This paper advances a new criterion of a vulnerable population in research. According to this criterion, there are consent-based and fairness-based reasons for calling a group vulnerable. The criterion is then applied to the case of people with serious illnesses. It is argued that people with serious illnesses meet this criterion for reasons related to consent. Seriously ill people have a susceptibility to "enticing offers" that hold out the prospect of removing or alleviating illness, and this susceptibility reduces their ability to safeguard their own interests. This explains the inclusion of people with serious illnesses in the Belmont Report's list of populations needing special protections, and supports the claim that vulnerability is the rule, rather than the exception, in biomedical research.
This paper defends the view that trust is a moral attitude, by putting forward the Obligation-Ascription Thesis: If E trusts F to do X, this implies that E ascribes an obligation to F to do X. I explicate the idea of obligation-ascription in terms of requirement and the appropriateness of blame. Then, drawing a distinction between attitude and ground, I argue that this account of the attitude of trust is compatible with the possibility of amoral trust, that is, trust held among amoral persons on the basis of amoral grounds. It is also compatible with trust adopted on purely predictive grounds. Then, defending the thesis against a challenge of motivational inefficacy, I argue that obligation-ascription can motivate people to act even in the absence of definite, mutually-known agreements. I end by explaining, briefly, the advantages of this sort of moral account of trust over a view based on reactive attitudes such as resentment.
This paper explores the role of moral uncertainty in explaining the morally disruptive character of new technologies. We argue that existing accounts of technomoral change do not fully explain its disruptiveness. This explanatory gap can be bridged by examining the epistemic dimensions of technomoral change, focusing on moral uncertainty and inquiry. To develop this account, we examine three historical cases: the introduction of the early pregnancy test, the contraception pill, and brain death. The resulting account highlights what we call “differential disruption” and provides a resource for fields such as technology assessment, ethics of technology, and responsible innovation.
The adoption of web-based telecare services has raised multifarious ethical concerns, but a traditional principle-based approach provides limited insight into how these concerns might be addressed and what, if anything, makes them problematic. We take an alternative approach, diagnosing some of the main concerns as arising from a core phenomenon of shifting trust relations that come about when the physician plays a less central role in the delivery of care, and new actors and entities are introduced. Correspondingly, we propose an applied ethics of trust based on the idea that patients should be provided with good reasons to trust telecare services, which we call sound trust. On the basis of this approach, we propose several concrete strategies for safeguarding sound trust in telecare.
This paper develops a philosophical account of moral disruption. According to Robert Baker, moral disruption is a process in which technological innovations undermine established moral norms without clearly leading to a new set of norms. Here I analyze this process in terms of moral uncertainty, formulating a philosophical account with two variants. On the harm account, such uncertainty is always harmful because it blocks our knowledge of our own and others’ moral obligations. On the qualified harm account, there is no harm in cases where moral uncertainty is related to innovation that is “for the best” in historical perspective or where uncertainty is the expression of a deliberative virtue. The two accounts are compared by applying them to Baker’s historical case of the introduction of mechanical ventilation and organ transplantation technologies, as well as the present-day case of mass data practices in the health domain.
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