Background:Africa is increasingly becoming an important region for health research, mainly due to its heavy burden of disease, socioeconomic challenges, and inadequate health facilities. Regulatory...

Volume 19, Issue 6, June 2019, Page 19-21.

In this paper I argue for recognizing the moral duty to participate in research. I base my argument on the need for biomedical research and the fact that at some point studies require human participants, what I call collaborative necessity. In presenting my position, I argue against the widely accepted views of Han Jonas and all of those who have accepted his declarations without challenge. I go on to show why it is both just and fair to invite and encourage (...) people to participate in studies. It is just because research participation is the necessary means to achieve the broadly shared goals of preventing and curing disease and alleviating disease symptoms. Mutual love requires us to be willing to do for others what we would want them to do for us. It is fair because the approach treats similarly situated people in the same way. Research participation is morally required because failing to do one's part in the collaborative project of advancing biomedical science would be free-riding. People who exempt themselves from participation while eagerly accepting benefits from others doing their part are taking advantage of their compatriots and treating themselves as more deserving than others when they are not. (shrink)

Non-human animal models of human diseases advance our knowledge of the genetic underpinnings of disease and lead to the development of novel therapies for humans. While mice are the most common model organisms, their usefulness is limited. Larger animals may provide more accurate and valuable disease models, but it has, until recently, been challenging to create large animal disease models. Genome editors, such as Clustered Randomised Interspersed Palindromic Repeat, meet some of these challenges and bring routine genome engineering of larger (...) animals and non-human primates well within reach. There is growing interest in creating NHP models of brain disorders such as autism, depression and Alzheimer’s, which are very difficult to model or study in other organisms, including humans. New treatments are desperately needed for this set of disorders. This paper is novel in asking: Insofar as NHPs are being considered for use as model organisms for brain disorders, can this be done ethically? The paper concludes that it cannot. Notwithstanding ongoing debate about NHPs’ moral status, animal welfare concerns, the availability of alternative methods of studying brain disorders and unmet expectations of benefit justify a stop on the creation of NHP model organisms to study brain disorders. The lure of using new genetic technologies combined with the promise of novel therapeutics presents a formidable challenge to those who call for slow, careful, and only necessary research involving NHPs. But researchers should not create macaques with social deficits or capuchin monkeys with memory deficits just because they can. (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)

Full aptness is the most important concept in performance-based virtue epistemology. The structure of full aptness, in epistemology and elsewhere, is bi-levelled. At the first level, we evaluate beliefs, like performances, on the basis of whether they are successful, competent, and apt – viz., successful because competent. But the fact that aptness itself can be fragile – as it is when an apt performance could easily have been inapt – points to a higher zone of quality beyond mere aptness. To (...) break in to this zone, one must not merely perform aptly but also in doing so safeguard in skilled ways against certain risks to inaptness. But how must this be done, exactly? This paper has two central aims. First, I challenge the credentials of mainstream thinking about full-aptness by raising some new and serious problems for the view. I then propose a novel account of full aptness – what I call de minimis normativism – which keeps all the advantages of the canonical view, avoids its problems entirely, and offers some additional payoffs. (shrink)