Luciano Floridi

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Vývoj informačních a komunikačních technologií (ICT) radikálně proměňuje nejen to, jak rozumíme světu a jak vzájemně komunikujeme, ale také způsob, jakým se díváme sami na sebe a jak chápeme svou vlastní povahu, existenci a odpovědnost. Rozšíření ICT tak představuje čtvrtou revoluci v dlouhém procesu přehodnocování základní podstaty a role lidstva ve vesmíru: jakožto lidstvo netvoříme nehybný střed vesmíru (kopernikovská revoluce), nelišíme se nijak mimořádně od zbytku zvířecího světa (darwinovská revoluce) a zdaleka nejsme sami pro sebe ve svém vědomí zcela transparentní (freudovská revoluce). ICT nám nyní dávají najevo, že nepředstavujeme izolované, odpojené činitele, ale informační organismy, kteří spolu s jinými druhy těchto činitelů sdílejí globální prostředí, v konečném pohledu utvářené z informací, takzvanou infosféru (Turingova revoluce).

This book presents cutting edge research on the new ethical challenges posed by biomedical Big Data technologies and practices. 'Biomedical Big Data' refers to the analysis of aggregated, very large datasets to improve medical knowledge and clinical care. The book describes the ethical problems posed by aggregation of biomedical datasets and re-use/re-purposing of data, in areas such as privacy, consent, professionalism, power relationships, and ethical governance of Big Data platforms. Approaches and methods are discussed that can be used to address these problems to achieve the appropriate balance between the social goods of biomedical Big Data research and the safety and privacy of individuals. Seventeen original contributions analyse the ethical, social and related policy implications of the analysis and curation of biomedical Big Data, written by leading experts in the areas of biomedical research, medical and technology ethics, privacy, governance and data protection. The book advances our understanding of the ethical conundrums posed by biomedical Big Data, and shows how practitioners and policy-makers can address these issues going forward.

This book presents cutting edge research on the new ethical challenges posed by biomedical Big Data technologies and practices. ‘Biomedical Big Data’ refers to the analysis of aggregated, very large datasets to improve medical knowledge and clinical care. The book describes the ethical problems posed by aggregation of biomedical datasets and re-use/re-purposing of data, in areas such as privacy, consent, professionalism, power relationships, and ethical governance of Big Data platforms. Approaches and methods are discussed that can be used to address these problems to achieve the appropriate balance between the social goods of biomedical Big Data research and the safety and privacy of individuals. Seventeen original contributions analyse the ethical, social and related policy implications of the analysis and curation of biomedical Big Data, written by leading experts in the areas of biomedical research, medical and technology ethics, privacy, governance and data protection. The book advances our understanding of the ethical conundrums posed by biomedical Big Data, and shows how practitioners and policy-makers can address these issues going forward.

This paper is divided into two parts. In the first, I shall briefly analyse the phenomenon of “big data”, and argue that the real epistemological challenge posed by the zettabyte era is small patterns. The valuable undercurrents in the ocean of data that we are accumulating are invisible to the computationally-naked eye, so more and better technology will help. However, because the problem with big data is small patterns, ultimately, the game will be won by those who “know how to ask and answer questions” (Plato, Cratylus, 390c). This introduces the second part, concerning information quality (IQ): which data may be useful and relevant, and so worth collecting, curating, and querying, in order to exploit their valuable (small) patterns? I shall argue that the standard way of seeing IQ in terms of fit-for-purpose is correct but needs to be complemented by a methodology of abstraction, which allows IQ to be indexed to different purposes. This fundamental step can be taken by adopting a bi-categorical approach. This means distinguishing between purpose/s for which some information is produced (P-purpose) and purpose/s for which the same information is consumed (C-purpose). Such a bi-categorical approach in turn allows one to analyse a variety of so-called IQ dimensions, such as accuracy, completeness, consistency, and timeliness. I shall show that the bi-categorical approach lends itself to simple visualisations in terms of radar charts.

Infosfera di Luciano Floridi investe un ampio spettro di questioni, relative alla natura dell'informazione, degli agenti artificiali, della responsabilità nei sistemi multiagenti, dell'etica informatica, del ruolo dell'informazione nel ragionamento e nella logica, etc., nella consapevolezza che ci troviamo ad interagire in un ambiente intelligente ed ubiquo costituito di informazioni, che è già diventato più ampio delle rappresentazioni del mondo concepite in termini di cyberspazio o di spazio reticolare.

In Floridi (2005), I argued that a definition of semantic information in terms of alethically-neutral content–that is, strings of well-formed and meaningful data that can be additionally qualified as true or untrue (false, for the classicists among us), depending on supervening evaluations–provides only necessary but insufficient conditions: if some content is to qualify as semantic information, it must also be true. One speaks of false information in the same way as one qualifies someone as a false friend, (i.e. not a friend at all). This leads to a refinement of the initial definition into: [Def]: p qualifies as semantic information if and only if p is (constituted by) well-formed, meaningful and veridical data. [Def] captures the general consensus reached by the debate and mentioned at the outset of this section. According to it, semantic information is, strictly speaking, inherently truth-constituted and not a contingent truth-bearer, exactly like knowledge but unlike propositions or beliefs, for example, which are what they are independently of their truth values and then, because of their truth-aptness, may be further qualified alethically.