Many believe that a suitably programmed computer could act for its own goals and experience feelings. I challenge this view and argue that agency, mental causation and qualia are all founded in the unique, homeostatic nature of living matter. The theory was formulated for coherence with the concept of an agent, neuroscientific data and laws of physics. By this method, I infer that a successful action is homeostatic for its agent and can be caused by a feeling - which does (...) not motivate as a force, but as a control signal. From brain research and the locality principle of physics, I surmise that qualia are a fundamental, biological form of energy generated in specialized neurons. Subjectivity is explained as thermodynamically necessary on the supposition that, by converting action potentials to feelings, the neural cells avert damage from the electrochemical pulses. In exchange for this entropic benefit, phenomenal energy is spent as and where it is produced - which precludes the objective observation of qualia. (shrink)

The notion of responsible innovation suggests that innovators carry additional responsibilities beyond those commonly suggested. In this paper, we will discuss the meaning of these novel responsibilities focusing on two philosophical problems of attributing such responsibilities to innovators. The first is the allocation of responsibilities to innovators. Innovation is a process that involves a multiplicity of agents and unpredictable, far-reaching causal chains from innovation to social impacts, which creates great uncertainty. A second problem is constituted by possible trade-offs between different (...) kinds of responsibility. It is evident that attributing backward-looking responsibility for product failures diminishes the willingness to learn about such defects and to take forward-looking responsibility. We will argue that these problems can be overcome by elaborating what it is exactly that innovators are responsible for. In this manner, we will distinguish more clearly between holding responsible and taking responsibility. This opens a space for ‘supererogatory’ responsibilities. Second, we will argue that both innovation processes and outcomes can be objects of innovators’ responsibility. Third, we will analyze different kinds of responsibility and show that the functions of their attribution are not necessarily contradictory. Based on this conceptual refinement, we will argue that accountability, responsibility-as-virtue and the willingness to take responsibility are crucial for responsible innovation. (shrink)

The paper has two goals. The first is presenting the main results of the recent report Ethics of Connected and Automated Vehicles: recommendations on road safety, privacy, fairness, explainability and responsibility written by the Horizon 2020 European Commission Expert Group to advise on specific ethical issues raised by driverless mobility, of which the author of this paper has been member and rapporteur. The second is presenting some broader ethical and philosophical implications of these recommendations, and using these to contribute to (...) the establishment of Ethics of Transportation as an independent branch of applied ethics. The recent debate on the ethics of Connected and Automated Vehicles presents a paradox and an opportunity. The paradox is the presence of a flourishing debate on the ethics of one very specific transportation technology without ethics of transportation being in itself a well-established academic discipline. The opportunity is that now that a spotlight has been switched on the ethical dimensions of CAVs it may be easier to establish a broader debate on ethics of transportation. While the 20 recommendations of the EU report are grouped in three macro-areas: road safety, data ethics, and responsibility, in this paper they will be grouped according to eight philosophical themes: Responsible Innovation, road justice, road safety, freedom, human control, privacy, data fairness, responsibility. These are proposed as the first topics for a new ethics of transportation. (shrink)

The notion of “responsibility gap” with artificial intelligence (AI) was originally introduced in the philosophical debate to indicate the concern that “learning automata” may make more difficult or impossible to attribute moral culpability to persons for untoward events. Building on literature in moral and legal philosophy, and ethics of technology, the paper proposes a broader and more comprehensive analysis of the responsibility gap. The responsibility gap, it is argued, is not one problem but a set of at least four interconnected (...) problems – gaps in culpability, moral and public accountability, active responsibility—caused by different sources, some technical, other organisational, legal, ethical, and societal. Responsibility gaps may also happen with non-learning systems. The paper clarifies which aspect of AI may cause which gap in which form of responsibility, and why each of these gaps matter. It proposes a critical review of partial and non-satisfactory attempts to address the responsibility gap: those which present it as a new and intractable problem (“fatalism”), those which dismiss it as a false problem (“deflationism”), and those which reduce it to only one of its dimensions or sources and/or present it as a problem that can be solved by simply introducing new technical and/or legal tools (“solutionism”). The paper also outlines a more comprehensive approach to address the responsibility gaps with AI in their entirety, based on the idea of designing socio-technical systems for “meaningful human control", that is systems aligned with the relevant human reasons and capacities. (shrink)

The Safe-by-Design approach in synthetic biology holds the promise of designing the building blocks of life in an organism guided by the value of safety. This paves a new way for using biotechnologies safely. However, the Safe-by-Design approach moves the bulk of the responsibility for safety to the actors in the research and development phase. Also, it assumes that safety can be defined and understood by all stakeholders in the same way. These assumptions are problematic and might actually undermine safety. (...) This research explores these assumptions through the use of a Group Decision Room. In this set up, anonymous and non-anonymous deliberation methods are used for different stakeholders to exchange views. During the session, a potential synthetic biology application is used as a case for investigation: the Food Warden, a biosensor contained in meat packaging for indicating the freshness of meat. Participants discuss what potential issues might arise, how responsibilities should be distributed in a forward-looking way, who is to blame if something would go wrong. They are also asked what safety and responsibility mean at different phases, and for different stakeholders. The results of the session are not generalizable, but provide valuable insights. Issues of safety cannot all be taken care of in the R&D phase. Also, when things go wrong, there are proximal and distal causes to consider. In addition, capacities of actors play an important role in defining their responsibilities. Last but not least, this research provides a new perspective on the role of instruction manuals in achieving safety. (shrink)

This article reinvigorates a key question in publication ethics: Is there research that it is permissible to conduct but that ought not to be published? The article raises the question in relation to two recent medical studies. It is argued that the publication of these studies may cause significant harm to individuals, that editors of medical journals have a moral responsibility for such harm, that denial of publication is inadequate as an instrument to fulfil this moral responsibility and that internationally (...) acknowledged publication ethics codes should incorporate this aspect of editors’ moral responsibility. (shrink)

AI has numerous applications and in various fields, including the military domain. The increase in the degree of autonomy in some decision-making systems leads to discussions on the possible future use of lethal autonomous weapons systems (LAWS). A central issue in these discussions is the assignment of moral responsibility for some AI-based outcomes. Several authors claim that the high autonomous capability of such systems leads to a so-called “responsibility gap.” In recent years, there has been a surge in philosophical literature (...) around the concept of responsibility gaps and different solutions have been devised to close or bridge these gaps. In order to move forward in the research around LAWS and the problem of responsibility, it is important to increase our understanding of the different perspectives and discussions in this debate. This paper attempts to do so by disentangling the various arguments and providing a critical overview. After giving a brief outline of the state of the technology of LAWS, I will review the debates over responsibility gaps using three differentiators: those who believe in the existence of responsibility gaps versus those who do not, those who hold that responsibility gaps constitute a new moral problem versus those who argue they do not, and those who claim that solutions can be successful as opposed to those who believe that it is an unsolvable problem. (shrink)

Many morally significant outcomes can be brought about only if several individuals contribute to them. However, individual contributions to collective outcomes often fail to have morally significant effects on their own. Some have concluded from this that it is permissible to do nothing. What I call ‘the problem of insignificant hands’ is the challenge of determining whether and when people are obligated to contribute. For this to be the case, I argue, the prospect of helping to bring about the outcome (...) has to be good enough. Furthermore, the individual must be in a position to increase the probability of its being brought about to an appropriate extent. Finally, I argue that when too few are willing to contribute, people may have a duty to increase their number. Thus, someone can be obligated to contribute or to get others to contribute. This prospect account is consistent with Kantianism, contractualism and rule consequentialism but inconsistent with act consequentialism. (shrink)

Many morally significant outcomes can be brought about only if several individuals contribute to them. However, individual contributions to collective outcomes often fail to have morally significant effects on their own. Some have concluded from this that it is permissible to do nothing. What I call ‘the problem of insignificant hands’ is the challenge of determining whether and when people are obligated to contribute. For this to be the case, I argue, the prospect of helping to bring about the outcome (...) has to be good enough. Furthermore, the individual must be in a position to increase the probability of its being brought about to an appropriate extent. Finally, I argue that when too few are willing to contribute, people may have a duty to increase their number. Thus, someone can be obligated to contribute or to get others to contribute. This prospect account is consistent with Kantianism, contractualism and rule consequentialism but inconsistent with act consequentialism. (shrink)

The purpose of this paper is to discuss the responsibility of AI experts for guiding the development of AI in a desirable direction. More specifically, the aim is to answer the following research question: To what extent are AI experts responsible in a forward-looking way for effects of AI technology that go beyond the immediate concerns of the programmer or designer? AI experts, in this paper conceptualised as experts regarding the technological aspects of AI, have knowledge and control of AI (...) technology that non-experts do not have. Drawing on responsibility theory, theories of the policy process, and critical algorithm studies, we discuss to what extent this capacity, and the positions that these experts have to influence the AI development, make AI experts responsible in a forward-looking sense for consequences of the use of AI technology. We conclude that, as a professional collective, AI experts, to some extent, are responsible in a forward-looking sense for consequences of use of AI technology that they could foresee, but with the risk of increased influence of AI experts at the expense of other actors. It is crucial that a diversity of actors is included in democratic processes on the future development of AI, but for this to be meaningful, AI experts need to take responsibility for how the AI technology they develop affects public deliberation. (shrink)

Who should be the author(s) of an academic paper? This question is becoming increasingly pressing, due to the increasing prevalence and scale of scientific collaboration, and the corresponding diversity of authorship practices in different disciplines and subdisciplines. This paper addresses the conceptual issues underlying authorship, with an eye to ameliorating authorship practices. The first part of the paper distinguishes five roles played by authorship attributions: allocating credit, constructing a speaker, enabling credibility judgements, supporting accountability, and creating an intellectual marketplace. The (...) second part of the paper argues that distinguishing these functions helps us see that at least some of the confusions around authorship are due to tensions between these functions. The final part of the paper suggests a way to resolve these conceptual confusions, which we will call the CSWG proposal. This proposal suggests replacing authorship with a bundle of roles tailored to the functions of authorship—contributor, spokesperson, writer, and guarantor—which can be distributed in a number of different ways. (shrink)

To support the trustworthiness of AI systems, it is essential to have precise methods to determine what or who is to account for the behaviour, or the outcome, of AI systems. The assignment of responsibility to an AI system is closely related to the identification of individuals or elements that have caused the outcome of the AI system. In this work, we present an overview of approaches that aim at modelling responsibility of AI systems, discuss their advantages and shortcomings to (...) deal with various aspects of the notion of responsibility, and present research gaps and ways forward. (shrink)

To develop more effective ethics education for cross-cultural and international engineering, a study was conducted to determine what Chinese engineering students have learned and think about ethics. Recent research shows traditional approaches to ethics education are potentially ineffective, but also points towards ways of improving ethical behaviors. China is the world’s most populous country, graduating and employing the highest number of STEM majors, although little empirical research exists about the ethical knowledge and perspectives of Chinese engineering students. When compared to (...) engineering students in the US, Chinese engineering students received less ethics education; the form of the education they did receive stressed virtue ethics or the development of moral character; conceive of ethics in contradistinction to the law, where ethics deals with matters of right and wrong not covered by legality. Based on these findings and research in moral psychology and behavioral ethics, recommendations are made for improving engineering ethics education both in China and abroad. (shrink)

As artificial intelligence becomes more sophisticated and robots approach autonomous decision-making, debates about how to assign moral responsibility have gained importance, urgency, and sophistication. Answering Stenseke’s (2022a) call for scaffolds that can help us classify views and commitments, we think the current debate space can be represented hierarchically, as answers to key questions. We use the resulting taxonomy of five stances to differentiate—and defend—what is known as the “blank check” proposal. According to this proposal, a person activating a robot could (...) willingly make themselves answerable for whatever events ensue, even if those events stem from the robot’s autonomous decision(s). This blank check solution was originally proposed in the context of automated warfare (Champagne & Tonkens, 2015), but we extend it to cover all robots. We argue that, because moral answerability in the blank check is accepted voluntarily and before bad outcomes are known, it proves superior to alternative ways of assigning blame. We end by highlighting how, in addition to being just, this self-initiated and prospective moral answerability for robot harm provides deterrence that the four other stances cannot match. (shrink)

We argue that explainable artificial intelligence (XAI), specifically reason-giving XAI, often constitutes the most suitable way of ensuring that someone can properly be held responsible for decisions that are based on the outputs of artificial intelligent (AI) systems. We first show that, to close moral responsibility gaps (Matthias 2004), often a human in the loop is needed who is directly responsible for particular AI-supported decisions. Second, we appeal to the epistemic condition on moral responsibility to argue that, in order to (...) be responsible for her decision, the human in the loop has to have an explanation available of the system’s recommendation. Reason explanations are especially well-suited to this end and we examine whether – and how – it might be possible to make such explanations fit with AI systems. We support our claims by focusing on a case of disagreement between human in the loop and AI system. (shrink)