What is data ethics?

Abstract

This theme issue has the founding ambition of landscaping data ethics as a new branch of ethics that studies and evaluates moral problems related to data (including generation, recording, curation, processing, dissemination, sharing and use), algorithms (including artificial intelligence, artificial agents, machine learning and robots) and corresponding practices (including responsible innovation, programming, hacking and professional codes), in order to formulate and support morally good solutions (e.g. right conducts or right values). Data ethics builds on the foundation provided by computer and information ethics but, at the same time, it refines the approach endorsed so far in this research field, by shifting the level of abstraction of ethical enquiries, from being information-centric to being data-centric. This shift brings into focus the different moral dimensions of all kinds of data, even data that never translate directly into information but can be used to support actions or generate behaviours, for example. It highlights the need for ethical analyses to concentrate on the content and nature of computational operations—the interactions among hardware, software and data—rather than on the variety of digital technologies that enable them. And it emphasizes the complexity of the ethical challenges posed by data science. Because of such complexity, data ethics should be developed from the start as a macroethics, that is, as an overall framework that avoids narrow, ad hoc approaches and addresses the ethical impact and implications of data science and its applications within a consistent, holistic and inclusive framework. Only as a macroethics will data ethics provide solutions that can maximize the value of data science for our societies, for all of us and for our environments. This article is part of the themed issue ‘The ethical impact of data science’.

Resisting big data exploitations in public healthcare: free riding or distributive justice?

“…As de la Bellacasa () would assert, establishing and maintaining the technoscientific assemblage of a national healthcare database should not be about deprecating concerns, distorting agendas (Galis and Lee ) or excluding from translations those who disagree with it, based on binary (moral and epistemological) understandings of caring (or not) to ‘save lives’. If treated as a collective action in the context of deliberative politics (Welsh and Wynne ), choice could act as, for example, a barometer of ‘social acceptability’ (Floridi and Taddeo ) for big data programmes in healthcare – not only the ethical right of the public but also a distributed form of enforced public awareness, accountability, oversight and social responsibility.…”

From What to How: An Initial Review of Publicly Available AI Ethics Tools, Methods and Research to Translate Principles into Practices

“…As the availability of data on almost every aspect of life, and the sophistication of machine learning (ML) techniques, has increased (Lepri, Oliver, Letouzé, Pentland, & Vinck, 2018) so have the opportunities for improving both public and private life (Luciano Floridi & Taddeo, 2016). Society has greater control than it has ever had over outcomes related to: (1) who people can become; (2) what people can do; (3) what people can achieve; and (4) how people can interact with the world (Floridi and colleagues, 2018a).…”

Soft Ethics and the Governance of the Digital

“…On the governance of the digital, there is much to be said, and even more still to be understood and theorised, but one point is clear: the governance of the digital (henceforth digital governance), the ethics of the digital (henceforth digital ethics, also known as computer, information or data ethics (Floridi and Taddeo 2016)) and the regulation of the digital (henceforth digital regulation) are different normative approaches, complementary, but not to be confused with each other, in the following sense (see Fig. 1 for a visual representation).…”