In terms of intervening in embodied experience, medical treatment is wonder-full in its ambition and its metaphysical presumption; yet, wonder’s role in clinical medicine has received little philosophical attention. In this paper, I propose, to doctors and others in routine clinical life, the value of an openness to wonder and to the sense of wonder. Key to this is the identity of the central ethical challenges facing most clinicians, which is not the high-tech drama of the popular conceptions of medical (...) ethics but, rather, the routine of patients’ undramatic but unremitting demands for the clinician’s time and respectful attention. Wonder (conceived as an intense and transfiguring attentiveness) is a ubiquitous ethical source, an alternative to the more familiar respect for rational autonomy, a source of renewal galvanizing diagnostic imagination, and a timely recalling of the embodied agency of both patient and clinician. (shrink)

Rapid advancements in machine learning techniques allow mass surveillance to be applied on larger scales and utilize more and more personal data. These developments demand reconsideration of the privacy-security dilemma, which describes the tradeoffs between national security interests and individual privacy concerns. By investigating mass surveillance techniques that use bulk data collection and machine learning algorithms, we show why these methods are unlikely to pinpoint terrorists in order to prevent attacks. The diverse characteristics of terrorist attacks—especially when considering lone-wolf terrorism—lead (...) to irregular and isolated footprints. The irregularity of data affects the accuracy of machine learning algorithms and the mass surveillance that depends on them which can be explained by three kinds of known problems encountered in machine learning theory: class imbalance, the curse of dimensionality, and spurious correlations. Proponents of mass surveillance often invoke the distinction between collecting data and metadata, in which the latter is understood as a lesser breach of privacy. Their arguments commonly overlook the ambiguity in the definitions of data and metadata and ignore the ability of machine learning techniques to infer the former from the latter. Given the sparsity of datasets used for machine learning in counterterrorism and the privacy risks attendant with bulk data collection, policymakers and other relevant stakeholders should critically re-evaluate the likelihood of success of the algorithms and the collection of data on which they depend. (shrink)

The notion of patients’ duties has received periodic scholarly attention but remains overwhelmed by attention to the duties of healthcare professionals. In a previous paper the author argued that patients in publicly funded healthcare systems have a duty to participate in clinical research, arising from their debt to previous patients. Here the author proposes a greatly extended range of patients’ duties grounding their moral force distinctively in the interests of contemporary and future patients, since medical treatment offered to one patient (...) is always liable to be an opportunity cost in terms of medical treatment needed by other patients. This generates both negative and positive duties. Ten duties—enjoining obligations ranging from participation in healthcare schemes to promoting one’s own earliest recovery from illness—are proposed. The characteristics of these duties, including their basis, moral force, extent and enforceability, are considered. They are tested against a range of objections—principled, societal, epistemological and practical—and found to survive. Finally, the paper suggests that these duties could be thought to reinforce a regrettably adversarial characteristic, shared with rights-based approaches, and that a preferable alternative might be sought through the notion of a “virtuous patient” contributing to a problem-solving partnership with the clinician. However, in defining and giving content to that partnership, there is a clear role for most, if not all, of the proposed duties; their value thus extends beyond the adversarial context in which they might first be thought to arise. (shrink)

The coefficients of internal consistency and retest reliability had been rarely investigated within the methodology of dream content analysis. Analyzing a dream series of elderly, healthy persons obtained from weekly telephone interviews, the internal consistency of a series of 20 dreams and retests after 4 or 22 weeks, respectively, had been computed. The findings indicate that dream recall and dream length are quite stable, but dream characteristics such as bizarreness and emotional tone underlie large intraindividual fluctuations. In order to obtain (...) reliable measures for these variables which will be important for correlational studies, including waking-life trait measures, one has to obtain as many dreams as possible (about 20) in a very short time period. Further research is needed to extend the present findings to diary dreams and laboratory dreams. (shrink)

In studying the thinkers discussed, we have generally used (translations of) their writings. The very breadth of this study makes one dependent upon ...

Medical screening is justified on the strength of the assumption that the earlier disease is detected, the better it is for the patient. On examination, however, the assumption turns out to be severely flawed, and inadequate anyway, since it is not only the patient with whom we should be concerned, but healthy people as well. Instead of making assumptions about the ill, we should prove a test's overall benefit to the individual taking it before we recommend it.