This article argues that the study conducted by Facebook in conjunction with Cornell University did not have sufficient ethical oversight, and neglected in particular to obtain necessary informed consent from the participants in the study. It establishes the importance of informed consent in Internet research ethics and suggests that in Facebook’s case (and other, similar cases), a reasonable shift could be made from traditional medical ethics ‘effective consent’ to a ‘waiver of normative expectations’, although this would require much-needed change to (...) the company’s standard practice. Finally, it gives some practical recommendations for how to implement such consent strategies, and how the ethical oversight gap between university-led research and industry-led research can be bridged, potentially using emerging Responsible Research and Innovation frameworks which are currently gathering momentum in Europe. (shrink)

There are growing discontinuities between the research practices of data science and established tools of research ethics regulation. Some of the core commitments of existing research ethics regulations, such as the distinction between research and practice, cannot be cleanly exported from biomedical research to data science research. Such discontinuities have led some data science practitioners and researchers to move toward rejecting ethics regulations outright. These shifts occur at the same time as a proposal for major revisions to the Common Rule—the (...) primary regulation governing human-subjects research in the USA—is under consideration for the first time in decades. We contextualize these revisions in long-running complaints about regulation of social science research and argue data science should be understood as continuous with social sciences in this regard. The proposed regulations are more flexible and scalable to the methods of non-biomedical research, yet problematically largely exclude data science methods from human-subjects regulation, particularly uses of public datasets. The ethical frameworks for Big Data research are highly contested and in flux, and the potential harms of data science research are unpredictable. We examine several contentious cases of research harms in data science, including the 2014 Facebook emotional contagion study and the 2016 use of geographical data techniques to identify the pseudonymous artist Banksy. To address disputes about application of human-subjects research ethics in data science, critical data studies should offer a historically nuanced theory of “data subjectivity” responsive to the epistemic methods, harms and benefits of data science and commerce. (shrink)

This edited volume focuses on big data implications for computational social science and humanities from management to usage. The first part of the book covers geographic data, text corpus data, and social media data, and exemplifies their concrete applications in a wide range of fields including anthropology, economics, finance, geography, history, linguistics, political science, psychology, public health, and mass communications. The second part of the book provides a panoramic view of the development of big data in the fields of computational (...) social sciences and humanities. The following questions are addressed: why is there a need for novel data governance for this new type of data?, why is big data important for social scientists?, and how will it revolutionize the way social scientists conduct research? With the advent of the information age and technologies such as Web 2.0, ubiquitous computing, wearable devices, and the Internet of Things, digital society has fundamentally changed what we now know as "data", the very use of this data, and what we now call "knowledge". Big data has become the standard in social sciences, and has made these sciences more computational. Big Data in Computational Social Science and Humanities will appeal to graduate students and researchers working in the many subfields of the social sciences and humanities. (shrink)

This paper uses the example of payday loans to identify two standards of exploitation that better accord with intuitions about taking unfair advantage than neoclassical or neo-Marxian exploitation theory. These two standards are derived from ongoing policy debates about the regulation of payday loans. The sufficiency standard is more restrictive than relative-advantage theory, but the latter indicates when exceptions to the prohibition on exploitation should be made for the sake of the disadvantaged party.