Are trust relationships involving humans and artificial agents possible? This controversial question has become a hotly debated topic in the emerging field of machine ethics. Employing a model of trust advanced by Buechner and Tavani :39–51, 2011), I argue that the “short answer” to this question is yes. However, I also argue that a more complete and nuanced answer will require us to articulate the various levels of trust that are also possible in environments comprising both human agents and AAs. (...) In defending this view, I show how James Moor’s model for distinguishing four levels of ethical agents in the context of machine ethics :18–21, 2006) can help us to develop a framework that differentiates four levels of trust. Via a series of hypothetical scenarios, I illustrate each level of trust involved in HA–AA relationships. Finally, I argue that these levels of trust reflect three key factors or variables: the level of autonomy of the individual AAs involved, the degree of risk/vulnerability on the part of the HAs who place their trust in the AAs, and the kind of interactions that occur between the HAs and AAs in the trust environments. (shrink)

The paper examines the open problems that experts of space law shall increasingly address over the next few years, according to four different sets of legal issues. Such differentiation sheds light on what is old and what is new with today’s troubles of space law, e.g., the privatization of space, vis-à-vis the challenges that AI raises in this field. Some AI challenges depend on its unique features, e.g., autonomy and opacity, and how they affect pillars of the law, whether on (...) Earth or in space missions. The paper insists on a further class of legal issues that AI systems raise, however, only in outer space. We shall never overlook the constraints of a hazardous and hostile environment, such as on a mission between Mars and the Moon. The aim of this paper is to illustrate what is still mostly unexplored or in its infancy in this kind of research, namely, the fourfold ways in which the uniqueness of AI and that of outer space impact both ethical and legal standards. Such standards shall provide for thresholds of evaluation according to which courts and legislators evaluate the pros and cons of technology. Our claim is that a new generation of sui generis standards of space law, stricter or more flexible standards for AI systems in outer space, down to the “principle of equality” between human standards and robotic standards, will follow as a result of this twofold uniqueness of AI and of outer space. (shrink)

The debate about the ethical implications of Artificial Intelligence dates from the 1960s :741–742, 1960; Wiener in Cybernetics: or control and communication in the animal and the machine, MIT Press, New York, 1961). However, in recent years symbolic AI has been complemented and sometimes replaced by Neural Networks and Machine Learning techniques. This has vastly increased its potential utility and impact on society, with the consequence that the ethical debate has gone mainstream. Such a debate has primarily focused on principles—the (...) ‘what’ of AI ethics —rather than on practices, the ‘how.’ Awareness of the potential issues is increasing at a fast rate, but the AI community’s ability to take action to mitigate the associated risks is still at its infancy. Our intention in presenting this research is to contribute to closing the gap between principles and practices by constructing a typology that may help practically-minded developers apply ethics at each stage of the Machine Learning development pipeline, and to signal to researchers where further work is needed. The focus is exclusively on Machine Learning, but it is hoped that the results of this research may be easily applicable to other branches of AI. The article outlines the research method for creating this typology, the initial findings, and provides a summary of future research needs. (shrink)

PurposeTrust is a social factor at the foundations of human action. The pervasiveness of trust explains why it has been studied by a large variety of disciplines, and its complexity justifies the difficulties in reaching a shared understanding and definition. As for all the social factors, trust is continuously evolving as a result of the changes in social, economic and technological conditions. The internet and many other Information and Communication Technologies (ICT) solutions have changed organizational and social life. Such mutated (...) scenarios challenged what researchers know about trust, thus several studies tried to investigate the difference between online and traditional (physical) environments. The purpose of this paper is to solve this multi‐dimensional puzzle by presenting a conceptual framework that will take into consideration the complexity of ICT mediated‐trust.Design/methodology/approachThe extant literature still lacks a homogeneous framework and presents a large amount of different perspectives, each one addressing a very specific issue. By using the methodology suggested by Short and Cropanzano the paper proposes a conceptual model for understanding the dynamics of trust in online settings. In doing so the authors' adopted the Actor Network Theory conceptual frame for disentangling the ambiguous role of technology in its relation with trust.FindingsThis paper provides an ultimate conceptual model on trust in virtual settings.Research limitations/implicationsThe proposed model will help systematize the extant contributions and also identify the gaps that can be addressed by future researches.Originality/valueThe model permits the understanding of the dynamics of trust in online settings. (shrink)

We argue that while digital health technologies (e.g. artificial intelligence, smartphones, and virtual reality) present significant opportunities for improving the delivery of healthcare, key concepts that are used to evaluate and understand their impact can obscure significant ethical issues related to patient engagement and experience. Specifically, we focus on the concept of empowerment and ask whether it is adequate for addressing some significant ethical concerns that relate to digital health technologies for mental healthcare. We frame these concerns using five key (...) ethical principles for AI ethics (i.e. autonomy, beneficence, non-maleficence, justice, and explicability), which have their roots in the bioethical literature, in order to critically evaluate the role that digital health technologies will have in the future of digital healthcare. (shrink)