studies also demand a critical review for their human-centric conception of information systems. Last, we rethink the position of PETs in a surveillance society and argue for the necessity of multiple paradigms for addressing privacy concerns in information systems design. (shrink)

Building on conceptual insights from the history and sociology of numbers, media and surveillance studies, and theories of governance and risk, this article analyzes the forms of transparency produced by the use of numbers in social life. It examines what it is about numbers that often makes their ‘truth claims’ so powerful, investigates the role that numerical operations play in the production of retrospective, real-time and anticipatory forms of transparency in contemporary politics and economic transactions, and discusses some of the (...) implications resulting from the increasingly abstract and machine-driven use of numbers. It argues that the forms of transparency generated by machine-driven numerical operations open up for individual and collective practices in ways that are intimately linked to precautionary and pre-emptive aspirations and interventions characteristic of contemporary governance. As such, these numerical operations raise important political and ethical questions that deserve further conceptual and empirical scrutiny. (shrink)