Part 5, the concluding essay in the series describing and discussing the role, remit and function of research ethics committees, bases an enquiry into the nature of decision-making by research ethics committees on the processes followed by the committees in their deliberations leading to the final outcome.

For decades, scholars in the social sciences and humanities have questioned the appropriateness and utility of prior review of their research by human subjects' ethics committees. This essay seeks to organize thematically some of their published complaints and to serve as a brief restatement of the major critiques of ethics review. In particular, it argues that 1) ethics committees impose silly restrictions, 2) ethics review is a solution in search of a problem, 3) ethics committees lack expertise, 4) ethics committees (...) apply inappropriate principles, 5) ethics review harms the innocent, and 6) better options exist. (shrink)

Zachary Schrag would like to put the burden of proof for continuation of research ethics review in the Social Sciences on those who advocate for research ethics committees (RECs), and asks that we take the concerns that he raises seriously. I separate his concerns into a principled issue and a number of pragmatic issues. The principled issue concerns the justification for having research ethics committees; the pragmatic issues concern questions such as the effectiveness of review and the expertise of the (...) committee members. I argue that RECs can be justified by their role in improving ethical practice and in reducing wrongs done to research participants. I propose a model of review for doing this, which I think would also address the pragmatic issues raised. I then offer an account of where the UK ethics review system is now and suggest three steps which could improve social science ethics review in the UK and move it in a perhaps more desirable direction. (shrink)

Artificial Intelligence (AI) is already having a major impact on society. As a result, many organizations have launched a wide range of initiatives to establish ethical principles for the adoption of socially beneficial AI. Unfortunately, the sheer volume of proposed principles threatens to overwhelm and confuse. How might this problem of ‘principle proliferation’ be solved? In this paper, we report the results of a fine-grained analysis of several of the highest-profile sets of ethical principles for AI. We assess whether these (...) principles converge upon a set of agreed-upon principles, or diverge, with significant disagreement over what constitutes ‘ethical AI.’ Our analysis finds a high degree of overlap among the sets of principles we analyze. We then identify an overarching framework consisting of five core principles for ethical AI. Four of them are core principles commonly used in bioethics: beneficence, non-maleficence, autonomy, and justice. On the basis of our comparative analysis, we argue that a new principle is needed in addition: explicability, understood as incorporating both the epistemological sense of intelligibility (as an answer to the question ‘how does it work?’) and in the ethical sense of accountability (as an answer to the question: ‘who is responsible for the way it works?’). In the ensuing discussion, we note the limitations and assess the implications of this ethical framework for future efforts to create laws, rules, technical standards, and best practices for ethical AI in a wide range of contexts. (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)

Volume 19, Issue 11, November 2019, Page 9-12.

In information societies, operations, decisions and choices previously left to humans are increasingly delegated to algorithms, which may advise, if not decide, about how data should be interpreted and what actions should be taken as a result. More and more often, algorithms mediate social processes, business transactions, governmental decisions, and how we perceive, understand, and interact among ourselves and with the environment. Gaps between the design and operation of algorithms and our understanding of their ethical implications can have severe consequences (...) affecting individuals as well as groups and whole societies. This paper makes three contributions to clarify the ethical importance of algorithmic mediation. It provides a prescriptive map to organise the debate. It reviews the current discussion of ethical aspects of algorithms. And it assesses the available literature in order to identify areas requiring further work to develop the ethics of algorithms. (shrink)

This is the second in a series of five papers on the role, remit and function of research ethics committees which are intended to provide for REC members a broad understanding of the most important issues in research ethics and governance. This paper examines the role of ethics committees in assessing the science of the research it reviews. While ethics committees are not specifically constituted to review the science of a project, they must nevertheless assess the social benefits of research (...) and, in this context, have an important role in checking that the science has been properly peer-reviewed. (shrink)

This is the fourth in a series of five papers on the role, remit and function of research ethics committees which are intended to provide for REC members a broad understanding of the most important issues in research ethics and governance. This paper explores the role of ethics committees in reviewing proposed conditions for recruiting human subjects and in checking the intended procedures for gaining consent. In so doing the paper will reiterate the conditions which are traditionally thought to make (...) consent valid, identify a number of limitations to meeting these conditions, and show when consent, however broadly construed or indeterminately focused, may be unnecessary. (shrink)

This is the first in a series of five papers on the role, remit and function of research ethics committees which are intended to provide for REC members a broad understanding of the most important issues in research ethics and governance. The first considers the rationale for having ethics review by committee at all; seeking to explain why ethics committees, as we currently have them, are so important to the wider system of governing research.