New technologies not only contribute greatly to society and the economy; they also involve fundamental societal shifts, challenging our values and ideas about ourselves and the world. With a view to aligning technological change and innovation with ethical values, the concept of responsible innovation advocates the inclusion of a variety of stakeholders, in particular from society. In shifting moral responsibility towards the producers of innovations, responsible innovation rejects the standard normative economic view that the ethical evaluation of innovations is a (...) matter of individual consumers’ market-based choices. However, in this article we argue that responsible innovation should not abandon all normative consideration of the individual outright, to which end we present an alternative normative economic approach based on preference learning. We show how this approach can provide an enhanced understanding of responsible innovation by clarifying the redistribution of moral responsibility and casting individuals in the normative role of co-innovators, rather than mere consumers. We argue that responsible innovation should enable individuals to form preferences and evaluate innovations, so as to align innovation with ethical demands. Finally, we show how our proposed approach can be put into practice in so-called laboratories in real-world contexts, using methods from the field of design. In short, drawing on normative economics, this article aims to establish a new understanding of responsible innovation that is conceptually sound and can form the basis for novel innovation practices. (shrink)

In this article, I shall argue that AI’s likely developments and possible challenges are best understood if we interpret AI not as a marriage between some biological-like intelligence and engineered artefacts, but as a divorce between agency and intelligence, that is, the ability to solve problems successfully and the necessity of being intelligent in doing so. I shall then look at five developments: (1) the growing shift from logic to statistics, (2) the progressive adaptation of the environment to AI rather (...) than of AI to the environment, (3) the increasing translation of difficult problems into complex problems, (4) the tension between regulative and constitutive rules underpinning areas of AI application, and (5) the push for synthetic data. (shrink)

What is the relation between the ethics, the law, and the governance of the digital? In this article I articulate and defend what I consider the most reasonable answer.

In previous works (Floridi 2018) I introduced the distinction between hard ethics (which may broadly be described as what is morally right and wrong independently of whether something is legal or illegal), and soft or post-compliance ethics (which focuses on what ought to be done over and above existing legislation). This paper analyses the applicability of soft ethics to the General Data Protection Regulation and advances the theory that soft ethics has a dual advantage—as both an opportunity strategy and a (...) risk management solution. (shrink)

An increasing number of technology firms are implementing processes to identify and evaluate the ethical risks of their systems and products. A key part of these review processes is to foresee potential impacts of these technologies on different groups of users. In this article, we use the expression Ethical Foresight Analysis to refer to a variety of analytical strategies for anticipating or predicting the ethical issues that new technological artefacts, services, and applications may raise. This article examines several existing EFA (...) methodologies currently in use. It identifies the purposes of ethical foresight, the kinds of methods that current methodologies employ, and the strengths and weaknesses of each of these current approaches. The conclusion is that a new kind of foresight analysis on the ethics of emerging technologies is both feasible and urgently needed. (shrink)