Recent efforts in a range of scientific fields have emphasised research and methods concerning individual differences and individualisation. This article brings together various scientific disciplines—ecology, evolution, and animal behaviour; medicine and psychiatry; public health and sport/exercise science; sociology; psychology; economics and management science—and presents their research on individualisation. We then clarify the concept of individualisation as it appears in the disciplinary casework by distinguishing three kinds of individualisation studied in and across these disciplines: Individualisation ONE as creating/changing individual differences (the (...) process that generates differences between individuals: intrapopulation or intraspecific variation/heterogeneity); Individualisation TWO as individualising applications (the tailoring or customising of something—information, treatment, a product or service, etc.—for an individual or specific group of individuals); and Individualisation THREE as social changes influencing autonomy, risk, and responsibilities (the process discussed under the rubric of sociological individualisation theory). Moreover, we analyse conceptual links between individualisation and individuality, and characterise different sorts of individuality that the disciplines study. This paper aims to promote interdisciplinary research concerning individualisation by establishing a common conceptual-theoretical basis, while leaving room for disciplinary differences. (shrink)

Trust relations in the health services have changed from asymmetrical paternalism to symmetrical autonomy-based participation, according to a common account. The promises of personalized medicine emphasizing empowerment of the individual through active participation in managing her health, disease and well-being, is characteristic of symmetrical trust. In the influential Kantian account of autonomy, active participation in management of own health is not only an opportunity, but an obligation. Personalized medicine is made possible by the digitalization of medicine with an ensuing increased (...) tailoring of diagnostics, treatment and prevention to the individual. The ideal is to increase wellness by minimizing the layer of interpretation and translation between relevant health information and the patient or user. Arguably, this opens for a new level of autonomy through increased participation in treatment and prevention, and by that, increased empowerment of the individual. However, the empirical realities reveal a more complicated landscape disturbed by information ‘noise’ and involving a number of complementary areas of expertise and technologies, hiding the source and logic of data interpretation. This has lead to calls for a return to a mild form of paternalism, allowing expertise coaching of patients and even withholding information, with patients escaping responsibility through blind or lazy trust. This is morally unacceptable, according to Kant’s ideal of enlightenment, as we have a duty to take responsibility by trusting others reflexively, even as patients. Realizing the promises of personalized medicine requires a system of institutional controls of information and diagnostics, accessible for non-specialists, supported by medical expertise that can function as the accountable gate-keeper taking moral responsibility required for an active, reflexive trust. (shrink)

The genomics community has frequently compared advances in sequencing to advances in microelectronics. Lately there have been many claims, including by the National Human Genome Research Institute, that genomics is outpacing developments in computing as measured by Moore's law – the notion that computers double in processing capability per dollar spent every 18-24 months. Celebrations of the “$1000 genome” and other speed-related sequencing milestones might be dismissed as a distraction from genomics' slowness in delivering clinical breakthroughs, but the fact that (...) such celebrations have been persistently encouraged by the NHGRI reveals a great deal about the priorities and expectations of the American general public, the intended audience of the genomics–computing comparison. By delving into the history of speculative thinking about sequencing and computing, this article demonstrates just how much more receptive to high-risk/high-payoff ventures the NIH and the general public have become. The article also provides access to some of the roots and consequences of the association of “innovation talk” with genomics, and the means to look past that association to the less glamorous contributions of the NHGRI to building the field of genomics. (shrink)