Bold approaches to data collection and large-scale quantitative advances have long been a preoccupation for social science researchers. In this commentary we further debate over the use of large-scale survey data and official statistics with ‘Big Data’ methodologists, and emphasise the ability of these resources to incorporate the essential social and cultural heredity that is intrinsic to the human sciences. In doing so, we introduce a series of new data-sets that integrate approximately 30 years of survey data on victimisation, fear (...) of crime and disorder and social attitudes with indicators of socio-economic conditions and policy outcomes in Britain. The data-sets that we outline below do not conform to typical conceptions of ‘Big Data’. But, we would contend, they are ‘big’ in terms of the volume, variety and complexity of data which has been collated and ‘big’ also in that they allow us to explore key questions pertaining to how social and economic policy change at the national level alters the attitudes and experiences of citizens. Importantly, they are also ‘small’ in the sense that the task of rendering the data usable, linking it and decoding it, required both manual processing and tacit knowledge of the context of the data and intentions of its creators. (shrink)

This article presents a conceptual investigation into the value impacts and relations of algorithms in the domain of justice and security. As a conceptual investigation, it represents one step in a value sensitive design based methodology. Here, we explicate and analyse the expression of values of accuracy, privacy, fairness and equality, property and ownership, and accountability and transparency in this context. We find that values are sensitive to disvalue if algorithms are designed, implemented or deployed inappropriately or without sufficient consideration (...) for their value impacts, potentially resulting in problems including discrimination and constrained autonomy. Furthermore, we outline a framework of conceptual relations of values indicated by our analysis, and potential value tensions in their implementation and deployment with a view towards supporting future research, and supporting the value sensitive design of algorithms in justice and security. (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)

Cybervetting has become common practice in personnel decision-making processes of organizations. While it represents a quick and inexpensive way of obtaining additional information on employees and applicants, it gives rise to a variety of legal and ethical concerns. To limit companies’ access to personal information, a _right to be forgotten_ has been introduced by the European jurisprudence. By discussing the notion of forgetting from the perspective of French hermeneutic philosopher Paul Ricoeur, the present article demonstrates that both, companies and employees, (...) would be harmed if access to online information on applicants and current employees would be denied. Consistent with a Humanistic Management approach that promotes human dignity and flourishing in the workplace, this article proposes guidance for the responsible handling of unpleasant online memories in personnel decision-making processes, thereby following Ricoeur’s notion of forgetting as “kept in reserve”. Enabling applicants and employees to take a qualified stand on their past is more beneficial to both sides than a right to be forgotten that is questionable in several respects. (shrink)

This paper draws together empirical findings from our study of hackathons in the UK with literature on big data through three interconnected frameworks: data as discourse, data as datalogical and data as materiality. We suggest not only that hackathons resonate the wider socio-technical and political constructions of data that are currently enacted in policy, education and the corporate sector, but also that an investigation of hackathons reveals the extent to which ‘data’ operates as a powerful discursive tool; how the discourses (...) of data mask and reveal a series of tropes pertaining to data; that the politics of data are routinely and simultaneously obscured and claimed with serious implications for expertise and knowledge; and that ultimately, and for the vast majority of hackathons we have attended, the discursive and material constructions of data serve to underpin rather than challenge existing power relations and politics. (shrink)

La filosofía de la comunicación del siglo XX aceptó, en términos generales, la teoría de la agenda-setting propuesta por McCombs y Shaw (1972). Esta teoría subrayaba la capacidad de los medios de comunicación de masas para configurar la comprensión que el gran público tiene de la realidad social (Wolf, 1987). Sin embargo, Internet y las redes sociales han cambiado radicalmente el panorama, puesto que los grandes medios de comunicación tradicionales van ahora a remolque de lo que es trending-topic en las (...) redes. Este artículo señala la necesidad de desarrollar una nueva filosofía de la comunicación, adaptada a la existencia de un nuevo marco (frame) tecnológico y social, que redefina los patrones y los factores que configuran actualmente la agenda pública (agenda-setting 2.0). (shrink)

The exponential accumulation, processing and accrual of big data in healthcare are only possible through an equally rapidly evolving field of big data analytics. The latter offers the capacity to rationalize, understand and use big data to serve many different purposes, from improved services modelling to prediction of treatment outcomes, to greater patient and disease stratification. In the area of infectious diseases, the application of big data analytics has introduced a number of changes in the information accumulation models. These are (...) discussed by comparing the traditional and new models of data accumulation. Big data analytics is fast becoming a crucial component for the modelling of transmission—aiding infection control measures and policies—emergency response analyses required during local or international outbreaks. However, the application of big data analytics in infectious diseases is coupled with a number of ethical impacts. Four key areas are discussed in this paper: automation and algorithmic reliance impacting freedom of choice, big data analytics complexity impacting informed consent, reliance on profiling impacting individual and group identities and justice/fair access and increased surveillance and population intervention capabilities impacting behavioural norms and practices. Furthermore, the extension of big data analytics to include information derived from personal devices, such as mobile phones and wearables as part of infectious disease frameworks in the near future and their potential ethical impacts are discussed. Considered together, the need for a constructive and transparent inclusion of ethical questioning in this rapidly evolving field becomes an increasing necessity in order to provide a moral foundation for the societal acceptance and responsible development of the technological advancement. (shrink)

The advent of extremely large data sets, known as “big data,” has been heralded as the instantiation of a new science, requiring a new kind of practitioner: the “data scientist.” This article explores the concept of big data, drawing attention to a number of new issues—not least ethical concerns, and questions surrounding interpretation—which big data sets present. It is observed that the skills required for data scientists are in some respects closer to those traditionally associated with the arts and humanities (...) than to those associated with the natural sciences; and it is urged that big data presents new opportunities for dialogue, especially concerning hermeneutical issues, for theologians and data scientists. (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)

Metrics have long served as tools for governing at a distance. In the food industry, major manufacturers have embraced metrics as tools to govern the sustainability of the farms producing their commodity raw materials. This metrical turn has been influenced but also complicated by agricultural datafication, that is, the increasing quantities of data generated on and about farms. Despite the sheer abundance of data that companies might use to measure and drive improvement in on-farm sustainability, they have struggled to collect (...) data suitable for such purposes. Attention to the different kinds of distance and diversity across which metrics are supposed to govern suggests reasons why they may fail to do so, even when wielded by otherwise powerful corporations. (shrink)

Today's modern car is an assemblage of mechanical and digital components, of metal panels that comprise its structure and silicon chips that run its functions. Communication and information studies scholars have interrogated the problematic aspects of the programs that run those functions, revealing serious issues surrounding privacy and security, worker surveillance, and racial, gendered, and class-based bias. This article contributes to that work by taking a step back and asking about the issues inherent not in the software running on these (...) chips, but on the microchips themselves. Using the lens of “chipification”—the process by which a device is rendered capable of reading and processing data through the embedding of microchips—this article explores how the integration of microchips also involves processes that are often borne from, replicate, or create troubling power dynamics of their own. It takes light-duty passenger vehicles as a case study into how chipification is radically reshaping such processes as resource allocation, labor flows, and cultural practices around car manufacture, use, repair, and modification. By naming the process of chipification, this article allows researchers to identify and analyze the ways that integrating data processing capabilities into everyday devices is not a frictionless practice, but rather one that implicates a variety of power dynamics within these massive industries. (shrink)

Although true in some aspects, the suggested characterization of today’s science as a dichotomy between traditional science and data-driven science misses some of the nuance, complexity, and possibility that exists between the two positions. Part of the problem is the claim that Data Science works without theories. There are many theories behind the data that are used in science. However, for data science, the only theories that matter are those in mathematics, statistics, and computer science. In this conceptual paper, we (...) add two other philosophy of science tenets, experiments and data, to the discussion to create a more nuanced view of how data science uses theories. Following Ihde’s concept of technoscience and the incessant quest for more precision, magnification, and resolution, we argue that technology-driven science created a need for more technology-driven science, culminating in data science. Further, we adapt Hacking and Galison’s views on physics to argue that data science is also an experimental science, which uses data objects in experiments. Drawing from Heelan, we called these objects “data-objects-for-knowing”. Finally, we conclude that data science is a science to study artificially created phenomena—a science to study the data manipulated by the equations and operations of AI. It disregards the connections between data and the real world that were carefully built by the theories from other sciences. In the experiments of data science, data are the world itself. The knowledge created by data science is purposely disconnected from any theory from other sciences; it is a knowledge for the sake of itself. (shrink)

While we witness a growing belief in transparency as an ideal solution to a wide range of societal problems, we know less about the practical workings of transparency as it guides conduct in organizational and regulatory settings. This article argues that transparency efforts involve much more than the provision of information and other forms of ‘sunlight’, and are rather a matter of managing visibilities than providing insight and clarity. Building on actor-network theory and Foucauldian governmentality studies, it calls for careful (...) attention to the ways in which transparency ideals are translated into more situated practices and become associated with specific organizational and regulatory concerns. The article conceptualizes transparency as a force that shapes conduct in organizational and socio-political domains. In the second section, this conceptualization of transparency as a form of ‘ordering’ is substantiated further by using illustrations of the effects of transparency efforts in the internet domain. (shrink)

BackgroundSystems medicine is the name for an assemblage of scientific strategies and practices that include bioinformatics approaches to human biology ; “big data” statistical analysis; and medical informatics tools. Whereas personalized and precision medicine involve similar analytical methods applied to genomic and medical record data, systems medicine draws on these as well as other sources of data. Given this distinction, the clinical translation of systems medicine poses a number of important ethical and epistemological challenges for researchers working to generate systems (...) medicine knowledge and clinicians working to apply it.DiscussionThis article focuses on three key challenges: First, we will discuss the conflicts in decision-making that can arise when healthcare providers committed to principles of experimental medicine or evidence-based medicine encounter individualized recommendations derived from computer algorithms. We will explore in particular whether controlled experiments, such as comparative effectiveness trials, should mediate the translation of systems medicine, or if instead individualized findings generated through “big data” approaches can be applied directly in clinical decision-making. Second, we will examine the case of the Riyadh Intensive Care Program Mortality Prediction Algorithm, pejoratively referred to as the “death computer,” to demonstrate the ethical challenges that can arise when big-data-driven scoring systems are applied in clinical contexts. We argue that the uncritical use of predictive clinical algorithms, including those envisioned for systems medicine, challenge basic understandings of the doctor-patient relationship. Third, we will build on the recent discourse on secondary findings in genomics and imaging to draw attention to the important implications of secondary findings derived from the joint analysis of data from diverse sources, including data recorded by patients in an attempt to realize their “quantified self.”SummaryThis paper examines possible ethical challenges that are likely to be raised as systems medicine to be translated into clinical medicine. These include the epistemological challenges for clinical decision-making, the use of scoring systems optimized by big data techniques and the risk that incidental and secondary findings will significantly increase. While some ethical implications remain still hypothetical we should use the opportunity to prospectively identify challenges to avoid making foreseeable mistakes when systems medicine inevitably arrives in routine care. (shrink)

As Artificial Intelligence technology seems poised for a major take-off and changing societal dynamics are creating a high demand for caregivers for elders, children and those infirmed-robotic caregivers, may well be used much more often. This article examines the ethical concerns raised by the use of AI caregivers and concludes that many of these concerns are avoided when AI caregivers operate as partners rather than substitutes. Furthermore, most of the remaining concerns are minor and are faced by human caregivers as (...) well. Nonetheless, because AI caregivers’ systems are learning systems, an AI caregiver could stray from its initial guidelines. Therefore, subjecting AI caregivers to an AI-based oversight system is proposed to ensure that their actions remain both legal and ethical. (shrink)

The debate on the right to be forgotten on Google involves the relationship between human information processing and digital processing by algorithms. The specificity of digital memory is not so much its often discussed inability to forget. What distinguishes digital memory is, instead, its ability to process information without understanding. Algorithms only work with data without remembering or forgetting. Merely calculating, algorithms manage to produce significant results not because they operate in an intelligent way, but because they “parasitically” exploit the (...) intelligence, the memory, and the attribution of meaning by human actors. The specificity of algorithmic processing makes it possible to bypass the paradox of remembering to forget, which up to now blocked any human-based forgetting technique. If you decide to forget some memory, the most immediate effect is drawing attention to it, thereby activating remembering. Working differently from human intelligence, however, algorithms can implement, for the first time, the classical insight that it might be possible to reinforce forgetting not by erasing memories but by multiplying them. After discussing several projects on the web which implicitly adopt this approach, the article concludes by raising some deeper problems posed when algorithms use data and metadata to produce information that cannot be attributed to any human being. (shrink)

This article adapts the ethnographic medium of the diary to develop a method for studying data and related data practices. The article focuses on the creation of one data diary, developed iteratively over three years in the context of a national centre for monitoring disasters and natural hazards in Brazil. We describe four points of focus involved in the creation of a data diary – spaces, interfaces, types and situations – before reflecting on the value of this method. We suggest (...) data diaries are able to capture the informal dimension of data-intensive organisations; enable empirical analysis of the specific ways that data intervene in the unfolding of situations; and as a document, data diaries can foster interdisciplinary and inter-expert dialogue by bridging different ways of knowing data. (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)

Experimental design is one aspect of a scientific method. A well-designed, properly conducted experiment aims to control variables in order to isolate and manipulate causal effects and thereby maximize internal validity, support causal inferences, and guarantee reliable results. Traditionally employed in the natural sciences, experimental design has become an important part of research in the social and behavioral sciences. Experimental methods are also endorsed as the most reliable guides to policy effectiveness. Through a discussion of some of the central concepts (...) associated with experimental design, including controlled variation and randomization, this chapter will provide a summary of key ethical issues that tend to arise in experimental contexts. In addition, by exploring assumptions about the nature of causation and by analyzing features of causal relationships, systems, and inferences in social contexts, this chapter will summarize the ways in which experimental design can undermine the integrity of not only social and behavioral research but policies implemented on the basis of such research. (shrink)

Higher education institutions are mining and analyzing student data to effect educational, political, and managerial outcomes. Done under the banner of “learning analytics,” this work can—and often does—surface sensitive data and information about, inter alia, a student’s demographics, academic performance, offline and online movements, physical fitness, mental wellbeing, and social network. With these data, institutions and third parties are able to describe student life, predict future behaviors, and intervene to address academic or other barriers to student success (however defined). Learning (...) analytics, consequently, raise serious issues concerning student privacy, autonomy, and the appropriate flow of student data. We argue that issues around privacy lead to valid questions about the degree to which students should trust their institution to use learning analytics data and other artifacts (algorithms, predictive scores) with their interests in mind. We argue that higher education institutions are paradigms of information fiduciaries. As such, colleges and universities have a special responsibility to their students. In this article, we use the information fiduciary concept to analyze cases when learning analytics violate an institution’s responsibility to its students. (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)

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)

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)

Big Data must be processed with advanced collection and analysis tools, based on predetermined algorithms, in order to obtain relevant information. Algorithms must also take into account invisible aspects for direct perceptions. Big Data issues is multi-layered. A distributed parallel architecture distributes data on multiple servers (parallel execution environments) thus dramatically improving data processing speeds. Big Data provides an infrastructure that allows for highlighting uncertainties, performance, and availability of components. DOI: 10.13140/RG.2.2.12784.00004 .

Le terme big data désigne l'extraction, la manipulation et l'analyse des ensembles de données trop volumineux pour être traités de manière routinière. Pour cette raison, des logiciels spéciaux sont utilisés et, dans de nombreux cas, des ordinateurs et du matériel informatiques dédiés. Généralement, ces données sont analysées de manière statistique. Les données doivent être traitées avec des outils de collecte et d'analyse avancés, basés sur des algorithmes prédéterminés, afin d'obtenir des informations pertinentes. Les algorithmes doivent également prendre en compte les (...) aspects invisibles pour les perceptions directes. DOI: 10.13140/RG.2.2.19453.51684 . (shrink)

Proponents of the emerging field of P4 medicine argue that computational integration and analysis of patient-specific “big data” will revolutionize our health care systems, in particular primary care-based disease prevention. While many ambitions remain visionary, steps to personalize medicine are already taken via personalized genomics, mobile health technologies and pilot projects. An important aim of P4 medicine is to enable disease prevention among healthy persons through detection of risk factors. In this paper, we examine the current status of P4 medicine (...) in light of historical and current challenges to predictive and preventive medicine, including overdiagnosis and overtreatment. Moreover, we ask whether it is likely that in silico integration of patient-specific data will be able to better deal such challenges and to turn risk predictions into disease-preventive actions in a wider social context. Given the lack of evidence that P4 medicine can tip the balance between benefits and harms in preventive medicine, we raise concerns about the current promotion of P4 medicine as a solution to the current challenges in public health. (shrink)

Proponents of the emerging field of P4 medicine argue that computational integration and analysis of patient-specific “big data” will revolutionize our health care systems, in particular primary care-based disease prevention. While many ambitions remain visionary, steps to personalize medicine are already taken via personalized genomics, mobile health technologies and pilot projects. An important aim of P4 medicine is to enable disease prevention among healthy persons through detection of risk factors. In this paper, we examine the current status of P4 medicine (...) in light of historical and current challenges to predictive and preventive medicine, including overdiagnosis and overtreatment. Moreover, we ask whether it is likely that in silico integration of patient-specific data will be able to better deal such challenges and to turn risk predictions into disease-preventive actions in a wider social context. Given the lack of evidence that P4 medicine can tip the balance between benefits and harms in preventive medicine, we raise concerns about the current promotion of P4 medicine as a solution to the current challenges in public health. (shrink)

Principalele probleme cu care se confruntă oamenii de știință în lucrul cu seturile mari de date (Big Data), evidențiind principale aspecte etice, luând în considerare inclusiv legislația din Uniunea Europeană. După o scurtă Introducere despre Big Data, secțiunea Tehnologia prezintă aplicațiile specifice în cercetare. Urmează o abordare a principalelor probleme filosofice specifice în Aspecte filosofice, și Aspecte legale cu evidențierea problemelor etice specifice din Regulamentul UE privind protecția datelor 2016/679 (General Data Protection Regulation, "GDPR"). Secțiunea Probleme etice detaliază aspectele specifice (...) generate de Big Data. După o scurtă secțiune Cercetarea Big Data, finalizez lucrarea cu prezentarea Concluziilor pentru etica cercetării în lucrul cu Big CUPRINS: Abstract 1. Introducere - 1.1 Definiții - 1.2 Dimensiunile Big Data 2. Tehnologia - 2.1 Aplicații - - 2.1.1 În cercetare 3. Aspecte filosofice 4 Aspecte legale - 4.1 GDPR - - Etapele procesării datelor personale - - Principiile procesării datelor - - Politica de confidențialitate și transparența - - Scopurile procesării datelor - - Confidențialitate prin design și implicită - - Paradoxul (legal) al Big Data 5. Probleme etice - Etica în cercetare - Conștientizarea - Consimțământul - Controlul - Transparența - Încrederea - Proprietatea - Supravegherea și securitatea - Identitatea digitală - Realitatea ajustată - De-anonimizarea - Inegalitatea digitală - Confidențialitatea 6. Cercetarea Big Data Concluzii Bibliografie DOI: 10.13140/RG.2.2.27629.33761 . (shrink)