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.

Artificial agents, particularly but not only those in the infosphere Floridi (Information – A very short introduction. Oxford University Press, Oxford, 2010a), extend the class of entities that can be involved in moral situations, for they can be correctly interpreted as entities that can perform actions with good or evil impact (moral agents). In this chapter, I clarify the concepts of agent and of artificial agent and then distinguish between issues concerning their moral behaviour vs. issues concerning their responsibility. The conclusion is that there is substantial and important scope, particularly in information ethics, for the concept of moral artificial agents not necessarily exhibiting free will, mental states or responsibility. This complements the more traditional approach, which considers whether artificial agents may have mental states, feelings, emotions and so forth. By focussing directly on “mind-less morality”, one is able to by-pass such question as well as other difficulties arising in Artificial Intelligence, in order to tackle some vital issues in contexts where artificial agents are increasingly part of the everyday environment (Floridi L, Metaphilos 39(4/5): 651–655, 2008a).