Although the map of technology ethics is expanding, the growing subdomains within it may raise misgivings. In a recent and very interesting article, Sætra and Danaher have argued that the current dynamic of sub-specialization is harmful to the ethics of technology. In this commentary, we offer three reasons to diminish their concern about ethical proliferation. We argue first that the problem of demarcation is weakened if we attend to other sub-disciplines of technology ethics not mentioned by these authors. We claim (...) secondly that the logic of sub-specializations is less problematic if one does adopt mixed models (combining internalist and externalist approaches) in applied ethics. We finally reject that clarity and distinction are necessary conditions for defining sub-fields within ethics of technology, defending the porosity and constructive nature of ethical disciplines. (shrink)

This paper provides a systematic literature review, analysis and discussion of methods that are proposed to practise ethics in research and innovation. Ethical considerations concerning the impacts of R&I are increasingly important, due to the quickening pace of technological innovation and the ubiquitous use of the outcomes of R&I processes in society. For this reason, several methods for practising ethics have been developed in different fields of R&I. The paper first of all presents a systematic search of academic sources that (...) present and discuss such methods. Secondly, it provides a categorisation of these methods according to three main kinds: ex ante methods, dealing with emerging technologies, intra methods, dealing with technology design, and ex post methods, dealing with ethical analysis of existing technologies. Thirdly, it discusses the methods by considering problems in the way they deal with the uncertainty of technological change, ethical technology design, the identification, analysis and resolving of ethical impacts of technologies and stakeholder participation. The results and discussion of our literature review are valuable for gaining an overview of the state of the art and serve as an outline of a future research agenda of methods for practising ethics in R&I. (shrink)

The capacity to collect and analyse data is growing exponentially. Referred to as ‘Big Data’, this scientific, social and technological trend has helped create destabilising amounts of information, which can challenge accepted social and ethical norms. Big Data remains a fuzzy idea, emerging across social, scientific, and business contexts sometimes seemingly related only by the gigantic size of the datasets being considered. As is often the case with the cutting edge of scientific and technological progress, understanding of the ethical implications (...) of Big Data lags behind. In order to bridge such a gap, this article systematically and comprehensively analyses academic literature concerning the ethical implications of Big Data, providing a watershed for future ethical investigations and regulations. Particular attention is paid to biomedical Big Data due to the inherent sensitivity of medical information. By means of a meta-analysis of the literature, a thematic narrative is provided to guide ethicists, data scientists, regulators and other stakeholders through what is already known or hypothesised about the ethical risks of this emerging and innovative phenomenon. Five key areas of concern are identified: informed consent, privacy, ownership, epistemology and objectivity, and ‘Big Data Divides’ created between those who have or lack the necessary resources to analyse increasingly large datasets. Critical gaps in the treatment of these themes are identified with suggestions for future research. Six additional areas of concern are then suggested which, although related have not yet attracted extensive debate in the existing literature. It is argued that they will require much closer scrutiny in the immediate future: the dangers of ignoring group-level ethical harms; the importance of epistemology in assessing the ethics of Big Data; the changing nature of fiduciary relationships that become increasingly data saturated; the need to distinguish between ‘academic’ and ‘commercial’ Big Data practices in terms of potential harm to data subjects; future problems with ownership of intellectual property generated from analysis of aggregated datasets; and the difficulty of providing meaningful access rights to individual data subjects that lack necessary resources. Considered together, these eleven themes provide a thorough critical framework to guide ethical assessment and governance of emerging Big Data practices. (shrink)

Human enhancement is one of the leading research topics in contemporary applied ethics. Interestingly, the widespread attention to the ethical aspects of future enhancement applications has generated misgivings. Are researchers who spend their time investigating the ethics of futuristic human enhancement scenarios acting in an ethically suboptimal manner? Are the methods they use to analyze future technological developments appropriate? Are institutions wasting resources by funding such research? In this article, I address the ethics of doing human enhancement ethics focusing on (...) two main concerns. The Methodological Problem refers to the question of how we should methodologically address the moral aspects of future enhancement applications. The Normative Problem refers to what is the normative justification for investigating and funding the research on the ethical aspects of future human enhancement. This article aims to give a satisfactory response to both meta-questions in order to ethically justify the inquiry into the ethical aspects of emerging enhancement technologies. (shrink)

In anticipatory governance and responsible innovation, anticipation is a key theoretical and practical dimension for promoting a more responsible governance of new and emerging sciences and technologies. Yet, anticipation has been subjected to a range of criticisms, such that many now see it as unnecessary for AG and RI. According to Alfred Nordmann, practices engaging with ‘the future’, when performed under certain conditions, may reify the future, diminish our ability to see what is happening, and/or reproduce the illusion of control (...) over the future. Several authors have stressed that these critiques fail to capture the heterogeneous character of anticipatory practices, and yet research on the question of what particular kind of socio-epistemic engagements with ‘the future’ AG and RI aim to enact through anticipation remains fragmentary and their underlying rationale under-theorised. This article aims to advance the theoretical characterisation and problematisation of anticipation as key interventive tools for AG and RI. By distinguishing between four modes of anticipation and heuristically testing them against Nordmann’s critiques, the article argues that despite his assessment failing to recognise the heterogeneity of anticipatory practices considered valuable for AG and RI, it reinforces the relevance of performing certain modes of anticipatory exercises, namely critical-hermeneutic ones. Thus, anticipation continues to be a necessary heuristic dimension for AG and RI. More concretely, the article maintains that such anticipatory heuristics may find their radical constructive and critical-reflective character in the dynamics of inclusive scrutiny and negotiation about the plausibility and desirability of the envisioned or created futures. (shrink)

This article proposes a conceptual mapping to outline salient properties and relations that allow for a knowledge transfer from the well-established greenwashing phenomenon to the more recent machinewashing. We account for relevant dissimilarities, indicating where conceptual boundaries may be drawn. Guided by a “reasoning by analogy” approach, the article addresses the structural analogy and machinewashing idiosyncrasies leading to a novel and theoretically informed model of machinewashing. Consequently, machinewashing is defined as a strategy that organizations adopt to engage in misleading behavior (...) about ethical Artificial Intelligence /algorithmic systems. Machinewashing involves misleading information about ethical AI communicated or omitted via words, visuals, or the underlying algorithm of AI itself. Furthermore, and going beyond greenwashing, machinewashing may be used for symbolic actions such as lobbying and prevention of stricter regulation. By outlining diverse theoretical foundations of the established greenwashing domain and their relation to specific research questions, the article proposes a machinewashing model and a set of theory-related research questions on the macro, meso, and micro-level for future machinewashing research. We conclude by stressing limitations and by outlining practical implications for organizations and policymakers. (shrink)