Recent experiments have been used to “edit” genomes of various plant, animal and other species, including humans, with unprecedented precision. Furthermore, editing the Cas9 endonuclease gene with a gene encoding the desired guide RNA into an organism, adjacent to an altered gene, could create a “gene drive” that could spread a trait through an entire population of organisms. These experiments represent advances along a spectrum of technological abilities that genetic engineers have been working on since the advent of recombinant DNA (...) techniques. The scientific and bioethics communities have built substantial literatures about the ethical and policy implications of genetic engineering, especially in the age of bioterrorism. However, recent CRISPr/Cas experiments have triggered a rehashing of previous policy discussions, suggesting that the scientific community requires guidance on how to think about social responsibility. We propose a framework to enable analysis of social responsibility, using two example.. (shrink)

Background Machine learning (ML) is utilized increasingly in health care, and can pose harms to patients, clinicians, health systems, and the public. In response, regulators have proposed an approach that would shift more responsibility to ML developers for mitigating potential harms. To be effective, this approach requires ML developers to recognize, accept, and act on responsibility for mitigating harms. However, little is known regarding the perspectives of developers themselves regarding their obligations to mitigate harms.Methods We conducted 40 semi-structured interviews with (...) developers of ML predictive analytics applications for health care in the United States.Results Participants varied widely in their perspectives on personal responsibility and included examples of both moral engagement and disengagement, albeit in a variety of forms. While most (70%) of participants made a statement indicative of moral engagement, most of these statements reflected an awareness of moral issues, while only a subset of these included additional elements of engagement such as recognizing responsibility, alignment with personal values, addressing conflicts of interests, and opportunities for action. Further, we identified eight distinct categories of moral disengagement reflecting efforts to minimize potential harms or deflect personal responsibility for preventing or mitigating harms.Conclusions These findings suggest possible facilitators and barriers to the development of ethical ML that could act by encouraging moral engagement or discouraging moral disengagement. Regulatory approaches that depend on the ability of ML developers to recognize, accept, and act on responsibility for mitigating harms might have limited success without education and guidance for ML developers about the extent of their responsibilities and how to implement them. (shrink)

The US National Institute of Health’s Human Microbiome Project aims to use genomic techniques to understand the microbial communities that live on the human body. The emergent field of microbiome science brought together diverse disciplinary perspectives and technologies, thus facilitating the negotiation of differing values. Here, we describe how values are conceptualized and negotiated within microbiome research. Analyzing discussions from a series of interdisciplinary workshops conducted with microbiome researchers, we argue that negotiations of epistemic, social, and institutional values were inextricable (...) from the reflective and strategic category work that defined and organized the microbiome as an object of study and a potential future site of biomedical intervention. Negotiating the divergence or tension between emerging scientific and regulatory classifications also activated “values levers” and opened up reflective discussions of how classifications embody values and how these values might differ across domains. These data suggest that scholars at the intersections of science and technology studies, ethics, and policy could leverage such openings to identify and intervene in the ways that ethical/regulatory and scientific/technical practices are coproduced within unfolding research. (shrink)