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.

The Fairness, Accountability, and Transparency (FAccT) literature tends to focus on bias as a problem that requires ex post solutions (e.g. fairness metrics), rather than addressing the underlying social and technical conditions that (re)produce it. In this article, we propose a complementary strategy that uses genealogy as a constructive, epistemic critique to explain algorithmic bias in terms of the conditions that enable it. We focus on XAI feature attributions (Shapley values) and counterfactual approaches as potential tools to gauge these conditions and offer two main contributions. One is constructive: we develop a theoretical framework to classify these approaches according to their relevance for bias as evidence of social disparities. We draw on Pearl’s ladder of causation (Causality: models, reasoning, and inference. Cambridge University Press, Cambridge, 2000, Causality, 2nd edn. Cambridge University Press, Cambridge, 2009. https://doi.org/10.1017/CBO9780511803161) to order these XAI approaches concerning their ability to answer fairness-relevant questions and identify fairness-relevant solutions. The other contribution is critical: we evaluate these approaches in terms of their assumptions about the role of protected characteristics in discriminatory outcomes. We achieve this by building on Kohler-Hausmann’s (Northwest Univ Law Rev 113(5):1163–1227, 2019) constructivist theory of discrimination. We derive three recommendations for XAI practitioners to develop and AI policymakers to regulate tools that address algorithmic bias in its conditions and hence mitigate its future occurrence.

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).

The previous chapters have provided a detailed overview of the variety of ethical challenges posed by the development of ICTs. By way of conclusion, in this epilogue I would like to invite the reader to look into the possible future of Information and Computer Ethics. More specifically, I shall try to forecast how the convergence of two fundamental trends of our times, globalization and the development of the information society, may interact with the ethical problems analysed in this book. The exercise will not be based on some untenable technological determinism. Humanity is, and will remain, firmly in charge of its destiny and hence be responsible for it. Rather, it will mean adopting the farmer's view that, with enough intelligence, toil and a bit of luck, one might be able to tell today what one will probably reap tomorrow. Before trying to ‘look into the seeds of time, and say which grain will grow and which will not’ (Shakespeare, Macbeth, Act I, Scene III, 59–62), two clarifications might be in order. First, the future of globalization is a phenomenon too complex even to sketch in this brief epilogue. For a synthetic, well-balanced and informed overview, the reader may wish to consult Held and McGrew (2001) and consider that this chapter is written from what Held et al. (1999)) have defined as a ‘transformationalist perspective’, according to which ‘globalization does not simply denote a shift in the extensity or scale of social relations and activity.

The post-Westphalian Nation State developed by becoming more and more an Information Society. However, in so doing, it progressively made itself less and less the main information agent, because what made the Nation State possible and then predominant, as a historical driving force in human politics, namely ICTs, is also what is now making it less central, in the social, political and economic life of humanity across the world. ICTs fluidify the topology of politics. They do not merely enable but actually promote (through management and empowerment) the agile, temporary and timely aggregation, disaggregation and re-aggregation of distributed groups around shared interests across old, rigid boundaries represented by social classes, political parties, ethnicity, language barriers, physical barriers, and so forth. This is generating a new tension between the Nation State, still understood as a major organisational institution, yet no longer monolithic but increasingly morphing into a multiagent system itself, and a variety of equally powerful, indeed sometimes even more politically influential and powerful, non-Statal organisations. Geo-politics is now global and increasingly non-territorial, but the Nation State still defines its identity and political legitimacy in terms of a sovereign territorial unit, as a Country. Such tension calls for a serious exercise in conceptual re-engineering: how should the new informational multiagent systems (MASs) be designed in such a way as to take full advantage of the socio-political progress made so far, while being able to deal successfully with the new global challenges (from the environment to the financial markets) that are undermining the legacy of that very progress? In the lecture, I shall defend an answer to this question in terms of a design of political MAS based on principles borrowed from information ethics.