Traditionally, the manufacturer/operator of a machine is held (morally and legally) responsible for the consequences of its operation. Autonomous, learning machines, based on neural networks, genetic algorithms and agent architectures, create a new situation, where the manufacturer/operator of the machine is in principle not capable of predicting the future machine behaviour any more, and thus cannot be held morally responsible or liable for it. The society must decide between not using this kind of machine any more (which is not a (...) realistic option), or facing a responsibility gap, which cannot be bridged by traditional concepts of responsibility ascription. (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)

Current advances in research, development and application of artificial intelligence systems have yielded a far-reaching discourse on AI ethics. In consequence, a number of ethics guidelines have been released in recent years. These guidelines comprise normative principles and recommendations aimed to harness the “disruptive” potentials of new AI technologies. Designed as a semi-systematic evaluation, this paper analyzes and compares 22 guidelines, highlighting overlaps but also omissions. As a result, I give a detailed overview of the field of AI ethics. Finally, (...) I also examine to what extent the respective ethical principles and values are implemented in the practice of research, development and application of AI systems—and how the effectiveness in the demands of AI ethics can be improved. (shrink)

In this book, the author examines the ethical implications of Artificial Intelligence systems as they integrate and replace traditional social structures in new sociocognitive-technological environments. She discusses issues related to the integrity of researchers, technologists, and manufacturers as they design, construct, use, and manage artificially intelligent systems; formalisms for reasoning about moral decisions as part of the behavior of artificial autonomous systems such as agents and robots; and design methodologies for social agents based on societal, moral, and legal values. Throughout (...) the book the author discusses related work, conscious of both classical, philosophical treatments of ethical issues and the implications in modern, algorithmic systems, and she combines regular references and footnotes with suggestions for further reading. This short overview is suitable for undergraduate students, in both technical and non-technical courses, and for interested and concerned researchers, practitioners, and citizens. (shrink)

Volume 19, Issue 11, November 2019, Page 9-12.

Modern digital technologies—from web-based services to Artificial Intelligence (AI) solutions—increasingly affect the daily lives of billions of people. Such innovation brings huge opportunities, but also concerns about design, development, and deployment of digital technologies. This article identifies and discusses five clusters of risk in the international debate about digital ethics: ethics shopping; ethics bluewashing; ethics lobbying; ethics dumping; and ethics shirking.

This article reports the findings of AI4People, an Atomium—EISMD initiative designed to lay the foundations for a “Good AI Society”. We introduce the core opportunities and risks of AI for society; present a synthesis of five ethical principles that should undergird its development and adoption; and offer 20 concrete recommendations—to assess, to develop, to incentivise, and to support good AI—which in some cases may be undertaken directly by national or supranational policy makers, while in others may be led by other (...) stakeholders. If adopted, these recommendations would serve as a firm foundation for the establishment of a Good AI Society. (shrink)

Artificial intelligence (AI) is increasingly being developed for use in medicine, including for diagnosis and in treatment decision making. The use of AI in medical treatment raises many ethical issues that are yet to be explored in depth by bioethicists. In this paper, I focus specifically on the relationship between the ethical ideal of shared decision making and AI systems that generate treatment recommendations, using the example of IBM’s Watson for Oncology. I argue that use of this type of system (...) creates both important risks and significant opportunities for promoting shared decision making. If value judgements are fixed and covert in AI systems, then we risk a shift back to more paternalistic medical care. However, if designed and used in an ethically informed way, AI could offer a potentially powerful way of supporting shared decision making. It could be used to incorporate explicit value reflection, promoting patient autonomy. In the context of medical treatment, we need value-flexible AI that can both respond to the values and treatment goals of individual patients and support clinicians to engage in shared decision making. (shrink)

Book reviewed in this article: Principles of Biomedical Ethics. By Tom L. Beauchamp and James F. Childress.

This paper pertains to research works aiming at linking ethics and automated reasoning in autonomous machines. It focuses on a formal approach that is intended to be the basis of an artificial agent’s reasoning that could be considered by a human observer as an ethical reasoning. The approach includes some formal tools to describe a situation and models of ethical principles that are designed to automatically compute a judgement on possible decisions that can be made in a given situation and (...) explain why a given decision is ethically acceptable or not. It is illustrated on three ethical frameworks—utilitarian ethics, deontological ethics and the Doctrine of Double effect whose formal models are tested on ethical dilemmas so as to examine how they respond to those dilemmas and to highlight the issues at stake when a formal approach to ethical concepts is considered. The whole approach is instantiated on the drone dilemma, a thought experiment we have designed; this allows the discrepancies that exist between the judgements of the various ethical frameworks to be shown. The final discussion allows us to highlight the different sources of subjectivity of the approach, despite the fact that concepts are expressed in a more rigorous way than in natural language: indeed, the formal approach enables subjectivity to be identified and located more precisely. (shrink)

In the past few years, scholars have been questioning whether the current approach in data ethics based on the higher level case studies and general principles is effective. In particular, some have been complaining that such an approach to ethics is difficult to be applied and to be taught in the context of data science. In response to these concerns, there have been discussions about how ethics should be “embedded” in the practice of data science, in the sense of showing (...) how ethical issues emerge in small technical choices made by data scientists in their day-to-day activities, and how such an approach can be used to teach data ethics. However, a precise description of how such proposals have to be theoretically conceived and could be operationalized has been lacking. In this article, we propose a full-fledged characterization of ‘embedding’ ethics, and how this can be applied especially to the problem of teaching data science ethics. Using the emerging model of ‘microethics’, we propose a way of teaching daily responsibility in digital activities that is connected to the higher level ethical challenges discussed in digital/data ethics. We ground this microethical approach into a virtue theory framework, by stressing that the goal of a microethics is to foster the cultivation of moral virtues. After delineating this approach of embedding ethics in theoretical detail, this article discusses a concrete example of how such a ‘micro-virtue ethics’ approach could be practically taught to data science students. (shrink)

The use of Intelligent Assistive Technology in dementia care opens the prospects of reducing the global burden of dementia and enabling novel opportunities to improve the lives of dementia patients. However, with current adoption rates being reportedly low, the potential of IATs might remain under-expressed as long as the reasons for suboptimal adoption remain unaddressed. Among these, ethical and social considerations are critical. This article reviews the spectrum of IATs for dementia and investigates the prevalence of ethical considerations in the (...) design of current IATs. Our screening shows that a significant portion of current IATs is designed in the absence of explicit ethical considerations. These results suggest that the lack of ethical consideration might be a codeterminant of current structural limitations in the translation of IATs from designing labs to bedside. Based on these data, we call for a coordinated effort to proactively incorporate ethical considerations early in the design and development of new products. (shrink)

The notion that it is useful to specify norms progressively in order to resolve doubts about what to do, which I developed initially in a 1990 article, has been only partly assimilated by the bioethics literature. The thought is not just that it is helpful to work with relatively specific norms. It is more than that: specification can replace deductive subsumption and balancing. Here I argue against two versions of reliance on balancing that are prominent in recent bioethical discussions. Without (...) meaning to address the substance or the overall merits of either view I criticize, I attack Gert, Culver and Clouser's implicit reliance on some overall dimension of balancing as a basis of resolving conflicts among norms and Beauchamp and Childress's residual acceptance of 'justified balancing'. The former authors' description of resolving conflicts depends upon a type of value commensurability that (as they otherwise seem to admit) does not obtain, while the latter authors' role for justified balancing would be better served by continued specification. (shrink)

This paper responds to the commentaries from Stacy Carter and Alan Cribb. We pick up on two main themes in our response. First, we reflect on how the process of setting standards for empirical bioethics research entails drawing boundaries around what research counts as empirical bioethics research, and we discuss whether the standards agreed in the consensus process draw these boundaries correctly. Second, we expand on the discussion in the original paper of the role and significance of the concept of (...) ‘integrating’ empirical methods and ethical argument as a standard for research practice within empirical bioethics. (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 chapter, 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 chapter 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)