The potential development of self-driving cars (also known as autonomous vehicles or AVs – particularly Level 5 AVs) has called the attention of different interested parties. Yet, there are still only a few relevant international regulations on them, no emergency patterns accepted by communities and Original Equipment Manufacturers (OEMs), and no publicly accepted solutions to some of their pending ethical problems. Thus, this paper aims to provide some possible answers to these moral and practical dilemmas. In particular, we focus on (...) what AVs should do in no-win scenarios and on who should be held responsible for these types of decisions. A naturalistic perspective on ethics informs our proposal, which, we argue, could represent a pragmatic and realistic solution to the regulation of AVs. We discuss the proposals already set out in the current literature regarding both policy-making strategies and theoretical accounts. In fact, we consider and reject descriptive approaches to the problem as well as the option of using either a strict deontological view or a solely utilitarian one to set AVs’ ethical choices. Instead, to provide concrete answers to AVs’ ethical problems, we examine three hierarchical levels of decision-making processes: country-wide regulations, OEM policies, and buyers’ moral attitudes. By appropriately distributing ethical decisions and considering their practical implications, we maintain that our proposal based on ethical naturalism recognizes the importance of all stakeholders and allows the most able of them to take actions (the OEMs and buyers) to reflect on the moral leeway and weight of their options. (shrink)

A widespread need to explain the behavior and outcomes of AI-based systems has emerged, due to their ubiquitous presence. Thus, providing renewed momentum to the relatively new research area of eXplainable AI (XAI). Nowadays, the importance of XAI lies in the fact that the increasing control transference to this kind of system for decision making -or, at least, its use for assisting executive stakeholders- already affects many sensitive realms (as in Politics, Social Sciences, or Law). The decision-making power handover to (...) opaque AI systems makes mandatory explaining those, primarily in application scenarios where the stakeholders are unaware of both the high technology applied and the basic principles governing the technological solutions. The issue should not be reduced to a merely technical problem; the explainer would be compelled to transmit richer knowledge about the system (including its role within the informational ecosystem where he/she works). To achieve such an aim, the explainer could exploit, if necessary, practices from other scientific and humanistic areas. The first aim of the paper is to emphasize and justify the need for a multidisciplinary approach that is beneficiated from part of the scientific and philosophical corpus on Explaining, underscoring the particular nuances of the issue within the field of Data Science. The second objective is to develop some arguments justifying the authors’ bet by a more relevant role of ideas inspired by, on the one hand, formal techniques from Knowledge Representation and Reasoning, and on the other hand, the modeling of human reasoning when facing the explanation. This way, explaining modeling practices would seek a sound balance between the pure technical justification and the explainer-explainee agreement. (shrink)

This paper examines the ethical pitfalls and challenges that non-ethicists, such as researchers and programmers in the fields of computer science, artificial intelligence and robotics, face when building moral machines. Whether ethics is “computable” depends on how programmers understand ethics in the first place and on the adequacy of their understanding of the ethical problems and methodological challenges in these fields. Researchers and programmers face at least two types of problems due to their general lack of ethical knowledge or expertise. (...) The first type is so-called rookie mistakes, which could be addressed by providing these people with the necessary ethical knowledge. The second, more difficult methodological issue concerns areas of peer disagreement in ethics, where no easy solutions are currently available. This paper examines several existing approaches to highlight the ethical pitfalls and challenges involved. Familiarity with these and similar problems can help programmers to avoid pitfalls and build better moral machines. The paper concludes that ethical decisions regarding moral robots should be based on avoiding what is immoral in combination with a pluralistic ethical method of solving moral problems, rather than relying on a particular ethical approach, so as to avoid a normative bias. (shrink)

Trolley cases are widely considered central to the ethics of autonomous vehicles. We caution against this by identifying four problems. Trolley cases, given technical limitations, rest on assumptions that are in tension with one another. Furthermore, trolley cases illuminate only a limited range of ethical issues insofar as they cohere with a certain design framework. Furthermore, trolley cases seem to demand a moral answer when a political answer is called for. Finally, trolley cases might be epistemically problematic in several ways. (...) To put forward a positive proposal, we illustrate how ethical challenges arise from mundane driving situations. We argue that mundane situations are relevant because of the specificity they require and the scale they exhibit. We then illustrate some of the ethical challenges arising from optimizing for safety, balancing safety with other values such as mobility, and adjusting to incentives of legal frameworks. (shrink)

A recent interpretation of artificial intelligence (AI) (Floridi 2013, 2022) suggests that the implementation of AI demands the investigation of the binding conditions that make it possible to build and integrate artifacts into our lived world. Such artifacts can successfully interact with the world because our environment has been designed to be compatible with intelligent machines (such as robots). As the use of AI becomes ubiquitous in society, possibly leading to the formation of increasingly intelligent bio-technological unions, there will likely (...) be a coexistence of a plethora of micro-environments wrapped and tailored around humans and basic robots. The key element of this pervasive process will be the capacity to integrate biological realms in an infosphere suitable for the implementation of AI technologies. This process will require extensive datafication. This is because data is the basis of the logical-mathematical codes and models that drive and guide AI. This process will have huge consequences on workplaces, on workers, as well as on the decision-making processes required for the functioning of future societies. In this paper we will offer a comprehensive reflection on the moral and social implications of datafication as well as a set of considerations about its desirability, which will be informed by the following insights: (1) full protection of privacy may become structurally impossible, thus leading to undesirable forms of political and social control; (2) worker’s freedom may be reduced; (3) human creativity, imagination, and even divergence from AI logic might be channeled and possibly discouraged; (4) there will likely be a push towards efficiency and instrumental reason, which will become preeminent in production lines as well as in society. (shrink)

The characteristics of green intelligent engineering ethics emphasize the necessity of GI engineering ethics education. The ethics education of GI engineering is in the development stage, and it is urgent to fully understand the significance of evaluating the development of GI EEE. Only based on the GI manufacturing situation system to understand the implementation status of the core education of EEE can we objectively grasp the improvement space of GI EEE. In this study, the corresponding indicators were selected from three (...) dimensions of cultivation education, collaborative education, and situational education to form the element community of evaluation indicators. The fuzzy analytic hierarchy process and the fuzzy comprehensive evaluation method were used to empirically evaluate the implementation of the key mechanism of GI EEE. The results are as follows. The key education of GI EEE includes cultivation education of micro dimension, collaborative education of medium dimension, and situational education of macro dimension. The most important education is to strengthen the ethics education of GI engineering in the training process of college students. The coordination of GI EEE is becoming more and more important, and the integration and construction are the important pursuit of GI EEE. The cultivation education, collaborative education, and situational education of GI EEE are all at a general level. There is not only a gap between theory and practice in GI EEE but also insufficient attention to localization and coordination issues. The willingness of the government to participate in the ethical education of GI engineering is very insufficient. The optimized space of training education includes teaching cases and full-cycle ethical education. (shrink)

Much of the debate on the ethics of self-driving cars has revolved around trolley scenarios. This paper instead takes up the political or institutional question of who should decide how a self-driving car drives. Specifically, this paper is on the question of whether and why passengers should be able to control how their car drives. The paper reviews existing arguments—those for passenger ethics settings and for mandatory ethics settings respectively—and argues that they fail. Although the arguments are not successful, they (...) serve as the basis to formulate desiderata that any approach to regulating the driving behavior of self-driving cars ought to fulfill. The paper then proposes one way of designing passenger ethics settings that meets these desiderata. (shrink)

The introduction of self-driving vehicles gives rise to a large number of ethical issues that go beyond the common, extremely narrow, focus on improbable dilemma-like scenarios. This article provides a broad overview of realistic ethical issues related to self-driving vehicles. Some of the major topics covered are as follows: Strong opinions for and against driverless cars may give rise to severe social and political conflicts. A low tolerance for accidents caused by driverless vehicles may delay the introduction of driverless systems (...) that would substantially reduce the risks. Trade-offs will arise between safety and other requirement on the road traffic system. Over-reliance on the swift collision-avoiding reactions of self-driving vehicles can induce people to take dangerous actions, such as stepping out in front of a car, relying on its fast braking. Children travelling alone can violate safety instructions such as the use of seatbelts. Digital information about routes and destinations can be used to convey commercial and political messages to car users. If fast passage can be bought, then socio-economic segregation of road traffic may result. Terrorists and other criminals can hack into a vehicle and make it crash. They can also use self-driving vehicles for instance to carry bombs to their designed places of detonation or to wreak havoc on a country’s road system. (shrink)

The philosophical–ethical literature and the public debate on autonomous vehicles have been obsessed with ethical issues related to crashing. In this article, these discussions, including more empirical investigations, will be critically assessed. It is argued that a related and more pressing issue is questions concerning safety. For example, what should we require from autonomous vehicles when it comes to safety? What do we mean by ‘safety’? How do we measure it? In response to these questions, the article will present a (...) foundation for a continued discussion on these issues and an argument for why discussions about safety should be prioritized over ethical concerns related to crashing. (shrink)

Organizations such as the EU High-Level Expert Group on AI and the IEEE have recently formulated ethical principles and (moral) values that should be adhered to in the design and deployment of artificial intelligence (AI). These include respect for autonomy, non-maleficence, fairness, transparency, explainability, and accountability. But how can we ensure and verify that an AI system actually respects these values? To help answer this question, I propose an account for determining when an AI system can be said to embody (...) certain values. This account understands embodied values as the result of design activities intended to embed those values in such systems. AI systems are here understood as a special kind of sociotechnical system that, like traditional sociotechnical systems, are composed of technical artifacts, human agents, and institutions but—in addition—contain artificial agents and certain technical norms that regulate interactions between artificial agents and other elements of the system. The specific challenges and opportunities of embedding values in AI systems are discussed, and some lessons for better embedding values in AI systems are drawn. (shrink)

Ethical, legal and social implications are widely regarded as important considerations with respect to technological developments. Agile Worth-Oriented Systems Engineering is an innovative approach to incorporating ethically relevant criteria during agile development processes through a flexibly applicable methodology. First, a predefined model for the ethical evaluation of socio-technical systems is used to assess ethical issues according to different dimensions. The second part of AWOSE ensures that ethical issues are not only identified, but also systematically considered during the design of systems (...) based on information and communication technology. For this purpose, the findings from the first step are integrated with approaches from worth-centered development into a process model that, unlike previous approaches to ethical system development, is thoroughly compatible with agile methodologies like Scrum or Extreme Programming. Artifacts of worth-centered development called Worth Maps have been improved to guide the prioritization of development tasks as well as choices among design alternatives with respect to ethical implications. Furthermore, the improved Worth Maps facilitate the identification of suitable criteria for system evaluations in association to ethical concerns and desired positive outcomes of system usage. The potential of the AWOSE methodology has been demonstrated in the context of a technical system that supports elderly and people with particular handicaps. (shrink)

This paper proposes that autonomous vehicles should be designed to reduce light pollution. In support of this specific proposal, a moral assessment of autonomous vehicles more comprehensive than the dilemmatic life-and-death questions of trolley problem-style situations is presented. The paper therefore consists of two interrelated arguments. The first is that autonomous vehicles are currently still a technology in development, and not one that has acquired its definitive shape, meaning the design of both the vehicles and the surrounding infrastructure is open-ended. (...) Design for values is utilized to articulate a path forward, by which engineering ethics should strive to incorporate values into a technology during its development phase. Second, it is argued that nighttime lighting—a critical supporting infrastructure—should be a prima facie consideration for autonomous vehicles during their development phase. It is shown that a reduction in light pollution, and more boldly a better balance of lighting and darkness, can be achieved via the design of future autonomous vehicles. Two case studies are examined through which autonomous vehicles may be designed for “driving in the dark.” Nighttime lighting issues are thus inserted into a broader ethics of autonomous vehicles, while simultaneously introducing questions of autonomous vehicles into debates about light pollution. (shrink)

We motivate the desire for self-driving and explain its potential and limitations, and explore the need for—and potential implementation of—morals, ethics, and other value systems as complementary “capabilities” to the Deep Technologies behind self-driving. We consider how the incorporation of such systems may drive or slow adoption of high automation within vehicles. First, we explore the role for morals, ethics, and other value systems in self-driving through a representative hypothetical dilemma faced by a self-driving car. Through the lens of engineering, (...) we explain in simple terms common moral and ethical frameworks including utilitarianism, deontology, and virtue ethics before characterizing their relationship to the fundamental algorithms enabling self-driving. The concepts of behavior cloning, state-based modeling, and reinforcement learning are introduced, with some algorithms being more suitable for the implementation of value systems than others. We touch upon the contemporary cross-disciplinary landscape of morals and ethics in self-driving systems from a joint philosophical and technical perspective, and close with considerations for practitioners and the public, particularly as individuals may not appreciate the nuance and complexity of using imperfect information to navigate diverse scenarios and tough-to-quantify value systems, while “typical” software development reduces complex problems to black and white decision-making. (shrink)

Autonomous vehicles, and the larger socio-technical systems that they are a part of are likely to have a deep and lasting impact on our societies. Trust is a key value that will play a role in the development of autonomous driving systems. This paper suggests that trust of autonomous driving systems will impact the ways that these systems are taken up, the norms and laws that guide them and the design of the systems themselves. Further to this, in order to (...) have autonomous driving systems that are worthy of our trust, we need a superstructure of oversight and a process that designs trust into these systems from the outset. Rather than banning or avoiding all autonomous vehicles should a tragedy occur, despite these systems having some level of risk, we want resilient systems that can survive tragedies, and indeed, improve from them. I will argue that trust plays a role in developing these resilient systems. (shrink)

In this paper we focus on how automated vehicles can reduce the number of deaths and injuries in accident situations in order to protect public health. This is actually a problem not only of public health and ethics, but also of big data—not only in terms of all the different data that could be used to inform such decisions, but also in the sense of deciding how wide the scope of data should be. We identify three key different types of (...) data, including basic data, advanced data and preference data, provide an ethical analysis of the use of these different types of data and of different ways of prioritizing between pedestrians and passengers, and propose four rules that can help set ethical priorities for ethical data use and decision making by automated vehicles. (shrink)

This paper advocates for an ethical analysis of autonomous vehicle systems (AVSs) based on a moral epistemic pluralism. This paper contends that approaching the design of intricate social technologies, such as AVSs, is most effective when acknowledging a diverse range of values. Additionally, a comprehensive ethical framework for autonomous vehicles should be applied across two interconnected layers. The first layer centers on the individual level, where each autonomous vehicle becomes a unit of moral consideration. The second layer focuses on the (...) system level, directing moral attention toward the intricate autonomous vehicle system as a whole. Distinguishing the approach from metaphysical pluralism, the paper responds to counterarguments from a moral relativist and value monist perspectives. It concludes by emphasizing the necessity of embracing epistemic pluralism to navigate the complex ethical landscape of AVSs, urging a holistic understanding that transcends individual events and integrates system-level considerations. (shrink)

In this article we summarise some previously described proposals for ethical governance of autonomous vehicles, critique them, and offer an alternative solution. Rather than programming cars to react to crash situations in the same way as humans, having humans program pre-set responses for a wide range of different potential scenarios, or applying particular ethical theories, we suggest that decisions should be made jointly between humans and cars. Given that humans lack the requisite processing capacity, and computers lack the necessary ethical (...) capacity, the medical paradigm of advance care planning can be retooled for this new context. Advance car-crash planning provides a way to combine humans’ ethical preferences with the advanced data processing capacities of computers to enable shared decision making in collision situations. (shrink)