In spite of advances in medicine and public health, malaria and other mosquito‐borne diseases are on the rise worldwide. Although vaccines, genetically modified mosquitoes and safer insecticides are under development, herein we examine a promising new approach to malaria control through better repellents. Current repellents, usually based on DEET, inhibit host finding by impeding insect olfaction, but have significant drawbacks. We discuss how comparative genomics, using data from the Anopheles genome project, allows the rapid identification of members of three (...) protein classes critical to insect olfaction: odorant‐binding proteins, G‐protein‐coupled receptors, and odorant‐degrading enzymes. A rational design approach similar to that used by the pharmaceutical industry for drug development can then be applied to the development of products that interfere with mosquito olfaction. Such products have the potential to provide more complete, safer and longer lasting protection than conventional repellents, preventing disease transmission by interrupting the parasite life cycle. BioEssays 25:1011–1020, 2003. © 2003 Wiley Periodicals, Inc. (shrink)

The Snowden leaks, first published in June 2013, provided unprecedented insights into the operations of state-corporate surveillance, highlighting the extent to which everyday communication is integrated into an extensive regime of control that relies on the ‘datafication’ of social life. Whilst such data-driven forms of governance have significant implications for citizenship and society, resistance to surveillance in the wake of the Snowden leaks has predominantly centred on techno-legal responses relating to the development and use of encryption and policy advocacy (...) around privacy and data protection. Based on in-depth interviews with a range of social justice activists, we argue that there is a significant level of ambiguity around this kind of anti-surveillance resistance in relation to broader activist practices, and critical responses to the Snowden leaks have been confined within particular expert communities. Introducing the notion of ‘data justice’, we therefore go on to make the case that resistance to surveillance needs to be conceptualized on terms that can address the implications of this data-driven form of governance in relation to broader social justice agendas. Such an approach is needed, we suggest, in light of a shift to surveillance capitalism in which the collection, use and analysis of our data increasingly comes to shape the opportunities and possibilities available to us and the kind of society we live in. (shrink)

Educational institutions increasingly rely on digital platforms to deliver content and learning, monitor attendance, communicate with stakeholders, and evaluate institutional performance. Despite the efficiency and accessibility gains they offer, digital platforms are powered by personal data which, through a process of datafication, can be used to track, monitor, and profile staff and students. The insights drawn from this data can be used to shape educational and professional futures. This article examines how datafication has become a social justice (...) issue in education, discussing the implications for well-being, decision-making, governance, and power in education. Using Hintz and colleagues framework for data justice, it applies and explores the three dimensions of data justice to the context of education, including: (1) infrastructures (2) regulation, and (3) informed and knowledgeable stakeholders. The paper discusses the unique challenges to achieving data justice in education and concludes by outlining the key questions for a future research agenda. (shrink)

The advent of artificial intelligence (AI) challenges political theorists to think about data ownership and policymakers to regulate the collection and use of public data. AI producers benefit from free public data for training their systems while retaining the profits. We argue against the view that the use of public data must be free. The proponents of unconstrained use point out that consuming data does not diminish its quality and that information is in ample supply. (...) Therefore, they suggest, publicly available data should be free. We present two objections. First, allowing free data use promotes unwanted inequality. Second, contributors of information did not and could not anticipate that their contribution would be used to train AI systems. Therefore, charging for extensive data use is pro tanto permissible and desirable. We discuss policy implications and propose a progressive data use tax to counter the inequality arising. (shrink)

Volume 20, Issue 10, October 2020, Page 32-33.

The increasing availability of digital data reflecting economic and human development, and in particular the availability of data emitted as a by-product of people’s use of technological devices and services, has both political and practical implications for the way people are seen and treated by the state and by the private sector. Yet the data revolution is so far primarily a technical one: the power of data to sort, categorise and intervene has not yet been explicitly (...) connected to a social justice agenda by the agencies and authorities involved. Meanwhile, although data-driven discrimination is advancing at a similar pace to data processing technologies, awareness and mechanisms for combating it are not. This paper posits that just as an idea of justice is needed in order to establish the rule of law, an idea of data justice – fairness in the way people are made visible, represented and treated as a result of their production of digital data – is necessary to determine ethical paths through a datafying world. Bringing together the emerging scholarly perspectives on this topic, I propose three pillars as the basis of a notion of international data justice: visibility, engagement with technology and antidiscrimination. These pillars integrate positive with negative rights and freedoms, and by doing so challenge both the basis of current data protection regulations and the growing assumption that being visible through the data we emit is part of the contemporary social contract. (shrink)

Background Bioethical debates about privacy, big data, and public health surveillance have not sufficiently engaged the perspectives of those being surveilled. The data justice framework suggests that big data applications have the potential to create disproportionate harm for socially marginalized groups. Using examples from our research on HIV surveillance for individuals incarcerated in jails, we analyze ethical issues in deploying big data in public health surveillance. -/- Methods We conducted qualitative, semi-structured interviews with 24 people (...) living with HIV who had been previously incarcerated in county jails about their perspectives on and experiences with HIV surveillance, as part of a larger study to characterize ethical considerations in leveraging big data techniques to enhance continuity of care for incarcerated people living with HIV. -/- Results Most participants expressed support for the state health department tracking HIV testing results and viral load data. Several viewed HIV surveillance as a violation of privacy, and several had actively avoided contact from state public health outreach workers. Participants were most likely to express reservations about surveillance when they viewed the state’s motives as self-interested. Perspectives highlight the mistrust that structurally vulnerable people may have in the state’s capacity to act as an agent of welfare. Findings suggest that adopting a nuanced, context-sensitive view on surveillance is essential. -/- Conclusions Establishing trustworthiness through interpersonal interactions with public health personnel is important to reversing historical legacies of harm to racial minorities and structurally vulnerable groups. Empowering stakeholders to participate in the design and implementation of data infrastructure and governance is critical for advancing a data justice agenda, and can offset privacy concerns. The next steps in advancing the data justice framework in public health surveillance will be to innovate ways to represent the voices of structurally vulnerable groups in the design and governance of big data initiatives. (shrink)

The proliferation of personal data collection practices fundamentally reshapes how society is ordered and commercialized, and demands reconsideration of the possibilities for a just and equitable s...

Diffusions in Architecture: Artificial Intelligence and Image Generators delves into the impact of Diffusion AI algorithms and generative image models on architecture design and aesthetics. The book presents an in-depth analysis of how these new technologies are revolutionizing the field of architecture. The architects presented in the book focus on the application of specific AI techniques and tools used in generative design, such as Diffusion models, Dall-E2, Stable Diffusion, and MidJourney. It discusses how these techniques can generate synthetic images that (...) are both realistic and imaginative, creating new possibilities for architectural design and aesthetics. This comprehensive overview of the impact of Diffusion AI algorithms and generative image models on the field of architecture shows how they are changing the way architects approach their work. With a foreword by Lev Manovich—artist, writer and one of the world's most influential digital culture theorists. Sharing the work and insights of a team of designers and theorists from a range of backgrounds, offering disciplinary depth, and covering the full impact of these tools and models on architecture, Diffusions in Architecture includes information on: Fresh perspectives on design and aesthetics, with designs, images, and commentary from 22 leading architects, theorists, and designersThe potential of prompt engineering and text-to-image models applicable to a broad interdisciplinary audienceWhether image generators, or AI in general, will be an aid for human design, or potentially displace humans from the market fundamentals of a larger debate in the architectural discourse (and practice) on the use of image generatorsCollecting the different ideas that have emerged in the field, Diffusions in Architecture provides architects, designers, concept artists, and theorists with an overview of this cornucopia of architectural imaginations produced in a common effort between humans and artificial intelligence. (shrink)

Purpose This study aims to develop an interdisciplinary political theory of data justice by connecting three major political theories of the public good with empirical studies about the functions of big data and offering normative principles for restricting and guiding the state’s data practices from a public good perspective. Design/methodology/approach Drawing on three major political theories of the public good – the market failure approach, the basic rights approach and the democratic approach – and critical (...) class='Hi'>data studies, this study synthesizes existing studies on the promises and perils of big data for public good purposes. The outcome is a conceptual paper that maps philosophical discussions about the conditions under which the state has a legitimate right to collect and use big data for public goods purposes. Findings This study argues that market failure, basic rights protection and deepening democracy can be normative grounds for justifying the state’s right to data collection and utilization, from the perspective of political theories of the public good. The state’s data practices, however, should be guided by three political principles, namely, the principle of transparency and accountability; the principle of fairness; and the principle of democratic legitimacy. The paper draws on empirical studies and practical examples to explicate these principles. Originality/value Bringing together normative political theory and critical data studies, this study contributes to a more philosophically rigorous understanding of how and why big data should be used for public good purposes while discussing the normative boundaries of such data practices. (shrink)

The inclusion of members of structurally marginalized communities in data-intensive innovation initiatives, such as precision medicine projects, is an urgent contemporary issue. On the one hand, th...

This paper argues that data-driven medicine gives rise to a particular normative challenge. Against the backdrop of a distinction between the good and the right, harnessing personal health data towards the development and refinement of data-driven medicine is to be welcomed from the perspective of the good. Enacting solidarity drives progress in research and clinical practice. At the same time, such acts of sharing could—especially considering current developments in big data and artificial intelligence—compromise the right by (...) leading to injustices and affecting concrete modes of individual self-determination. In order to address this potential tension, two key elements for ethical reflection on data-driven medicine are proposed: the controllability of information flows, including technical infrastructures that are conducive towards controllability, and a paradigm shift towards output-orientation in governance and policy. (shrink)

Reporters' use of government data bases can create problems with serving justice and maintaining privacy. Although there are many advantages to the new reporting tool, problems can arise when the information is inaccurate or is misused for purposes other than originally intended. The ethical question of maintaining privacy while ful-filling the political function of the media is discussed. Suggested guidelines are given.

In this work, Carol V.A. Quinn considers survivors’ arguments in the debate concerning the ethics of using Nazi medical data, showing what it would mean to take their claims seriously. Her approach is interdisciplinary, incorporating philosophy, psychology, trauma research, survivors’ testimony, Holocaust poetry, literature, and the Hebrew Bible.

A growing body of research emphasises the role of ‘social determinants of health’ in generating inequalities in health outcomes. How, if at all, should primary care providers respond? In this paper, I want to shed light on this issue by focusing on the role that ‘big data’ might play in allowing primary care providers to respond to the social determinants that affect individual patients’ health. The general idea has been proposed and endorsed by the Institute of Medicine, and the (...) idea has been developed in more detail by Bazemore et al.. In Bazemore et al.’s proposal, patients’ addresses are used to generate information about the patients’ neighbourhood; this information is then included in patients’ health care records and made available to providers. This allows primary care providers to take this information into account when interacting with, and providing care to, patients. I explore three issues arising from this proposal. First, while questions of privacy have been central to discussions about big data, Bazemore et al.’s proposal also allows us to see that there might be costs to not making certain information available. Second, I consider some of the questions arising for primary care from the influence of social factors on health outcomes: given that we know these factors to be significant contributors to social inequalities in health, what precisely should be done about this in the primary care context? Finally, I address problems arising from the use of population level data when dealing with individuals. (shrink)

This paper argues for subsuming the question of open data within a larger question of information justice, with the immediate aim being to establish the need for rather than the principles of such a theory. I show that there are several problems of justice that emerge as a consequence of opening data to full public accessibility, and are generally a consequence of the failure of the open data movement to understand the constructed nature of (...) class='Hi'>data. I examine three such problems: the embedding of social privilege in datasets as the data is constructed, the differential capabilities of data users, and the norms that data systems impose through their function as disciplinary systems. In each case I show that open data has the quite real potential to exacerbate rather than alleviate injustices. This necessitates a theory of information justice. I briefly suggest two complementary directions in which such a theory might be developed: one defining a set of moral inquiries that can be used to evaluate the justness of data practices, and another exploring the practices and structures that a social movement promoting information justice might pursue. (shrink)

This paper explores the politics of representing events in the world in the form of data points, data sets, or data associations. Data collection involves an act of seeing and recording something that was previously hidden and possibly unnamed. The incidences included in a data set are not random or unrelated but stand for coherent, classifiable phenomena in the world. Moreover, for data to have an impact on law and policy, such information must be (...) seen as actionable, that is, the aggregated data must show people both something they can perceive and something that demands interrogation, explanation, or resolution. Actionable data problematize the taken-for-granted order of society by pointing to questions or imbalances that can be corrected or rectified, or simply better understood, through systematic compilations of occurrences, frequencies, distributions, or correlations. The paper describes and analyzes three different modes of authorized seeing that render data on global environmental phenomena such as climate change both visible and actionable. It argues that the political force of environmental data compilations derives from the divergent epistemological standpoints and expert practices associated with producing views from nowhere, everywhere, and somewhere. (shrink)

The potential to collect brain data more directly, with higher resolution, and in greater amounts has heightened worries about mental and brain privacy. In order to manage the risks to individuals posed by these privacy challenges, some have suggested codifying new privacy rights, including a right to “mental privacy.” In this paper, we consider these arguments and conclude that while neurotechnologies do raise significant privacy concerns, such concerns are—at least for now—no different from those raised by other well-understood (...) class='Hi'>data collection technologies, such as gene sequencing tools and online surveillance. To better understand the privacy stakes of brain data, we suggest the use of a conceptual framework from information ethics, Helen Nissenbaum’s “contextual integrity” theory. To illustrate the importance of context, we examine neurotechnologies and the information flows they produce in three familiar contexts—healthcare and medical research, criminal justice, and consumer marketing. We argue that by emphasizing what is distinct about brain privacy issues, rather than what they share with other data privacy concerns, risks weakening broader efforts to enact more robust privacy law and policy. (shrink)

This article discusses the notion of justice from a capabilities approach. We undertake an empirical analysis of the concepts of justice held by healthcare personnel, gleaned from a qualitative analysis of interviews on the subject of ethical dilemmas in everyday practice. The article states that Justice undoubtedly presents a work in progress, which implicates the link between justice as capability and human dignity.We empirically found a contrast between the views of justice based on the patient's (...) own perceptions and those based on the perceptions of healthcare personnel. We establish the kind of actions, communication skills and justice required to build a stronger relationship between patients and healthcare professionals, which would improve prognosis, treatment efficiency and therapeutic adhesion. (shrink)

This article discusses the notion of justice from a capabilities approach. We undertake an empirical analysis of the concepts of justice held by healthcare personnel, gleaned from a qualitative analysis of interviews on the subject of ethical dilemmas in everyday practice. The article states that Justice undoubtedly presents a work in progress, which implicates the link between justice as capability and human dignity. We empirically found a contrast between the views of justice based on the (...) patient's own perceptions and those based on the perceptions of healthcare personnel. We establish the kind of actions, communication skills and justice required to build a stronger relationship between patients and healthcare professionals, which would improve prognosis, treatment efficiency and therapeutic adhesion. (shrink)

Much bioethical literature and policy guidances for big data analytics in biomedical research emphasize the importance of trust. It is essential that potential participants trust so they will allow their data to be used to further research. However, comparatively, little guidance is offered as to what trustworthy oversight mechanisms are, or how policy should support them, as data are collected, shared, and used. Generally, “trust” is not characterized well enough, or meaningfully enough, for the term to be (...) systematically applied in policy development. Yet points made in the philosophical literature on trust can help. They allow us, not only to better distinguish the different ways the term “trust” may be interpreted, but also to better determine how different approaches to trust can align with policy and governance—in what ways they may relate to key bioethical concepts and related laws, and in what ways they can help to balance individual and group interests in data sharing. This article draws from the philosophical literature on trust to identify a relationship among consent, trust, and justice. Specifically, parallels are drawn between “character-trustworthiness” and “natural justice,” a set of widely held legal safeguards intended to ensure decision-makers follow a pattern of procedural fairness which protects the rights of the individual and thereby maintains public confidence in the decision-making process. Relevance to traditional bioethical principles, established laws, and consent procedures are addressed throughout. In conclusion, policy actions are suggested. (shrink)

It is held that absolute poverty causes approximately one third of all human deaths, some 18 million annually, and blights billions of lives with hunger and disease. This book develops universalizable norms aimed at tackling absolute poverty and the complex and multilayered problems associated with it.

Over the last decade, humans have produced each year as much data as were produced throughout the entire history of humankind. These data, in quantities that exceed current analytical capabilities, have been described as “the new oil,” an incomparable source of value. This is true for healthcare, as well. Conducting analyses of large, diverse, medical datasets promises the detection of previously unnoticed clinical correlations and new diagnostic or even therapeutic possibilities. However, using Big Data poses several problems, (...) especially in terms of representing the uniqueness of each patient and expressing the differences between individuals, primarily gender and sex differences. The first two sections of the paper provide a definition of “Big Data” and illustrate the uses of Big Data in medicine. Subsequently, the paper explores the struggle to represent exhaustively the uniqueness of the patient through Big Data is highlighted prior to a deeper investigation of the digital representation of gender in personalized medicine. The final part of the paper put forward a series of recommendations for better approaching the complexity of gender in medical and clinical research involving Big Data for the creation or enhancement of personalized medicine services. (shrink)

Over the last decade, humans have produced each year as much data as were produced throughout the entire history of humankind. These data, in quantities that exceed current analytical capabilities, have been described as “the new oil,” an incomparable source of value. This is true for healthcare, as well. Conducting analyses of large, diverse, medical datasets promises the detection of previously unnoticed clinical correlations and new diagnostic or even therapeutic possibilities. However, using Big Data poses several problems, (...) especially in terms of representing the uniqueness of each patient and expressing the differences between individuals, primarily gender and sex differences. The first two sections of the paper provide a definition of “Big Data” and illustrate the uses of Big Data in medicine. Subsequently, the paper explores the struggle to represent exhaustively the uniqueness of the patient through Big Data is highlighted prior to a deeper investigation of the digital representation of gender in personalized medicine. The final part of the paper put forward a series of recommendations for better approaching the complexity of gender in medical and clinical research involving Big Data for the creation or enhancement of personalized medicine services. (shrink)

Violence risk assessment tools are increasingly used within criminal justice and forensic psychiatry, however there is little relevant, reliable and unbiased data regarding their predictive accuracy. We argue that such data are needed to (i) prevent excessive reliance on risk assessment scores, (ii) allow matching of different risk assessment tools to different contexts of application, (iii) protect against problematic forms of discrimination and stigmatisation, and (iv) ensure that contentious demographic variables are not prematurely removed from risk assessment (...) tools. (shrink)

In the era of precision medicine and expanding health information technologies, large representative datasets are considered necessary for addressing health inequities. Partially in response to gro...

The proliferation of big data analytics in criminal justice suggests that there are positive frames and imaginaries legitimising them and depicting them as the panacea for efficient crime control. Criminological and criminal justice scholarship has paid insufficient attention to these frames and their accompanying narratives. To address the gap created by the lack of theoretical and empirical insight in this area, this article draws on a study that systematically reviewed and compared multidisciplinary academic abstracts on the (...) class='Hi'>data-driven tools now shaping decision-making across several justice systems. Using insights distilled from the study, the article proposes three frames for understanding how the technologies are portrayed. Inherent in the frames are a set of narratives emphasising their ostensible status as vital crime control mechanisms. These narratives obfuscate the harms of data-driven technologies and evince idealistic imaginaries of their capabilities. The narratives are bolstered by unequal structural arrangements, specifically the unevenly distributed digital capital with which some are empowered to participate in technology development for criminal justice application and other forms of penal governance. In unravelling these issues, the article advances current understanding of the dynamics that sustain the depiction of data-driven technologies as prime crime prevention and law enforcement tools. (shrink)

We have seen through many examples that data science and artificial intelligence can reinforce structural inequalities like sexism and racism. Data is power, and that power is distributed unequally. This book offers a vision for a feminist data science that can challenge power and work towards justice. This book takes a stand against a world that benefits some (including the authors, two white women) at the expense of others. It seeks to provide concrete steps for (...) class='Hi'>data scientists seeking to learn how feminism can help them work towards justice, and for feminists seeking to learn how their own work can carry over to the growing field of data science. It is addressed to professionals in all fields where data-driven decisions are being made, as well as to communities that want to better understand the data that surrounds them. It is written for everyone who seeks to better understand the charts and statistics that they encounter in their day-to-day lives, and for everyone who seeks to better communicate the significance of such charts and statistics to others. This is an example-driven book written with a broad audience of scholars, students, and practitioners in mind. It offers a way of thinking about data, both their uses and their limits, that is informed by direct experience, by a commitment to action, and by the ideas associated with intersectional feminist thought. (shrink)

Current strategies to address global inequities in access to life-saving vaccines use averaged national income data to determine eligibility. While largely successful in the lowest income countries, we argue that this approach could lead to significant inefficiencies from the standpoint of justice if applied to middle-income countries, where income inequalities are large and lead to national averages that obscure truly needy populations. Instead, we suggest alternative indicators more sensitive to social justice concerns that merit consideration by policy-makers (...) developing new initiatives to redress health inequities in middle-income countries. (shrink)

Moving away from the strong body of critique of pervasive ‘bad data’ practices by both governments and private actors in the globalized digital economy, this book aims to paint an alternative, more optimistic but still pragmatic picture of the datafied future. The authors examine and propose ‘good data’ practices, values and principles from an interdisciplinary, international perspective. From ideas of data sovereignty and justice, to manifestos for change and calls for activism, this collection opens a multifaceted (...) conversation on the kinds of futures we want to see, and presents concrete steps on how we can start realizing good data in practice. (shrink)

Les perspectives ouvertes par le big data et la justice prédictive ont été largement commentés par les économistes du droit. L’article revient sur la manière dont on peut appréhender ces évolutions économiques et technologiques en montrant comment la possibilité de disposer d’informations plus précises sur le droit à venir renouvelle les problématiques classiques de l’économie du droit. Après une brève description économique de ces innovations techniques, on revient sur la possible automatisation et individualisation de l’application des règles de (...) droit pour en saisir les implications en termes d’efficacité économique du droit. Enfin, on traite de l’automatisation des jugements et du travail du juge en croisant cette question avec celle, bien connue en économie du droit, des biais de jugements et des biais cognitifs. (shrink)

The potential to collect brain data more directly, with higher resolution, and in greater amounts has heightened worries about mental and brain privacy. In order to manage the risks to individuals posed by these privacy challenges, some have suggested codifying new privacy rights, including a right to “mental privacy.” In this paper, we consider these arguments and conclude that while neurotechnologies do raise significant privacy concerns, such concerns are—at least for now—no different from those raised by other well-understood (...) class='Hi'>data collection technologies, such as gene sequencing tools and online surveillance. To better understand the privacy stakes of brain data, we suggest the use of a conceptual framework from information ethics, Helen Nissenbaum’s “contextual integrity” theory. To illustrate the importance of context, we examine neurotechnologies and the information flows they produce in three familiar contexts—healthcare and medical research, criminal justice, and consumer marketing. We argue that by emphasizing what is distinct about brain privacy issues, rather than what they share with other data privacy concerns, risks weakening broader efforts to enact more robust privacy law and policy. (shrink)

Using a time-lagged design, we tested the main effects of Islamic Work Ethic (IWE) and perceived organizational justice on turnover intentions, job satisfaction, and job involvement. We also investigated the moderating influence of IWE in justice–outcomes relationship. Analyses using data collected from 182 employees revealed that IWE was positively related to satisfaction and involvement and negatively related to turnover intentions. Distributive fairness was negatively related to turnover intentions, whereas procedural justice was positively related to satisfaction. In (...) addition, procedural justice was positively related to involvement and satisfaction for individuals high on IWE however it was negatively related to both outcomes for individuals low on IWE. For low IWE, procedural justice was positively related to turnover intentions, however it was negatively related to turnover intentions for high IWE. In contrast, distributive justice was negatively related to turnover intentions for low IWE and it was positively related to turnover intentions for high IWE. (shrink)

Purpose As data-driven tools increasingly shape our life and tech ethics crises become strikingly frequent, data ethics coursework is urgently needed. The purpose of this study is to map the field of data ethics curricula, tracking relations between courses, instructors, texts and writers, and present a proof-of-concept interactive website for exploring these relations. This method is designed to be used in curricular research and development and provides multiple vantage points on this multidisciplinary field. Design/methodology/approach The authors use (...) data science methods to foster insights about the field of data ethics education and literature. The authors present a semantic, linked open data graph in the Resource Description Framework, along with proof-of-concept analyses and an exploratory website. Its framework is open-source and language-agnostic, providing the seed for future contributions of code, syllabi and resources from the global data ethics community. Findings This method provides a convenient means of exploring an overview of the field of data ethics’ social and textual relations. For educators designing or refining a course, the authors provide a method for curricular introspection and discovery of transdisciplinary curricula. Research limitations/implications The syllabi the authors have collected are self-selected and represent only a subset of the field. Furthermore, this method exclusively represents a course’s assigned literature rather than a holistic view of what courses teach. The authors present a prototype rather than a finished product. Originality/value This curricular survey provides a new way of modeling a field of study, using existing ontologies to organize graph data into a comprehensible overview. This framework may be repurposed to map the institutional knowledge structures of other disciplines, as well. (shrink)

In this paper I argue that there is an urgent need for more empirical research into everyday experiences of living with datafication, something that has not been prioritised in the emerging field of data studies to date. As a result of this absence, the knowledge produced within data studies is not as aligned to the aims of data activism as it might be. Data activism seeks to challenge existing, unequal data power relations and to mobilise (...) data in order to enhance social justice, yet data studies has focused primarily on identifying the former and not on imagining the latter. To build a picture of what more just conditions of datafication might look like, I argue that it is important to take account of everyday experiences of datafication, of what people themselves say would enable them to live better with data and would constitute more just data arrangements, based on their experiences. I explore two possible approaches to this endeavour, both of which suggest the need for a vocabulary of emotions in researching everyday living with data. (shrink)

Recognizing the importance of involving suppliers in the new product development (NPD) process, extensive studies have examined this issue at a buyer–supplier dyadic level. However, how supplier involvement leads to better NPD performance is not clearly explained. Additionally, extending the dyadic relationships to triadic relationships and addressing how to manage the two competing suppliers with fair conduct remains unexplored. To answer these questions, this study developed a conceptual model theorizing the role of supplier involvement, information sharing, and justice in (...) the NPD process within a buyer–supplier–supplier triadic relationship. Based on survey data collected from 200 U.S. firms, Structural Equation Modeling is used to test the hypothesis. The results first confirmed the criticality of involving both primary and secondary suppliers during NPD. Second, the positive effect of triadic supplier involvement on innovation performance is fully mediated by information sharing. Finally, this study explored the different roles of procedural justice and distributive justice; the results confirmed that procedural justice acts as a moderator for the relationship between triadic supplier involvement and information sharing, whereas distributive justice moderates the effect between information sharing and innovation performance. Our findings contribute to the literature of triadic supplier involvement-new product development and relationship management. Accordingly, these findings highlight key implications for managers and policymakers. (shrink)

We are now acutely aware, as if all of the sudden, that data matters enormously to how we live. How did information come to be so integral to what we can do? How did we become people who effortlessly present our lives in social media profiles and who are meticulously recorded in state surveillance dossiers and online marketing databases? What is the story behind data coming to matter so much to who we are? -/- In How We Became (...) Our Data, Colin Koopman excavates early moments of our rapidly accelerating data-tracking technologies and their consequences for how we think of and express our selfhood today. Koopman explores the emergence of mass-scale record keeping systems like birth certificates and social security numbers, as well as new data techniques for categorizing personality traits, measuring intelligence, and even racializing subjects. This all culminates in what Koopman calls the “informational person” and the “informational power” we are now subject to. The recent explosion of digital technologies that are turning us into a series of algorithmic data points is shown to have a deeper and more turbulent past than we commonly think. Blending philosophy, history, political theory, and media theory in conversation with thinkers like Michel Foucault, Jürgen Habermas, and Friedrich Kittler, Koopman presents an illuminating perspective on how we have come to think of our personhood—and how we can resist its erosion. (shrink)

Digital inequality and digital justice are pressing issues in today's world. This work examines the socio-philosophical aspects of these problems and proposes measures to achieve digital justice. The authors draw attention to the fact that digital inequality can manifest itself in various forms, such as access to information, technology and resources, as well as opportunities to participate in the digital economy. This can lead to increased social inequalities and limited opportunities for the development of individuals and society as (...) a whole. To achieve digital justice, the authors propose a number of measures, such as improving access to digital technologies and resources, ensuring equal opportunities to participate in the digital economy, and protecting consumer rights and data privacy. They also draw attention to the need to promote digital literacy and education so that people can make effective use of digital technologies and resources. The authors also examine digital inequality and digital justice in the context of monopoly and free speech. They point out that some companies that declare their social responsibility may use their monopolistic position in the market to limit freedom of speech and access to information. In this context, the authors suggest strengthening the role of the state in regulating the digital economy and protecting consumer rights. In conclusion, the research is a valuable contribution to the field of research on digital inequality and digital justice. It emphasizes the need to take into account the socio-philosophical dimensions of these issues and suggests measures to achieve digital justice. It also draws attention to the importance of cultural and historical sensitivity in the development of digital policies and resources. (shrink)

Some recent uses of artificial intelligence for facial recognition, evaluating resumes, and sorting photographs by subject matter have revealed troubling disparities in performance or impact based on the demographic traits of subject populations. These disparities raise pressing questions about how using artificial intelligence can work to promote justice or entrench injustice. Political theorists and philosophers have developed nuanced vocabularies and theoretical frameworks for understanding and adjudicating disputes about what justice requires and what constitutes injustice. The interdisciplinary community committed (...) to understanding and conscientiously using big data could benefit from this work. Thus, in the spirit of encouraging cross-disciplinary dialogue and collaboration, this piece examines contemporary scholarship in political theory and philosophy to illustrate some of the vocabularies and frameworks political theorists and philosophers have developed for thinking about justice and injustice. It then draws on these frameworks to illuminate how the use of artificial intelligence can implicate questions of justice, with a focus on institutional discrimination, structural injustice, and epistemic injustice. Ultimately, the piece argues that the use of artificial intelligence—far from representing a decision to take power out of human hands—represents a novel way of harnessing human power, making questions of justice central to its conscientious undertaking. (shrink)

Big data, artificial intelligence, and increasingly precise biometric techniques have given state and private organizations unprecedented scope and power for the surveillance and dataveillance of migrants. In many cases, these technologies have evolved faster than our legal, political, and ethical mechanisms. This paper, drawing on current discussions of justice and non-domination, proposes a non-domination-based ethics of digital surveillance and mobility, in which the legitimacy of these technologies depends on their avoidance of the arbitrary use of power. This allows (...) us to ethically assess new technologies and justify juridical, democratic, and administrative mechanisms. (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)

In this article, we argue that dominant norms of demographic data are insufficient for accounting for the complexities that characterize many lesbian, gay, bisexual, transgender, and queer lives. Here, we draw from the responses of 178 people who identified as non-heterosexual or non-cisgender to demographic questions we developed regarding gender and sexual orientation. Demographic data commonly imagines identity as fixed, singular, and discrete. However, our findings suggest that, for LGBTQ people, gender and sexual identities are often multiple and (...) in flux. An overwhelming majority of our respondents reported shifting in their understandings of their sexual identities over time. In addition, for many of our respondents, gender identity was made up of overlapping factors, including the relationship between gender and transgender identities. These findings challenge researchers to reconsider how identity is understood as and through data. Drawing from critical data studies, feminist and queer digital media studies, and social justice initiatives like Data for Black Lives, we call for a reimagining of identity-based data as “queer data” or “data for queer lives.” We offer also recommendations for researchers to develop more inclusive survey questions. At the same time, we address the ways that queer perspectives destabilize the underlying logics of data by resisting classification and “capture.” For marginalized people, the stakes of this work extend beyond academia, especially in the era of algorithms and big data when the issue of who is or is not “counted” profoundly affects visibility, access, and power in the digital realm. (shrink)

What could a social-justice oriented, feminist data studies look like? The current datalogical turn foregrounds the digital datafication of everyday life, increasing algorithmic processing and data as an emergent regime of power/knowledge. Scholars celebrate the politics of big data knowledge production for its omnipotent objectivity or dismiss it outright as data fundamentalism that may lead to methodological genocide. In this feminist and postcolonial intervention into gender-, race- and geography-blind ‘big data’ ideologies, I call for (...) ethical, anti-oppressive digital data-driven research in the social sciences and humanities. I argue that a reflexive data scholarship can emerge from the reintegration of feminist and postcolonial science studies and ethics of care ideals. Although it is not a panacea for all ails of data mining, I offer a road map for an alternative data-analysis practice that is more power-sensitive and accountable. By incorporating a people-centric and context-aware perspective that acknowledges relationships of dependency, reflects on temptations, and scrutinises benefits and harm, an ‘asymmetrically reciprocal’ (Young, 1997) research encounter may be achieved. I bring this perspective to bear on experiences of a two-year research project with eighty-four young Londoners on digital identities and living in a highly diverse city. I align awareness of uneven relations of power and knowledge with the messy relation of dependency between human and non-human actors in data analysis. This framework productively recognises that digital data cannot be expected to speak for itself, that data do not emerge from a vacuum, and that isolated data patterns cannot be the end-goal of a situated and reflexive research endeavor. Data-driven research, in turn, shows the urgency for renewed feminist ethical reflection on how digital mediation impacts upon responsibility, intersectional power relations, human subjectivity and the autonomy of research participants over their own data. (shrink)

Despite apparent political concern and action—often fuelled by high-profile cases and campaigns—legislative and institutional responses to image-based sexual abuse in the UK have been ad hoc, piecemeal and inconsistent. In practice, victim-survivors are being consistently failed: by the law, by the police and criminal justice system, by traditional and social media, website operators, and by their employers, universities and schools. Drawing on data from the first multi-jurisdictional study of the nature and harms of, and legal/policy responses to, image-based (...) sexual abuse, this article argues for a new joined-up approach that supports victim-survivors of image-based sexual abuse to ‘reclaim control’. It argues for a comprehensive, multi-layered, multi-institutional and multi-agency response, led by a government- and industry-funded online or e-safety organisation, which not only recognises the diversity of victim-survivor experiences and the intersection of image-based sexual abuse with other forms of sexual and gender-based violence and discrimination, but which also enables victim-survivors to reclaim control within and beyond the criminal justice system. (shrink)

We are living in a world where power abuse has become the new norm, as well as the biggest, silent driver of persistent inequalities, racism and human rights violations. As humanity is getting to grips with socio-economic consequences that can only be compared with those that followed World War II, this timely book challenges current thinking, while creating a much needed normative and practical framework for revealing and challenging the power structures that feed our subconscious feelings of despair and defeatism. (...) Structured around the four concepts of power - race - justice - restorative justice, the book uses empirical new data and normative analysis to reconstruct the way we prevent power abuse and harm at the inter-personal, inter-community and international levels. This book offers new lenses, which allow us to view power, race and justice in a modern reality where communities have been silenced, but through restorative justice are gaining voice. The book is enriched with twenty-five case studies written by survivors, practitioners and those with direct experiences of power abuse and inequality. Through robust research methodologies, Gavrielides' new monograph reveals new forms of slavery, while creating a new, philosophical framework for restorative punishment through the acknowledgement of pain and the use of catharsis for internal transformation and individual empowerment. This is a powerful book that generates much needed hope. Through a multi-disciplinary dialogue that uses social sciences, criminology, law, psychology and human rights, the book opens new avenues for practitioners, researchers and policy makers internationally. (shrink)

In this paper, we examine diverse political philosophical conceptualisations of justice and interrogate how these contested understandings are drawn upon in the burgeoning food justice scholarship. We suggest that three interconnected dimensions of justice—plurality, the spatial–temporal and the more-than-human—deserve further analytical attention and propose the notion of the ‘justice multiple’ to bring together a multiplicity of framings and situated practices of (food) justice. Given the lack of critical engagement food justice has received as both (...) a concept and social movement in the context of the United Kingdom (UK), we draw upon empirical research with practitioners and activists involved with heterogenous food movements working at the local, regional and national level and apply the justice multiple concept to the interview data. We highlight the diverse ways that justice is discussed in terms of access, fairness, empowerment, rights and dignity that reflect established organisational discursive framings and the fragmented nature of food system advocacy and activism. Based on this insight, we argue that a plurivocal, relational conceptualisation of socioecological justice can help enhance the multiple politics of food justice, pluralise UK food movement praxis and nurture avenues for broader coalition-building across the food system. (shrink)

This article argues that ‘the digital’ and ‘big data’ are metaphors of obfuscation, which are used to screen the real effects of technologies on lived experiences and the planet. Now that technolog...

This paper discusses obligations of international distributive justice-specifically, obligations rich countries have to transfer resources to poor countries. It argues that the major seven OECD countries each have an obligation to transfer at least one percent of their GDP to developing countries. -/- The strategy of the paper is to defend this position without having to resolve the many debates that attend questions of international distributive justice. In this respect, it belongs to the neglected category of nonideal theory. (...) The key to the strategy is to show that a significant amount of good would be accomplished by a one percent transfer, despite the fact that one percent is quite a small amount. -/- To make this showing, the paper takes health as a fundamental measure of individual well-being and examines the improvement in life expectancy that would likely result from devoting the one percent transfer to the major determinants of health. It adduces data indicating that substantial progress towards raising life expectancy in developing countries to the global average of 64.5 years can be expected from expenditures of $125 per capita, divided between health care, education, and basic nutrition and income support. A one percent transfer from the major seven is enough to cover expenditures on that scale for the poorest fifth of the world's population. (shrink)