Ethics Of Big Data Research Articles

Data protection during the coronavirus crisis.

Smartphone apps to track SARS-CoV 2 infections need to fulfill certain minimal requirements to guarantee privacy and justify their use under data protection laws.

Science Without Conscience Is but the Ruin of the Soul: The Ethics of Big Data and Artificial Intelligence in Perioperative Medicine.

Artificial intelligence-driven anesthesiology and perioperative care may just be around the corner. However, its promises of improved safety and patient outcomes can only become a reality if we take the time to examine its technical, ethical, and moral implications. The aim of perioperative medicine is to diagnose, treat, and prevent disease. As we introduce new interventions or devices, we must take care to do so with a conscience, keeping patient care as the main objective, and understanding that humanism is a core component of our practice. In our article, we outline key principles of artificial intelligence for the perioperative physician and explore limitations and ethical challenges in the field.

Ethics of Big Data: A Socio-Economic Perspective

With the development of information technology, artificial intelligence, and robots, capitalism has increasingly assumed a form of platform capitalism which is ‘reconceptualizing our economy’ to the extent that it is ‘forcing us to rethink economics’. Capitalism and various institutions controlled by this system have been the subject of criticism in the past and need was expressed to reform them. But today it has become most obvious that there is need for ‘replacing it with a more caring and provisioning sustainable system’.

Big Data Ethics in Social Media-- A Case Study of Evaluating Websites

This article combines qualitative and quantitative analysis to study the ethical issues of Big Data in social media, especially in evaluating websites. First, this article discusses the Big Data ethics of evaluation websites, and finds that there are some problems in the evaluation websites, such as false information, hidden information, and lack of user information protection. Second, this article uses questionnaires to investigate the awareness of users of different genders and ages on the evaluation website and their personal information protection consciousness.

Big Data, Big Waste? A Reflection on the Environmental Sustainability of Big Data Initiatives

This paper addresses a problem that has so far been neglected by scholars investigating the ethics of Big Data and policy makers: that is the ethical implications of Big Data initiatives’ environmental impact. Building on literature in environmental studies, cultural studies and Science and Technology Studies, the article draws attention to the physical presence of data, the material configuration of digital service, and the space occupied by data. It then explains how this material and situated character of data raises questions concerning the ethics of the increasingly fashionable Big Data discourses. It argues that attention should be paid to (1) the vocabulary currently used when discussing the governance of data initiatives; (2) the internal tension between current data initiatives and environmental policies; (3) issues of fair distribution. The article explains how taking into account these aspects would allow for a more responsible behaviour in the context of data storage and production.

Round table: AI and Big Data: Ethical Challenges and Health Opportunities

Abstract The recent emergence of Big Data in healthcare (including large linked data from electronic patient records (EPR) as well as streams of real-time geolocated health data collected by personal wearable devices, etc.) and the open data movement enabling sharing datasets are creating new challenges around ownership of personal data whilst at the same time opening new research opportunities and drives for commercial exploitation. A balance must be struck between an individual’s desire for privacy and their desire for good evidence to drive healthcare, which may sometimes be in conflict. With the increasing use of mobile and wearable devices, new opportunities have been created for personalized health (tailored care to the needs of an individual), crowdsourcing, participatory surveillance, and movement of individuals pledging to become “data donors” and the “quantified self” initiative (where citizens share data through mobile device-connected technologies). These initiatives created large volumes of data with considerable potential for research through open data initiatives. In this workshop we will hear from a panel of international speakers working across the digital health, Big Data ethics, computer science, public health divide on how they have addressed the challenges presented by increased use of Big Data and AI systems in healthcare with insights drawn from their own experience to illustrate the new opportunities that development of these movements has opened up. Key messages The potential of open access to healthcare data, sharing Big Data sets and rapid development of AI technology, is enormous - so as are the challenges and barriers to achieve this goal. Policymakers, scientific and business communities should work together to find novel approaches for underlying challenges of a political and legal nature associated with use of big data for health.

Engaging with ethics in Internet of Things: Imaginaries in the social milieu of technology developers

Discussions about ethics of Big Data often focus on the ethics of data processing: collecting, storing, handling, analysing and sharing data. Data-based systems, however, do not come from nowhere. They are designed and brought into being within social spaces – or social milieu. This paper connects philosophical considerations of individual and collective capacity to enact practical reason to the influence of social spaces. Building a deeper engagement with the social imaginaries of technology development through analysis of two years of fieldwork with start-ups working on Internet of Things, this paper suggests that different action positions can emerge, with consequences for how data is understood and valued. The Disengaged, Pragmatist and Idealist ethical action positions identified in the paper reveal the ways individuals and groups negotiate possibilities for ethical action, through justifications, explanations and structuring of system features.

Big data phenotyping in rare diseases: some ethical issues

Big data phenotyping in rare diseases: some ethical issues

Big Data ethics and selection-bias: An official statistician’s perspective

Big Data ethics and selection-bias: An official statistician’s perspective

Big Data Ethics and Politics: Toward New Understandings

The hype around big data does not seem to abate nor do the scandals. Privacy breaches in the collection, use, and sharing of big data have affected all the major tech players, be it Facebook, Google, Apple, or Uber, and go beyond the corporate world including governments, municipalities, and educational and health institutions. What has come to light is that enabled by the rapid growth of social media and mobile apps, various stakeholders collect and use large amounts of data, disregarding the ethics and politics. As big data touch on many realms of daily life and have profound impacts in the social world, the scrutiny around big data practice becomes increasingly relevant. This special issue investigates the ethics and politics of big data using a wide range of theoretical and methodological approaches. Together, the articles provide new understandings of the many dimensions of big data ethics and politics, showing it is important to understand and increase awareness of the biases and limitations inherent in big data analysis and practices.

Where is the human in the data? A guide to ethical data use.

Being asked to write about the ethics of big data is a bit like being asked to write about the ethics of life. Big data is now integral to so many aspects of our daily lives—communication, social interaction, medicine, access to government services, shopping, and navigation. Given this diversity, there is no one-size-fits-all framework for how to ethically manage your data. With that in mind, I present seven ethical values for responsible data use.

Future Anthropology Ethics and Datafication: Temporality and Responsibility in Research

In this article, we argue for an ethics of big data that is embedded in the emergent processes through which data are made, interpreted, and mobilized in mundane everyday contexts and examine how this could potentially be played out in research practice. We situate this as a response to a current crisis in accountability that has arisen in the context of the use of digital data to inform societal interventions, which we propose calls for a future-oriented anthropological ethics situated in the ongoingness of life. Such a standpoint offers a revised approach to temporality and attends to the ethics of intervening and engaging with the uncertainty of what is as yet unknown rather than simply with an ethics of the past. It offers us an opportunity to think differently about big data and ethics and to create an alternative ethics for big data and their analysis.

Why Are Norms Ignored? Collective Action and the Privacy Commons

Informational privacy is the ability to govern when others may collect your information and how they may use it. Norms can, and do, provide such governance, as Helen Nissenbaum’s seminal work shows. The relevant norms are informational norms, social norms that govern the collection, use, and distribution of information. With noteworthy exceptions (Woodrow Hartzog and Neil Richards, for example), contemporary discussions of privacy rarely mention informational norms, or at best assign them a peripheral role. We claim they should play a central role. Our argument is that ensuring adequate informational privacy is (at least in part) a collective action problem. Norms can, and often do, solve collective action problems. Further, informational norms currently do solve a wide range of important collective action problems centered around privacy. Shouldn’t informational norms take center stage in proposals about informational privacy? We argue they should by answering three objections to giving them that role. (1) Lack of norms: Rapid advances in technology have created a wide variety of situations for which are not governed by relevant norms. (2) Disagreement about norms: Even if relevant norms exist, lack of agreement about their content makes them a poor foundation on which to build public policy. (3) Lack of an adequate theory: Even if norms exist and their content is uncontroversial, norms are a poor tool for public policy because there is no adequate theory that allows one to make accurate predictions about the causes and effects of norms. The first two objections have relatively easy answers. The third is fundamental. We outline a theory that treats norm-created informational privacy as a commons—a special kind of commons, a common pool resource. We thereby link norm-created privacy to a rich body of empirical and theoretical work. We hope the resulting theory of norm-created governance of information flows contributes to the understanding of privacy that Neil Richards and Jonathan King call for in Big Data Ethics: “privacy in the age of big data should be . . . understood as the need to expand the rules we use to govern the flows of personal information.”

Big Data for Biomedical Research and Personalised Medicine: an Epistemological and Ethical Cross-Analysis

Abstract Big data techniques, data-driven science and their technological applications raise many serious ethical questions, notably about privacy protection. In this paper, we highlight an entanglement between epistemology and ethics of big data. Discussing the mobilisation of big data in the fields of biomedical research and health care, we show how an overestimation of big data epistemic power – of their objectivity or rationality understood through the lens of neutrality – can become ethically threatening. Highlighting the irreducible non-neutrality at play in big data tools, we insist upon the ethical importance of a critical epistemological approach in which big data are understood as possibly valuable only when coupled with human intelligence and evaluative rationality.

The Ethics of Big Data and Nursing Science.

Big data is a scientific, social, and technological trend referring to the process and size of datasets available for analysis. Ethical implications arise as healthcare disciplines, including nursing, struggle over questions of informed consent, privacy, ownership of data, and its possible use in epistemology. The author offers straight-thinking possibilities for the use of big data in nursing science.

The ethics of big data as a public good: which public? Whose good?

International development and humanitarian organizations are increasingly calling for digital data to be treated as a public good because of its value in supplementing scarce national statistics and informing interventions, including in emergencies. In response to this claim, a 'responsible data' movement has evolved to discuss guidelines and frameworks that will establish ethical principles for data sharing. However, this movement is not gaining traction with those who hold the highest-value data, particularly mobile network operators who are proving reluctant to make data collected in low- and middle-income countries accessible through intermediaries. This paper evaluates how the argument for 'data as a public good' fits with the corporate reality of big data, exploring existing models for data sharing. I draw on the idea of corporate data as an ecosystem involving often conflicting rights, duties and claims, in comparison to the utilitarian claim that data's humanitarian value makes it imperative to share them. I assess the power dynamics implied by the idea of data as a public good, and how differing incentives lead actors to adopt particular ethical positions with regard to the use of data.This article is part of the themed issue 'The ethical impact of data science'.

The opportunities and ethics of big data: practical priorities for a national Council of Data Ethics.

In order to generate the gains that can come from analysing and linking big datasets, data holders need to consider the ethical frameworks, principles and applications that help to maintain public trust. In the USA, the National Science Foundation helped to set up a Council for Big Data, Ethics and Society, of which there is no equivalent in the UK. In November 2015, the Royal Statistical Society convened a workshop of 28 participants from government, academia and the private sector, and discussed the practical priorities that might be assisted by a new Council of Data Ethics in the UK. This article draws together the views from that meeting. Priorities for policy-makers and others include seeking a public mandate and informing the terms of the social contract for use of data; building professional competence and due diligence on data protection; appointment of champions who are competent to address public concerns; and transparency, across all dimensions. For government data, further priorities include improvements to data access, and development of data infrastructure. In conclusion, we support the establishment of a national Data Ethics Council, alongside wider and deeper engagement of the public to address data ethics dilemmas.This article is part of the themed issue 'The ethical impact of data science'.

Round Table Discussion: Data Sharing and Ethics of Big Data

Round Table Discussion: Data Sharing and Ethics of Big Data

The Ethics of Big Data as a Public Good: Which Public? Whose Good?

The Ethics of Big Data as a Public Good: Which Public? Whose Good?

Ethics for Big Data and Analytics

This article investigates some issues associated with big data and analytics (big data) and examining how big data ethics are different than ethics and other more general ethical frameworks. In so doing, the author briefly investigates some of the previous research in computer ethics, reviews some codes of analyzes the application of two frameworks on ethics to big data, and provides a definition of big data ethics. Ultimately, the author argues that in order to get sufficient specificity, a code of ethics for big data is necessary.