Despite the great positive potential of AI, the AI ethics community has presented a rather gloomy picture of AI’s ethical implications. This paper examines the negativity within AI ethics through a philosophy of science lens. The prevailing negativity is a result of the particular way the discipline is institutionally organized, which pressures AI ethicists to portray AI in a critical light. As a consequence, the overall picture of AI offered by the AI ethics community is one-sided and negatively biased. We should be skeptical about the negative narrative promoted by AI ethics and explore ways of reforming the system.

Crashes involving self-driving cars at least superficially resemble trolley dilemmas. This article discusses what lessons machine ethicists working on the ethics of self-driving cars can learn from trolleyology. The article proceeds by providing an account of the trolley problem as a paradox and by distinguishing two types of solutions to the trolley problem. According to an optimistic solution, our case intuitions about trolley dilemmas are responding to morally relevant differences. The pessimistic solution denies that this is the case. An optimistic solution would yield first-order moral insights for the ethics of self-driving cars, but such a solution is difficult to come by. More plausible is the pessimistic solution, and it teaches us a methodological lesson. The lesson is that machine ethicists should discount case intuitions and instead rely on intuitions and judgments at a higher level of generality.

The recent decades have seen established liberal democracies expand their surveillance capacities on a massive scale. This article explores what is problematic about government surveillance by democracies. It proceeds by distinguishing three potential sources of concern: (1) the concern that governments diminish citizens’ privacy by collecting their data, (2) the concern that they diminish their privacy by accessing their data, and (3) the concern that the collected data may be used for objectionable purposes. Discussing the meaning and value of privacy, the article argues that only the latter two constitute compelling independent concerns. It then focuses particularly on the third concern, exploring the risk of government surveillance being used to enforce illegitimate laws. It discusses three legitimacy-related reasons why we should be worried about the expansion of surveillance capacities in established democracies: (1) Even established democracies might decay. There is a risk that surveillance capacities that are used for democratically legitimated purposes today will be used for poorly legitimated purposes in the future. (2) Surveillance may be used to enforce laws that lack legitimacy due to the disproportionate punishment attached to their violation. (3) The democratic procedures in established democracies fail to conform to the requirements formulated by mainstream theories of democratic legitimacy. Surveillance is thus used to enforce laws whose legitimacy is in doubt.

Recent decades have witnessed tremendous progress in artificial intelligence and in the development of autonomous systems that rely on artificial intelligence. Critics, however, have pointed to the difficulty of allocating responsibility for the actions of an autonomous system, especially when the autonomous system causes harm or damage. The highly autonomous behavior of such systems, for which neither the programmer, the manufacturer, nor the operator seems to be responsible, has been suspected to generate responsibility gaps. This has been the cause of much concern. In this article, I propose a more optimistic view on artificial intelligence, raising two challenges for responsibility gap pessimists. First, proponents of responsibility gaps must say more about when responsibility gaps occur. Once we accept a difficult-to-reject plausibility constraint on the emergence of such gaps, it becomes apparent that the situations in which responsibility gaps occur are unclear. Second, assuming that responsibility gaps occur, more must be said about why we should be concerned about such gaps in the first place. I proceed by defusing what I take to be the two most important concerns about responsibility gaps, one relating to the consequences of responsibility gaps and the other relating to violations of jus in bello.

AbstractSubjectivism about wellbeing rests on the idea that what is good for a person must ‘fit’ her, ‘resonate’ with her, not be ‘alien’ to her, etc. This idea has been called the ‘beating heart’ of subjectivism. In this article, I present the No-Beating-Heart Challenge for subjectivism, which holds that there is no satisfactory statement of this idea. I proceed by first identifying three criteria that any statement of the idea must meet if it is to provide support for subjectivism: Distinctness, Exclusiveness, and Explicitness. I then argue that no statement of this idea meets these criteria.

Digital Shadows as the aggregation, linkage and abstraction of data relating to physical objects are a central vision for the future of production. However, the majority of current research takes a technocentric approach, in which the human actors in production play a minor role. Here, the authors present an alternative anthropocentric perspective that highlights the potential and main challenges of extending the concept of Digital Shadows to humans. Following future research methodology, three prospections that illustrate use cases for Human Digital Shadows across organizational and hierarchical levels are developed: human-robot collaboration for manual work, decision support and work organization, as well as human resource management. Potentials and challenges are identified using separate SWOT analyses for the three prospections and common themes are emphasized in a concluding discussion.

Digitalization in the production sector aims at transferring concepts and methods from the Internet of Things (IoT) to the industry and is, as a result, currently reshaping the production area. Besides technological progress, changes in work processes and organization are relevant for a successful implementation of the “Internet of Production” (IoP). Focusing on the labor organization and organizational procedures emphasizes to consider intra-company factors such as (user) acceptance, ethical issues, and ergonomics in the context of IoP approaches. In the scope of this paper, a research approach is presented that considers these aspects from an intra-company perspective by conducting studies on the shop floor, control level and management level of companies in the production area. Focused on four central dimensions—governance, organization, capabilities, and interfaces—this contribution presents a research framework that is focused on a systematic integration and consideration of human aspects in the realization of the IoP.

Toleration is one of the core elements of a liberal polity, and yet it has come to be seen as puzzling, paradoxical and difficult. The aim of the present paper is to dispel three puzzles surrounding toleration. First, I will challenge the notion that it is difficult to see why tolerance should be a virtue given that it involves putting up with what one deems wrong. Second, I defuse the worry that the ideal of toleration is not fully realizable as toleration must necessarily be limited. Third, I take issue with the assumption that 'true' tolerance requires meta-tolerance, that is, that the issue of toleration must itself be approached in a 'tolerant' way.