Whilst Rahimzadeh et al. (2023) apply a critical lens to the pedagogical use of LLM bioethics assistants, we outline here further reason for skepticism. Two features of LLM chatbots are of signific...

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)

Neuroimaging has been to neuroethics what free will and determinism has been, albeit for much longer, to philosophy: pillars for scholarly inquiry and curiosity, and entries to dialogue, debate, and discovery. With interest piqued by reproducible measures of regional blood flow in the human brain under well-defined conditions such as existential problem solving, decision-making, and trust, this article meticulously documents emerging trends involving functional MRI studies. The article builds on that work and examines the hypothesis that almost twenty years after (...) the first wave of such studies, the focus on neuroimaging and its application to complex and profoundly personal human behaviors has not abated. Neuroimaging studies remain an unwavering source of energy for the field. It reviews some of the reasons that they have provoked so much attention in neuroethics and elsewhere, presenting a 2002–2008 update to the trends that documented for 1991–2001, comparing this second generation of data to the first. (shrink)

Background: The research community has a mandate to discover effective treatments for neurodegenerative disorders. The ethics landscape surrounding this mandate is in a constant state of flux, and ongoing challenges place ever greater demands on investigators to be accountable to the public and to answer questions about the implications of their work for health care, society, and policy. Methods: We surveyed US-based investigators involved in neurodegenerative diseases research about how they value ethics-related issues, what motivates them to give consideration to (...) those issues, and the barriers to doing so. Using the NIH CRISP database we identified 1,034 researchers with relevant, active grants and invited them to complete an online questionnaire. We received 193 responses. We used exploratory factor analysis to transform individual survey questions into a smaller set of factors, and linear regression to understand the effect of key variables of interest on the factor scores. Results: Ethics-related issues clustered into two groups: research ethics and external influences. Heads of research groups viewed issues of research ethics to be more important than the other respondents. Concern about external influences was related to overall interest in ethics. Motivators clustered into five groups: ensuring public understanding, external forces, requirements, values, and press and public. Heads of research groups were more motivated to ensure public understanding of research than the other respondents. Barriers clustered into four groups: lack of resources, administrative burden, relevance to the research, and lack of interest. Perceived lack of ethics resources was a particular barrier for investigators working in drug discovery. Conclusions: The data suggest that senior level neuroscientists working in the field of neurodegeneration (ND), and drug discovery specifically, are motivated to consider ethics issues related to their work, but the perceived lack of ethics resources thwarts their efforts. With bioethics centres at more than 50% of the institutions at which these respondents reside, the neuroscience and bioethics communities appear to be disconnected. Dedicated ethical, legal and social implications (ELSI) programs, such as those fully integrated into genetics and regenerative medicine, provide models for achieving meaningful partnerships not yet adequately realized for scholars and trainees interested in drug discovery for ND. (shrink)