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The unprecedented development of medical informatics is constantly transforming the concept of expertise in medical sciences in a way that has far-reaching consequences for both the theory of knowledge and the philosophy of informatics. Deep medicine is based on the assumption that medical diagnosis should take into account the wide array of possible health factors involved in the diagnostic process, such as not only genome analysis alone, but also the metabolome (analysis of all body metabolites important for e.g. drug-drug interactions), (...) microbiome (i.e. analysis of all bodily microorganisms interacting with host cells) or exposome (analysis of all environmental factors triggering potentially harmful cell mutations, such as UV radiation, heavy metals, various carcinogens, etc.). Deep data analysis is of tantamount importance for personalized diagnosis but, at the same time, hardly achievable by a regular human being. However, adequately designed artificial intelligence (e.g. a deep neural network) can undeniably be of great help for finding correlations between symptoms and underlying diseases. Nowadays AI applies to nearly every aspect of medicine, starting from the data analysis of scientific literature, through the diagnostic process, to the act of communication between physicians and their patients. Medical image processing algorithms greatly enhance the chances of successful recognition of melanoma or intestinal polyps. Communication tools designed for physicians use techniques known from social media to provide users with an opportunity to consult the case with colleagues from the same discipline. Natural language processing tools significantly improve doctor-patient communication by the automation of note-taking. Is this enough to support the claim that the non-epistemic competences in medicine are becoming more and more important? Can we attribute expertise only to a person? How is medical informatics changing the way most people usually understand human-computer interactions? (shrink)

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Natural language is one of the most enigmatic and sophisticated human capabilities with regard to both its evolutionary history and the level of complexity. The diversity of positions and debates on this subject clearly demonstrates that it is not yet a part of a science but rather an amalgam of different issues capable of being analyzed philosophically. The scarcity of evidence, restrictions of the comparative method and continuous discussions on the adaptive status of language are only a handful of current (...) issues. The main aim of this paper is to provide a critical analysis of crucial current approaches to the problem of the reconstruction of language evolution and pinpoint the most important methodological and philosophical arguments in the discussion. The paper also supports the view that only the multi-level approach to the problem, which encompasses both the genetic and cladistic levels, can offer a satisfactory explanation. (shrink)

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