The claim is frequently made that, as cities become loaded up with information and communications technology and a resultant profusion of data, so they are becoming sentient. But what might this mean? This paper offers some insights into this claim by, first of all, reworking the notion of the social as a spatial complex of ‘outstincts’. That makes it possible, secondly, to reconsider what a city which is aware of itself might look like, both by examining what kinds of technological (...) practices are becoming commonplace and by considering the particular case of spatial awareness. In turn, this leads to a third rumination on how cities might become aware as different kinds of sprite, channelling outstincts in spatially variable ways. Whatever the case, it is clear that new technical-artistic interventions are required if these sprites are not to become simply servants of the security–entertainment complex. Some of these interventions are examined in the fourth part of the paper. (shrink)

Data analytics, particularly the current rhetoric around “Big Data”, tend to be presented as new and innovative, emerging ahistorically to revolutionize modern life. In this article, we situate one branch of Big Data analytics, spatial Big Data, through a historical predecessor, geodemographic analysis, to help develop a critical approach to current data analytics. Spatial Big Data promises an epistemic break in marketing, a leap from targeting geodemographic areas to targeting individuals. Yet it inherits characteristics and problems from geodemographics, including a (...) justification through the market, and a process of commodification through the black-boxing of technology. As researchers develop sustained critiques of data analytics and its effects on everyday life, we must so with a grounding in the cultural and historical contexts from which data technologies emerged. This article and others develop a historically situated, critical approach to spatial Big Data. This history illustrates connections to the critical issues of surveillance, redlining, and the production of consumer subjects and geographies. The shared histories and structural logics of spatial Big Data and geodemographics create the space for a continued critique of data analyses’ role in society. (shrink)

A self-perceived lack of training in ethical theories and related pedagogy has kept many engineering faculty members from teaching data ethics, an important aspect of engineering research that has become more salient in recent years. This paper describes the development of a module, which includes concepts, cases, policies, and best practices, to support the teaching of ethical data practice. Based on a user-oriented design approach and a moral literacy framework, the module was designed to be used in different courses and (...) co-curricular activities for students of varying levels of competence to improve their ability to identify and analyze ethical problems associated with the handling of research data. This work seeks to encourage ethical reflection on researchers’ data practice through the idea of an “ecology of data,” which highlights the co-production of data by multiple, interconnected, and heterogeneous actors. This paper also presents online and in-class evidence about the impact and limitations of the module, which is now available for interested researchers and instructors to browse and use. (shrink)

Living in an era of technological innovations, we must understand and trust them to benefit from these new technologies. In this context, paternalism is renewed as the so-called “soft-” or “Libertarian paternalism”. How can we face it and ensure freedom in the vortex of wellmeaning advice and persuasion? This paper will discuss 1. the characteristics of freedom since the 18th century from the perspective of the Enlightenment discourse in Germany by Mendelssohn and Kant, 2. the conditions for freedom in the (...) contemporary age of accelerating technological innovation, and 3. from trans-modernism, rethinking the dichotomy between otherness and autonomy, coercion and freedom, by the idea of 融通無碍 Yuzu-Muge, tactfulness in 華厳学 Hua-Yan Philosophy. (shrink)

The human environment is currently undergoing massive change amid the rapid adoption of information and communications technology (ICT). ICT can be characterized as offering an opportunity to consider the nature of humanity, create new values, and foster new cultures. As humans, the question that technical innovation relating to Artificial Intelligence (AI) and Robots thrusts before us is, “What is a human?” What exactly are the things that AI will never be able to do, no matter how close it gets to (...) human capabilities? What makes us humans, and what is it that only humans can do? This essay discusses the impact of AI technology on humans and society from the perspective of a turning point in how people perceive themselves and humanity. (shrink)

The European Union approach to data protection consists of assessing the adequacy of the data protection offered by the laws of a particular jurisdiction against a set of principles that includes purpose limitation, transparency, quality, proportionality, security, access, and rectification. The EU's Data Protection Directive sets conditions on the transfer of data to third countries by prohibiting Member States from transferring to such countries as have been deemed inadequate in terms of the data protection regimes. In theory, each jurisdiction is (...) evaluated similarly and must be found fully compliant with the EU's data protection principles to be considered adequate. In practice, the inconsistency with which these evaluations are made presents a hurdle to international data-sharing and makes difficult the integration of different data-sharing approaches; in the 20 years since the Directive was first adopted, the laws of only five countries from outside of the EU, Economic Area, or the European Free Trade Agreement have been deemed adequate to engage in data transfers without the need for further administrative safeguards. (shrink)

Criticism of big data has focused on showing that more is not necessarily better, in the sense that data may lose their value when taken out of context and aggregated together. The next step is to incorporate an awareness of pitfalls for aggregation into the design of data infrastructure and institutions. A common strategy minimizes aggregation errors by increasing the precision of our conventions for identifying and classifying data. As a counterpoint, we argue that there are pragmatic trade-offs between precision (...) and ambiguity that are key to designing effective solutions for generating big data about biodiversity. We focus on the importance of theory-dependence as a source of ambiguity in taxonomic nomenclature and hence a persistent challenge for implementing a single, long-term solution to storing and accessing meaningful sets of biological specimens. We argue that ambiguity does have a positive role to play in scientific progress as a tool for efficiently symbolizing multiple aspects of taxa and mediating between conflicting hypotheses about their nature. Pursuing a deeper understanding of the trade-offs and synthesis of precision and ambiguity as virtues of scientific language and communication systems then offers a productive next step for realizing sound, big biodiversity data services. (shrink)

This article seeks to address current debates comparing polls and opinion mining as empirically based figuration models of public opinion in the light of in-depth intellectual debates on the role and nature of public opinion that began after the French Revolution and the controversy over public opinion spurred by the invention of polls. Issues of historical quantification and re-conceptualisation of public opinion are addressed in four parts. The first summarises the history of the rise and fall of the concept of (...) public opinion. The second re-examines the key controversies in the debates on the theoretical, empirical and social implications and consequences of the invention of polling. The third part scrutinises the datafication of public opinion that started with polling industry and continues in the age of big data and data mining. The final section discusses the controversial potentials of opinion-mining technology and suggests ways in which social scientists could critically respond to the big data and opinion-mining challenges in order to reintegrate the ideas of publicness, the public and public sphere into public opinion research. (shrink)

It is estimated that one in three women experience intimate partner violence (IPV) across the course of their life. The popular uptake of “smart speakers” powered by sophisticated AI means that surveillance of the domestic environment is increasingly possible. Correspondingly, there are various proposals to use smart speakers to detect or report IPV. In this paper, we clarify what might be possible when it comes to combatting IPV using existing or near-term technology and also begin the project of evaluating this (...) project both ethically and politically. We argue that the ethical landscape looks different depending on whether one is considering the decision to develop the technology or the decision to use it once it has been developed. If activists and governments wish to avoid the privatisation of responses to IPV, ubiquitous surveillance of domestic spaces, increasing the risk posed to members of minority communities by police responses to IPV, and the danger that more powerful smart speakers will be co-opted by men to control and abuse women, then they should resist the development of this technology rather than wait until these systems are developed. If it is judged that the moral urgency of IPV justifies exploring what might be possible by developing this technology, even in the face of these risks, then it will be imperative that victim-survivors from a range of demographics, as well as government and non-government stakeholders, are engaged in shaping this technology and the legislation and policies needed to regulate it. (shrink)

Why hasn’t democracy been promoted by nor ICT been controlled by democratic governance? To answer this question, this research begins its investigation by comparing knowledge acquisition systems throughout history: orality, literacy, hyperlink, and hyperlead. “Hyperlead” is a newly coined concept to emphasize the passivity of people when achieving knowledge and information via algorithmic recommendation technologies. Subsequently, the four systems are compared in terms of their epistemological characteristics and political implications. It is argued that, while literacy and hyperlink contributed to the (...) furthering of democracy, hyperlead poses a fundamental challenge to it, undermining human autonomy to make decisions and aggravating vertical and lateral polarizations. In addition, the similarity between orality and hyperlead is addressed. Finally, suggestions to improve or to advert the current trend are provided. What happened during the transition period from orality to literacy and subsequently to hyperlink could be a reference for an alternative to hyperlead. Some technical adjustments and appropriate regulations requiring more transparency in algorithmic recommendation systems would help us to overcome hyperlead and preserve human autonomy. (shrink)

\noindent\textbf{Introduction} Online interventions hold great potential for Therapeutic Change Process Research (TCPR), a field that aims to relate in-therapeutic change processes to the outcomes of interventions. Online a client is treated essentially through the language their counsellor uses, therefore the verbal interaction contains many important ingredients that bring about change. TCPR faces two challenges: how to derive meaningful change processes from texts, and secondly, how to assess these complex, varied and multi-layered processes? We advocate the use text mining and multi-level (...) models (MLMs): the former offers tools and methods to discovers patterns in texts; the latter can analyse these change processes as outcomes that vary at multiple levels. \noindent\textbf{Method} We (re-)used the data from \cite{Lamers2015} because it includes outcomes and the complete online intervention for clients with mild depressive symptoms. We used text mining to obtain basic text-variables from e-mails, that we analysed through MLMs. \noindent\textbf{Results} We found that we could relate outcomes of interventions to variables containing text-information. We conclude that we can indeed bridge text mining and MLMs for TCPR as it was possible to relate text-information (obtained through text mining) to multi-levelled TCPR outcomes (using a MLM). \noindent\textbf{Discussion} Text mining can be helpful to obtain change processes, which is also the main challenge for TCPR. We showed how MLMs and text mining can be combined, but our proposition leaves open how to obtain the most relevant textual operationalization of TCPR concepts. That requires interdisciplinary collaboration and discussion. The future does look bright: based on our proof-of-concept study we conclude that MLMs and text mining can indeed advance TCPR. (shrink)

Constellations, Volume 29, Issue 2, Page 146-160, June 2022.

This article critically examines the domination exerted by big digital companies on the current social, economic, and political context of modern societies, with a particular focus on the implications for the proper functioning of democracy. The objective of this article is to introduce and develop the concept of datafeudalism, expose its emergence for the proper functioning of modern societies and democracy, and to propose courses of action to reverse this situation. To achieve this purpose, firstly, the evolution from surveillance capitalism (...) to datafeudalism will be discussed. Secondly, the structures and operating logic of data feudalism will be analyzed. Thirdly, the harmful impacts of datafeudalism on the proper functioning of the democratic systems of the European Union will be examined. Finally, an attempt will be made to outline courses of action that will make it possible to reverse the situation of economic, social and political tyranny exercised by big digital companies through datafeudalism. (shrink)

We are living in an algorithmic age where mathematics and computer science are coming together in powerful new ways to influence, shape and guide our behaviour and the governance of our societies. As these algorithmic governance structures proliferate, it is vital that we ensure their effectiveness and legitimacy. That is, we need to ensure that they are an effective means for achieving a legitimate policy goal that are also procedurally fair, open and unbiased. But how can we ensure that algorithmic (...) governance structures are both? This article shares the results of a collective intelligence workshop that addressed exactly this question. The workshop brought together a multidisciplinary group of scholars to consider barriers to legitimate and effective algorithmic governance and the research methods needed to address the nature and impact of specific barriers. An interactive management workshop technique was used to harness the collective intelligence of this multidisciplinary group. This method enabled participants to produce a framework and research agenda for those who are concerned about algorithmic governance. We outline this research agenda below, providing a detailed map of key research themes, questions and methods that our workshop felt ought to be pursued. This builds upon existing work on research agendas for critical algorithm studies in a unique way through the method of collective intelligence. (shrink)

Contemporary privacy theories and European discussions about data protection employ the notion of ‘personal information’ to designate their areas of concern. The notion of personal information is demarcated from non-personal information—or just information—indicating that we are dealing with a specific kind of information. However, within privacy scholarship the notion of personal information appears undertheorized, rendering the concept somewhat unclear. We argue that in an age of datafication, protection of personal information and privacy is crucial, making the understanding of what is (...) meant by ‘personal information’ more important than ever. To contribute to this aim, we analyse the conception of personal information and its nature, including the distinction between personal and non-personal information from a philosophy of language perspective. Through analyses of aboutness and relative aboutness we point to challenges related to the demarcation between personal and non-personal information, which may in practice lead to all information being personal. (shrink)

Amongst other methods, political campaigns employ microtargeting, a specific technique used to address the individual voter. In the US, microtargeting relies on a broad set of collected data about the individual. However, due to the unavailability of comparable data in Germany, the practice of microtargeting is far more challenging. Citizens in Germany widely treat social media platforms as a means for political debate. The digital traces they leave through their interactions provide a rich information pool, which can create the necessary (...) conditions for political microtargeting following appropriate algorithmic processing. More specifically, data mining techniques enable information gathering about a people's general opinion, party preferences and other non-political characteristics. Through the application of data-intensive algorithms, it is possible to cluster users in respect of common attributes, and through profiling identify whom and how to influence. Applying machine learning algorithms, this paper explores the possibility to identify micro groups of users, which can potentially be targeted with special campaign messages, and how this approach can be expanded to large parts of the electorate. Lastly, based on these technical capabilities, we discuss the ethical and political implications for the German political system. (shrink)

Organized immaturity refers to the capacity of widely institutionalized sociotechnical systems to challenge qualities of human enlightenment, autonomy, and self-determination. In the context of surveillance capitalism, where these qualities are continuously put at risk, data transparency is increasingly proposed as a means of restoring human maturity by allowing individuals insight and choice vis-à-vis corporate data processing. In this article, however, I draw on research on General Data Protection Regulation–mandated data transparency practices to argue that transparency—while potentially fostering maturity—itself risks producing (...) new forms of organized immaturity by facilitating user ignorance, manipulation, and loss of control of personal data. Considering data transparency’s relative “successes” and “failures” regarding the cultivation of maturity, I outline a set of possible remedies while arguing for a general need to develop more sophisticated ethical appreciations of transparency’s complex and potentially problematic implications for organized (im)maturity in the digital age. (shrink)

Many studies in big data focus on the uses of data available to researchers, leaving without treatment data that is on the servers but of which researchers are unaware. We call this dark data, and in this article, we present and discuss it in the context of high-performance computing facilities. To this end, we provide statistics of a major HPC facility in Europe, the High-Performance Computing Center Stuttgart. We also propose a new position tailor-made for coping with dark data and (...) general data management. We call it the scientific data officer and we distinguish it from other standard positions in HPC facilities such as chief data officers, system administrators, and security officers. In order to understand the role of the SDO in HPC facilities, we discuss two kinds of responsibilities, namely, technical responsibilities and ethical responsibilities. While the former are intended to characterize the position, the latter raise concerns—and proposes solutions—to the control and authority that the SDO would acquire. (shrink)

Many studies in big data focus on the uses of data available to researchers, leaving without treatment data that is on the servers but of which researchers are unaware. We call this dark data, and in this article, we present and discuss it in the context of high-performance computing facilities. To this end, we provide statistics of a major HPC facility in Europe, the High-Performance Computing Center Stuttgart. We also propose a new position tailor-made for coping with dark data and (...) general data management. We call it the scientific data officer and we distinguish it from other standard positions in HPC facilities such as chief data officers, system administrators, and security officers. In order to understand the role of the SDO in HPC facilities, we discuss two kinds of responsibilities, namely, technical responsibilities and ethical responsibilities. While the former are intended to characterize the position, the latter raise concerns—and proposes solutions—to the control and authority that the SDO would acquire. (shrink)

This article argues that big data’s entrepreneurial potential is based not only on new technological developments that allow for the extraction of non-trivial, new insights out of existing data, but also on an ethical judgment that often remains implicit: namely the ethical judgment that those companies that generate these new insights can legitimately appropriate these insights. As a result, the business model of big data companies is essentially founded on a libertarian-inspired ‘finders, keepers’ ethic. The article argues, next, that this (...) presupposed ‘finder, keepers’ ethic is far from unproblematic and relies itself on multiple unconvincing assumptions. This leads to the conclusion that the conduct of companies working with big data might lack ethical justification. (shrink)

Google Trends reveals that at the time we were writing our article on ‘The Coming Crisis of Empirical Sociology’ in 2007 almost nobody was searching the internet for ‘Big Data’. It was only towards the very end of 2010 that the term began to register, just ahead of an explosion of interest from 2011 onwards. In this commentary we take the opportunity to reflect back on the claims we made in that original paper in light of more recent discussions about (...) the social scientific implications of the inundation of digital data. Did our paper, with its emphasis on the emergence of, what we termed, ‘social transactional data’ and ‘digital byproduct data’ prefigure contemporary debates that now form the basis and rationale for this excellent new journal? Or was the paper more concerned with broader methodological, theoretical and political debates that have somehow been lost in all of the loud babble that has come to surround Big Data. Using recent work on the BBC Great British Class Survey as an example this brief paper offers a reflexive and critical reflection on what has become – much to the surprise of its authors – one of the most cited papers in the discipline of sociology in the last decade. (shrink)

Biological sciences have strived to adopt the conceptual framework of physics and have become increasingly quantitatively oriented, aiming to refute the assertion that biology appears unquantifiable, unpredictable, and messy. But despite all effort, biology is characterized by a paucity of quantitative statements with universal applications. Nonetheless, many biological disciplines—most notably molecular biology—have experienced an ascendancy over the last 50 years. The underlying core concepts and ideas permeate and inform many neighboring disciplines. This surprising success is probably not so much attributable (...) to mathematical and statistical approaches in molecular biology, but rather to the preponderance of qualitative approaches, especially visualization. Visualizations can be afforded by quantitative research, but usually they rely on both, quantitative and qualitative research. I claim the following three features to be responsible for the unceasing zeal for using visualizations: visual representations facilitate reasoning, images can be cognitively processed in a “fast” manner, and abstractions of visual representations prompt conceptual advances. In summary, visualizations have largely contributed to the success of molecular biology by conveying its concepts to other disciplines, and at the same time, eclipsing mere quantitative approaches. However, visualizations also bear the risk of misinterpretation when traversing neighboring disciplines and even more so when pervading nonscientific domains. (shrink)

In this paper, we will argue that, while Big Data enthusiasts imply that the analysis of massive data sets can produce serendipitous (that is, unexpected and fortunate) discoveries, the way those models are currently designed not only does not create serendipity so easily but also frequently generates zemblanitous (that is, expected and unfortunate) findings.

In this paper we investigate if sentences presented as the result of the application of statistical models and artificial intelligence to large volumes of data – the so-called ‘Big Data’ – can be characterized as semantically true, or as quasi-true, or even if such sentences can only be characterized as probably quasi-false and, in a certain way, post-true; that is, if, in the context of Big Data, the representation of a data domain can be configured as a total structure, or (...) as a partial structure provided with a set of sentences assumed to be true, or if such representation cannot be configured as a partial structure provided with a set of sentences assumed to be true. (shrink)

The governments of China, India, and the United Kingdom are unanimous in their belief that bioinformatics should supply the link between basic life sciences research and its translation into health benefits for the population and the economy. Yet at the same time, as ambitious states vying for position in the future global bioeconomy they differ considerably in the strategies adopted in pursuit of this goal. At the heart of these differences lies the interaction between epistemic change within the scientific community (...) itself and the apparatus of the state. Drawing on desk-based research and thirty-two interviews with scientists and policy makers in the three countries, this article analyzes the politics that shape this interaction. From this analysis emerges an understanding of the variable capacities of different kinds of states and political systems to work with science in harnessing the potential of new epistemic territories in global life sciences innovation. (shrink)

Risk is an intrinsic part of our lives. In the future, the development and growth of the Internet of things allows getting a huge amount of data. Considering this evolution, our research focuses on developing a novel concept, namely Holistic Risk Assessment (HRA), that takes into consideration elements outside the direct influence of the individual to provide a highly personalized risk assessment. The HRA implies developing a methodology and a model. This paper is related to the epistemological positioning of this (...) research. We consider this research as an artificial science under the constructivism paradigm. We also introduce the positioning of this research in the complexity science paradigm. We end this paper by presenting a methodology based on an adapted Design Thinking Model. (shrink)

Critical Data Studies explore the unique cultural, ethical, and critical challenges posed by Big Data. Rather than treat Big Data as only scientifically empirical and therefore largely neutral phenomena, CDS advocates the view that Big Data should be seen as always-already constituted within wider data assemblages. Assemblages is a concept that helps capture the multitude of ways that already-composed data structures inflect and interact with society, its organization and functioning, and the resulting impact on individuals’ daily lives. CDS questions the (...) many assumptions about Big Data that permeate contemporary literature on information and society by locating instances where Big Data may be naively taken to denote objective and transparent informational entities. In this introduction to the Big Data & Society CDS special theme, we briefly describe CDS work, its orientations, and principles. (shrink)

In this paper we discuss the social and ethical issues that arise as a result of digitization based on six dominant technologies: Internet of Things, robotics, biometrics, persuasive technology, virtual & augmented reality, and digital platforms. We highlight the many developments in the digitizing society that appear to be at odds with six recurring themes revealing from our analysis of the scientific literature on the dominant technologies: privacy, autonomy, security, human dignity, justice, and balance of power. This study shows that (...) the new wave of digitization is putting pressure on these public values. In order to effectively shape the digital society in a socially and ethically responsible way, stakeholders need to have a clear understanding of what such issues might be. Supervision has been developed the most in the areas of privacy and data protection. For other ethical issues concerning digitization such as discrimination, autonomy, human dignity and unequal balance of power, the supervision is not as well organized. (shrink)

This article extends property-owning democracy to the digital realm and introduces “data-owning democracy,” a new political economic regime characterized by the wide distribution of data as capital among citizens. Drawing on republican theory and acknowledging data's unique role in the digital economy, it proposes a two-tier model that combines different modes of data ownership and corresponding rights. The first layer of “data-owning democracy” is characterized by a digital public infrastructure that enables citizens to collectively generate data and have a say (...) in how their citizen data are used. In the second layer, individuals automatically receive machine-readable copies of their data whenever they are generated—a slightly more advanced form of the European Union's existing right to data portability (Art. 20). With its focus on empowerment, data-owning democracy is designed to be complementary to existing data protection regulations. It also illustrates how political theory more broadly, and republican theory specifically, can be instructive for specifying the normative components of a new political economy dealing with questions of empowerment and digital rights. (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)

Intensified and extensive data production and data storage are characteristics of contemporary western societies. Health data sharing is increasing with the growth of Information and Communication Technology platforms devoted to the collection of personal health and genomic data. However, the sensitive and personal nature of health data poses ethical challenges when data is disclosed and shared even if for scientific research purposes. With this in mind, the Science and Values Working Group of the COST Action CHIP ME ‘Citizen's Health through (...) public-private Initiatives: Public health, Market and Ethical perspectives’ identified six core values they considered to be essential for the ethical sharing of health data using ICT platforms. We believe that using this ethical framework will promote respectful scientific practices in order to maintain individuals’ trust in research. We use these values to analyse five ICT platforms and explore how emerging data sharing platforms are reconfiguring the data sharing experience from a range of perspectives. We discuss which types of values, rights and responsibilities they entail and enshrine within their philosophy or outlook on what it means to share personal health information. Through this discussion we address issues of the design and the development process of personal health data and patient-oriented infrastructures, as well as new forms of technologically-mediated empowerment. (shrink)

Qual o lugar da filosofia nos dias atuais? Diante das inúmeras respostas possíveis a esta questão, nos debruçaremos em alguns tópicos que podemos inserir na chamada Ética Informacional, um ramo de investigação filosófico-interdisciplinar relativamente recente que discute problemas oriundos da relação ser humano/tecnologias digitais. Temas como privacidade informacional, arrogância epistêmica e divisão digital serão discutidos e relacionados, com o intuito de ilustrar o papel da filosofia na compreensão da complexidade inerente às dinâmicas sociais no contexto da sociedade da informação. Argumentaremos (...) que pensar o mundo contemporâneo a partir do viés da ética informacional se faz cada dia mais imprescindível para que possamos entrar em sintonia com as rápidas mudanças que a revolução informacional impõe à vida em sociedade e não sermos levados pelas enxurradas informacionais que presenciamos diariamente. (shrink)

Recently, there has been renewed interest in so-called evidence-based policy making. Enticed by the grand promises of Big Data, public officials seem increasingly inclined to experiment with more data-driven forms of governance. But while the rise of Big Data and related consequences has been a major issue of concern across different disciplines, attempts to develop a better understanding of the phenomenon's historical foundations have been rare. This short commentary addresses this gap by situating the current push for numerical evidence within (...) a broader socio-political context, demonstrating how the epistemological claims of Big Data science intersect with specific forms of trust, truth, and objectivity. We conclude by arguing that regulators' faith in numbers can be attributed to a distinct political culture, a representative democracy undermined by pervasive public distrust and uncertainty. (shrink)

In this paper, I critically evaluate several related, provocative claims made by proponents of data-intensive science and “Big Data” which bear on scientific methodology, especially the claim that scientists will soon no longer have any use for familiar concepts like causation and explanation. After introducing the issue, in Section 2, I elaborate on the alleged changes to scientific method that feature prominently in discussions of Big Data. In Section 3, I argue that these methodological claims are in tension with a (...) prominent account of scientific method, often called “Inference to the Best Explanation”. Later on, in Section 3, I consider an argument against IBE that will be congenial to proponents of Big Data, namely, the argument due to Roche and Sober Analysis, 73:659–668, that “explanatoriness is evidentially irrelevant.” This argument is based on Bayesianism, one of the most prominent general accounts of theory-confirmation. In Section 4, I consider some extant responses to this argument, especially that of Climenhaga Philosophy of Science, 84:359–368,. In Section 5, I argue that Roche and Sober’s argument does not show that explanatory reasoning is dispensable. In Section 6, I argue that there is good reason to think explanatory reasoning will continue to prove indispensable in scientific practice. Drawing on Cicero’s oft-neglected De Divinatione, I formulate what I call the “Ciceronian Causal-nomological Requirement”, which states, roughly, that causal-nomological knowledge is essential for relying on correlations in predictive inference. I defend a version of the CCR by appealing to the challenge of “spurious correlations,” chance correlations which we should not rely upon for predictive inference. In Section 7, I offer some concluding remarks. (shrink)

Slightly modified excerpt from the section 13.4 Zusammenfassung und Ausblick (translated into englisch): This chapter is based on an analysis of ethical debates on epigenetics and genome editing, debates, in which ethical arguments relating to future generations and justice play a central role. The analysis aims to contextualize new developments in genetic engineering, such as genome and epigenome editing, ethically. At the beginning, the assumptions of "genetic determinism," on which "genetic essentialism" is based, of "epigenetic determinism" as well as "genetic" (...) and "epigenetic exceptionalism" are analyzed and critically discussed. The remarks on the ethical discourse on epigenetics show that the notion of "epigenetic determinism" can sometimes be discerned not only in popular scientific discourse but also in ethical discourse. Ethical debates on epigenetics, however, have distanced themselves from this deterministic understanding. As a result, the focus in the ethical discourse on epigenetics shifts from responsibility for one's own health and that of subsequent generations to justice. What is meant here is justice, for example, in terms of access to healthy environmental conditions, regardless of whether these contribute to health with or without epigenetic agency. An analysis of the discourse on genome editing reveals that it is primarily germline interventions that are being ethically examined, with a concentration on the aspect of inheritance. The question is whether this is accompanied by an implicit "genetic determinism" or even a "genetic essentialism": the determinism could lie in the centrality of the aspect of heritability, since only genetic information is inherited. Does the aspect of heritability and genome modification play a more decisive role in debates on genome editing than the safety issue? Is the problem of embryos and their potential offspring not being able to consent to germline intervention given such a high priority because it is a genetic intervention? Under such a premise of "strong genetic determinism" supplemented by "epigenetic determinism," not only genome editing but also epigenome editing would be ethically relevant precisely because it too would have an influence on the genome. How this influence of genome editing and epigenome editing is ethically evaluated in each case therefore depends initially on whether the assumptions of "genetic" and "epigenetic determinism" are advocated. These assumptions are increasingly viewed critically in ethical discourse because they cannot be confirmed from a scientific perspective. In popular scientific debates in particular, however, they seem to persist, which ultimately also influences the public discussion. Since a broad public discussion is required especially on genome editing, a reflective approach to the various "-isms" analyzed in this chapter is central. DOI: 10.5771/9783748927242. (shrink)

In this paper, we examine how the availability of massive quantities of data i.e., the “Big Data” phenomenon, contributes to the creation, spread, and harms of online misinformation. Specifically, we argue that a factor in the problem of online misinformation is the evolved human instinct to recognize patterns. While the pattern-recognition instinct is a crucial evolutionary adaptation, we argue that in the age of Big Data, these capacities have, unfortunately, rendered us vulnerable. Given the ways in which online media outlets (...) profit from the spread of misinformation by preying on this pattern-finding instinct, we conceptualize the problem that we identify as a morally objectionable form of “epistemic exploitation.” As we argue, the consumer of digital misinformation is often exploited by having her pattern-recognition instinct used against her. This exploitation is morally objectionable because it deprives her of an epistemic good to which she has a right. This epistemic good is the integrity of the pattern-recognition instinct itself which, we argue, is a capacity that allows us to participate in uniquely human goods. While our primary goal is to bring attention to this form of epistemic exploitation, we conclude by briefly evaluating some general solutions to the growing problem of online misinformation. (shrink)

When radiocarbon dating techniques were applied to archaeological material in the 1950s they were hailed as a revolution. At last archaeologists could construct absolute chronologies anchored in temporal data backed by immutable laws of physics. This would make it possible to mobilize archaeological data across regions and time-periods on a global scale, rendering obsolete the local and relative chronologies on which archaeologists had long relied. As profound as the impact of 14C dating has been, it has had a long and (...) tortuous history now described as proceeding through three revolutions, each of which addresses distinct challenges of capturing, processing and packaging radiogenic data for use in resolving chronological puzzles with which archaeologists has long wrestled. In practice, mobilizing radiogenic data for archaeological use is a hard-won achievement; it involves multiple transformations that, at each step of the way, depend upon a diverse array of technical expertise and background knowledge. I focus on strategies of triangulation and traceability that establish the integrity of these data and their relevance as anchors for evidential reasoning in archaeology. (shrink)

The administrative reform of the datafied public administration places great emphasis on the classification, control, and prediction of citizen behavior and therefore has the potential to significantly impact citizen–state relations. There is a growing body of literature on data-oriented activism which aims to resist and counteract existing harmful data practices. However, little is known about the processes, policies, and political-economic structures that make datafication possible. There is a distinct research gap on situated and context-specific empirical research, which critically interrogates the (...) premises, interests, and agendas of data-driven public administration and how stakeholders can impact them. This paper therefore studies the conditions of participation in public administration datafication. It asks the overall research question of how citizens are problematized and included in policy and practitioner discourse in the datafication of public administration. The paper takes Norway as its case and applies Cardullo and Kitchin’s scaffold of smart citizen participation at the system level. It makes use of a unique empirical insight into the field, consisting of a survey, interviews, and an extensive document analysis. Unexpectedly, we find that citizens and civil society are rarely engaged in this administrative reform. Instead, we identify a paternalistic, top-down, technocratic approach where the context, values, and agendas of datafication are obscured from the citizen. (shrink)

This paper discusses the epistemic status of biology from the standpoint of the systemic approach to living systems based on the notion of biological autonomy. This approach aims to provide an understanding of the distinctive character of biological systems and this paper analyses its theoretical and epistemological dimensions. The paper argues that, considered from this perspective, biological systems are examples of emergent phenomena, that the biological domain exhibits special features with respect to other domains, and that biology as a discipline (...) employs some core concepts, such as teleology, function, regulation among others, that are irreducible to those employed in physics and chemistry. It addresses the claim made by Jacques Monod that biology as a science is marginal. It argues that biology is general insofar as it constitutes a paradigmatic example of complexity science, both in terms of how it defines the theoretical object of study and of the epistemology and heuristics employed. As such, biology may provide lessons that can be applied more widely to develop an epistemology of complex systems. (shrink)

This paper aims to contribute to the development of tools to support an analysis of Big Data as manifestations of social processes and human behaviour. Such a task demands both an understanding of the epistemological challenge posed by the Big Data phenomenon and a critical assessment of the offers and promises coming from the area of Big Data analytics. This paper draws upon the critical social and data scientists’ view on Big Data as an epistemological challenge that stems not only (...) from the sheer volume of digital data but, predominantly, from the proliferation of the narrow-technological and the positivist views on data. Adoption of the social-scientific epistemological stance presupposes that digital data was conceptualised as manifestations of the social. In order to answer the epistemological challenge, social scientists need to extend the repertoire of social scientific theories and conceptual frameworks that may inform the analysis of the social in the age of Big Data. However, an ‘epistemological revolution’ discourse on Big Data may hinder the integration of the social scientific knowledge into the Big Data analytics. (shrink)

This article argues that the self-management of one’s privacy is impossible due to privacy externalities. Privacy externalities are the negative by-product of the services offered by some data controllers, whereby the price to ‘pay’ for a service includes not just the provision of the user’s own personal data, but also that of others. This term, related to similar concepts from the literature on privacy such as ‘networked privacy’ or ‘data pollution’, is used here to bring to light the incentives and (...) exploitative dynamics behind a phenomenon which, I demonstrate, benefits both the user and the data controller to the detriment of third-party data subjects. Building on these novel elements and on the relevant concepts and examples found in the existing literature, this article draws a comprehensive picture of the phenomenon, and offers two promising paths to address it—better enforcing the principle of data protection by design and by default, and relying on the framework of joint controllership. (shrink)

This paper focuses on Precision Public Health (PPH), described in the scientific literature as an effort to broaden the scope of precision medicine by extrap- olating it towards public health. By means of the “All of Us” (AoU) research pro- gram, launched by the National Institutes of Health in the U.S., PPH is being devel- oped based on health data shared through a broad range of digital tools. PPH is an emerging idea to harness the data collected for precision medicine (...) to be able to tai- lor preventive interventions for at-risk groups. The character of these data concern genetic identity, lifestyle and overall health and therefore affect the ‘intimacy’ of personhood. Through the concept of biological citizenship, we elucidate how AoU and its recruitment tactics, by resonating ‘diversity’, at the same time appeal to and constitute identity, defining individuals as ‘data sharing subjects’. Although PPH is called for; the type of bio-citizenship that is enacted here, has a particular definition, where participant recruitment focuses on ‘citizenship’ in terms of empowerment (front), it is the ‘bio’ prefix that has become the main focus in terms of research. i.e. biosubjectivities vs biocapital. This raises the question whether the societal chal- lenges that often underlie public health issues can be sufficiently dealt with based on the way ‘diversity’ is accounted for in the program. We suggest that the AoU still risks of harming underrepresented groups based on the preconditions and the design of the program. (shrink)

Social practices of quantification, or the production and communication of numbers, have been recognized as important foundations of organizational knowledge, as well as sources of power. With the advent of increasingly sophisticated digital tools to capture and extract numerical data from social life, however, there is a pressing need to understand the ethical stakes of quantification. The current study examines quantification from an ethical lens, to frame and promote a research agenda around the ethics of quantification. After a brief overview (...) of quantification research and its uses in state and market organization, I discuss quantification in terms of three core subprocesses—capture, specification, and appropriation, illustrating and identifying ethical concerns around each process. Linking these processes to the performative effects of measures, I present a working model of quantification from which the discussion builds ideas for developing a research agenda around quantification. (shrink)

Although the Internet is frequently referred to as a global public resource, its functioning remains predominantly controlled by private actors. The Internet brought about significant shifts in the way we conceptualize governance. In particular, the handling of “big data” by private intermediaries has a direct impact on routine practices and personal lives. The implementation of the “right to be forgotten” following the May 2014 decision of the Court of Justice of the European Union against Google blurs the boundaries between the (...) public and the private, and extends the responsibilities of the latter to court-style decision making. This article analyzes the regulatory developments in this area and the implications of outsourcing of important governance practices to private intermediaries. It looks at the decision-making process for the “right to be forgotten” to illustrate the extent to which the hybridization of such procedures results in new arrangements between public and private ordering in Internet governance. (shrink)

In discussions on the ethics of genome collections and biobanks, the main worry about whether we are permitted to collect and use individuals’ genomic and genetic data is the potential for the violation of individuals’ right to informational privacy. Yet, if we do not permit these endeavors, we risk giving up on the future benefits of biomedical research. In this paper, I describe a private venture in blockchain genomics that seeks to provide an apt solution to concerns about potential privacy (...) violations in genome collections and biobanks. I then provide some reasons to doubt the kind of solution to the dilemma that such start-ups propose. I argue that the sort of autonomy that grounds the value of the right to informational privacy cannot be secured with blockchain technology alone. So, blockchain genomics ventures are insufficient to establish the permissibility of genome collections and biobanks. I then discuss an additional ethical challenge to genomic biobanks. This challenge takes the form of doubting that future benefits that result from biomedical research dependent on genomic databases will outweigh the costs. Despite criticisms of genomic research, I claim that it is reasonable to think that future net benefits will be gained from research on such databases. Therefore, I conclude that there remains a dilemma in the ethics of genomic biobanks. (shrink)

Many actors mobilize the cognitive, legal and technical tool-box of data protection when they discuss and address controversial issues such as digital mass surveillance. Yet, critical approaches to the digital only barely explore the politics of data protection in relation to data-driven governance. Building on governmentality studies and Actor-Network-Theory, this article analyses the potential and limits of using data protection to critique the ‘digital age’. Using the conceptual tool of dispositifs, it sketches an analytics of data protection and the emergence (...) of its configuration as ‘data protection by design and by default’. This exploration reminds us that governing through data implies, first and foremost, governing digital data. (shrink)