Vincent Rialle

Due to weak economies or ill-adapted public policies aggravated by the pandemic, official services dedicated to the unconditional reception and support of people in psychosocial distress in large urban areas are often put to the test. Here is the approach of the action research “Evolution after COVid-19 of the Invisibility of Precarities” (ECOVIP) dedicated to this phenomenon, as well as its first results concerning the precarity of unemployed “young” seniors (50-64 years old) in Lyon, France. This participative research is based on workshops that bring together professionals from both the front-line psychosocial field and other fields such as employment or work, and in which they are offered a free expression of their lived situations of reception of precarious people. The first results provided by the scientific and transparent analysis of these exchanges show both a fairly precise understanding of the institutional decision leading to increasing invisibility, and the emergence of innovative professional resources capable of curbing it.

Dans notre société de plus en plus digitalisée, avons-nous vraiment le choix d’adopter ou non les technologies? Comment cette digitalisation impacte-t-elle les personnes âgées en particulier et son écosystème? Quels sont les enjeux éthiques soulevés par cette digitalisation? Ce texte vise à amener des éléments de réflexions en lien avec ces enjeux selon le point de vue de divers experts des domaines de la technologie, du vieillissement et de la bioéthique. Ces experts se sont rencontrés lors d’un symposium ayant eu lieu à Angers, France, en octobre 2019. Le texte est un compte-rendu des échanges et points de vue de ces experts, ainsi que des discussions ouvertes qu’ils ont eues avec l’assistance, portant sur les principaux enjeux soulevés par cette digitalisation selon la perspective des personnes âgées, des proches-aidants, des soignants, de la société et de la recherche.

This paper presents work in progress on artificial intelligence in medicine (AIM) within the larger context of cognitive science. It introduces and develops the notion ofemergence both as an inevitable evolution of artificial intelligence towards machine learning programs and as the result of a synergistic co-operation between the physician and the computer. From this perspective, the emergence of knowledge takes placein fine in the expert's mind and is enhanced both by computerised strategies of induction and deduction, and by software abilities to dialogue, co-operate and function as a cognitive extension of the physician's intellectual capabilities. The proposed methodology gives the expert a prominent role which consists, first, of faithfully enunciating the descriptive features of his medical knowledge, thus giving the computer a precise description of his own perception of basic medicine, and secondly, of painstakingly gathering patients into computerised case bases which simulate exhaustive long-term memory. The AI capacities for knowledge elaboration are then triggered, giving rise to mathematically optimal diagnoses, prognoses, or treatment protocols which the physician may then evaluate, accept, reject, or adapt at his convenience, and finally append to a knowledge base. The idea of emergence embraces many issues concerning the purpose and intent of artificial intelligence in medical practice. Particularly, we address the representation problem as it is raised by classical decisional knowledge-based systems, and develop the notions of classifiers and hybrid systems as possible answers to this problem. Finally, since the whole methodology touches the problem of technological investment in health care, now inherent in modern medical practice, some ethical considerations accompany the exposé