Generalisation, universal knowledge claims, and recommendations within disaster studies are problematic because they lead to miscommunication and the misapplication of actionable knowledge. The consequences and impacts thereof are not often considered by experts; forgone as irrelevant to the academic division of labour. There is a disconnect between expert assertions for disaster risk reduction (DRR) and their practical suitability for laypersons. Experts currently assert independently of the context within which protective action measures (PAMs) are to be used, measures unconnected to the (...) people for whom they are developed. This has knock-on effects for DRR: much expert-generated science and policy remains unused, unimplemented, and sometimes misapplied. I use philosophical accounts of assertion and epistemic blame to highlight the epistemic relationship between experts and laypersons. This relationship includes responsibilities and agreements between epistemic agents. Since multilevel DRR knowledge still transfers top-down from experts to laypersons, if experts impair the epistemic relationship, they can be held epistemically blameworthy. To address the pervasiveness of top-down systems, I analyse the epistemic framings and narratives currently shaping DRR, and more specifically PAMs and campaigns. I deconstruct universal perspectives that dominate the epistemic processes of generating, disseminating, and implementing DRR knowledge and specifically for co-seismic landslide PAMs for Nepal. I argue for more inclusive, contextual, and epistemically responsible DRR. Co-production of knowledge should begin from the standpoints of marginalised persons who may have an epistemic advantage due to their socio-politically marginalised positions. Often these epistemic contributions are left out of DRR efforts because marginalised persons are rarely afforded equal, if any, epistemic agency, which results in epistemic gaps and a large pool of relevant knowledge remaining unincorporated and unused in DRR research and policy. (shrink)

Purpose Digital transformation leverages digital technologies to change current processes and introduce new processes in any organisation’s business model, customer/user experience and operational processes. Artificial intelligence plays a significant role in achieving DT. As DT is touching each sphere of humanity, AI led DT is raising many fundamental questions. These questions raise concerns for the systems deployed, how they should behave, what risks they carry, the monitoring and evaluation control we have in hand, etc. These issues call for the need (...) to integrate ethics in AI led DT. The purpose of this study is to develop an “AI led ethical digital transformation framework”. Design/methodology/approach Based on the literature survey, various existing business ethics decision-making models were synthesised. The authors mapped essential characteristics such as intensity and the individual, organisational and opportunity factors of ethics models with the proposed AI led ethical DT. The DT framework is evaluated using a thematic analysis of 23 expert interviews with relevant AI ethics personas from industry and society. The qualitative data of the interviews and opinion data has been analysed using MAXQDA software. Findings The authors have explored how AI can drive the ethical DT framework and have identified the core constituents of developing an AI led ethical DT framework. Backed by established ethical theories, the paper presents how DT pillars are related and sequenced to ethical factors. This research provides the potential to examine theoretically sequenced ethical factors with practical DT pillars. Originality/value The study establishes deduced and induced ethical value codes based on thematic analysis to develop guidelines for the pursuit of ethical DT. The authors identify four unique induced themes, namely, corporate social responsibility, perceived value, standard benchmarking and learning willingness. The comprehensive findings of this research, supported by a robust theoretical background, have substantial implications for academic research and corporate applicability. The proposed AI led ethical DT framework is unique and can be used for integrated social, technological and economic ethical research. (shrink)

Trafficking and persistence of fetal microchimeric cells (fMCs) and circulating extracellular vesicles (EVs) have been observed in animals and humans, but their consequences in the maternal body and their mechanistic contributions to maternal physiology and pathophysiology are not yet fully defined. Fetal cells and EVs may help remodel maternal organs after pregnancy‐associated changes, but the cell types and EV cargos reaching the mother in preterm pregnancies after exposure to various risk factors can be distinct from term pregnancies. As preterm delivery‐associated (...) maternal complications are rising, revisiting this topic and formulating scientific questions for future research to reduce the risk of maternal morbidities are timely. Epidemiological studies report maternal cardiovascular risk as one of the major complications after preterm delivery. This paper suggests a potential link between fMCs and circulating EVs and adverse maternal cardiovascular outcomes post‐pregnancies, the underlying mechanisms, consequences, and methods for and how this link might be assessed. (shrink)