Synaesthetes persistently perceive certain stimuli as systematically accompanied by illusory colours, even though they know those colours to be illusory. This appears to contrast with cases where a subject’s colour vision adapts to systematic distortions caused by wearing coloured goggles. Given that each case involves longstanding systematic distortion of colour perception that the subjects recognize as such, how can a theory of colour perception explain the fact that perceptual adaptation occurs in one case but not the other? I argue that (...) these cases and the relationship between them can be made sense of in light of an existing view of colour perception. Understanding colours as ways in which objects and surfaces modify light, perceived through grasping patterns and variations in colour appearances, provides a framework from which the cases and their apparent disanalogy can be predicted and explained. This theory’s ability to accommodate these cases constitutes further empirical evidence in its favour. (shrink)

Background The twenty first- century marked the exponential growth in the use of intelligent robots and artificial intelligent in nursing compared to the previous decades. To the best of our knowledge, this article is first in responding to question, “Can nurses in clinical practice ascribe responsibility to intelligent robots and artificial intelligence when they commit errors?”. Purpose The objective of this article is to present two worldviews (anthropocentrism and biocentrism) in responding to the question at hand chosen based on the (...) roles of the entities involved in the use of intelligent robots and artificial intelligence in nursing. Methods The development of this article was motivated by the immense discoveries, the current landscape, and nurses’ role in relation to advanced technologies in healthcare. The paper begins the discussion by situating the use of intelligent robots and artificial intelligence in nursing and healthcare and presenting its ethical and moral implications. Then, we presented the two worldviews: anthropocentrism and biocentrism which are used to respond to the task at hand. Results Anthropocentrism puts humans in the center in terms of moral standing and thus responsibility rests on them alone. Biocentrism declares that all creations deserve moral consideration and thus responsibility is equally allocated to all entities. Within these two worldviews, consensus development was offered to resolve these issues. Consensus provides clarity and democracy between and among the societies. Conclusions The findings of this article can be basis in (1) instituting mechanisms of robust peer review and a rigorous series of simulation before adopting or implementing intelligent robots and artificial intelligence in clinical practice; (2) education and training of highly specialized nurse practitioners who can be focal persons in responding to ethical and moral issues with regard to these advanced technologies; and (3) harmonization of robotics research, manufacturing, and clinical practice. (shrink)

The current research aims to answer the following question: “who will be held responsible for harm involving an artificial intelligence system?” Drawing upon the literature on moral judgments, we assert that when people perceive an AI system’s action as causing harm to others, they will assign blame to different entity groups involved in an AI’s life cycle, including the company, the developer team, and even the AI system itself, especially when such harm is perceived to be intentional. Drawing upon the (...) theory of mind perception, we hypothesized that two dimensions of mind: perceived agency—attributing intention, reasoning, pursuing goals, and communicating to AI, and perceived experience—attributing emotional states, such as feeling pain and pleasure, personality, and consciousness to AI—mediated the relationship between perceived intentional harm and blame judgments toward AI. We also predicted that people are likely to attribute higher mind characteristics to AI when harm is perceived to be directed to humans than when it is perceived to be directed to non-humans. We tested our research model in three experiments. In all experiments, we found that perceived intentional harm led to blame judgments toward AI. In two experiments, we found perceived experience, not agency, mediated the relationship between perceived intentional harm and blame judgments. We also found that companies and developers were held responsible for moral violations involving AI, with developers received the most blame among the entities involved. Our third experiment reconciles the findings by showing that perceived intentional harm directed to a non-human entity did not lead to increased attributions of mind to AI. These findings have implications for theory and practice concerning unethical outcomes and behavior associated with AI use. (shrink)

It is frequently demanded that AI-based Decision Support Tools (AI-DSTs) ought to be both explainable to, and trusted by, those who use them. The joint pursuit of these two principles is ordinarily believed to be uncontroversial. In fact, a common view is that AI systems should be made explainable so that they can be trusted, and in turn, accepted by decision-makers. However, the moral scope of these two principles extends far beyond this particular instrumental connection. This paper argues that if (...) we were to account for the rich and diverse moral reasons that ground the call for explainable AI, and fully consider what it means to “trust” AI in a descriptively rich sense of the term, we would uncover a deep and persistent tension between the two principles. For explainable AI to usefully serve the pursuit of normatively desirable goals, decision-makers must carefully monitor and critically reflect on the content of an AI-DST’s explanation. This entails a deliberative attitude. Conversely, calls for trust in AI-DSTs imply the disposition to put questions about their reliability out of mind. This entails an unquestioning attitude. As such, the joint pursuit of explainable and trusted AI calls on decision-makers to simultaneously adopt incompatible attitudes towards their AI-DST, which leads to an intractable implementation gap. We analyze this gap and explore its broader implications: suggesting that we may need alternate theoretical conceptualizations of what explainability and trust entail, and/or alternate decision-making arrangements that separate the requirements for trust and deliberation to different parties. (shrink)

Robots that incorporate the function of apologizing have emerged in recent years. This paper examines the moral permissibility of making robots apologize. First, I characterize the nature of apology based on analyses conducted in multiple scholarly domains. Next, I present a prima facie argument that robot apologies are not permissible because they may harm human societies by inducing the misattribution of responsibility. Subsequently, I respond to a possible response to the prima facie objection based on the interpretation that attributing responsibility (...) to a robot is analogous to having an attitude toward fiction. Then, I demonstrate that there are cases of robot apologies where the prima facie objection does not apply, by considering the following two points: (1) apology-related practices found in our human-to-human apologies, and (2) a difference in the degree of harm caused by robot failures and the resulting apologies. Finally, given the current norms governing our apology-related practices, I argue that some instances of making robots apologize are permissible, and I propose conducting critical robotics research questioning the validity of such norms. (shrink)

Compared to human-operated vehicles, autonomous vehicles offer numerous potential benefits. However, public acceptance of AVs remains low. Using 4 studies, including 1 preregistered experiment, the present research examines the role of trust in AV adoption decisions. Using the Trust-Confidence-Cooperation model as a conceptual framework, we evaluate whether perceived integrity of technology—a previously underexplored dimension of trust that refers to perceptions of the moral agency of a given technology—influences AV policy support and adoption intent. We find that perceived technology integrity predicts (...) adoption intent for AVs and that messages that increase perceived integrity of AV technology result in greater AV adoption intent and policy support. This knowledge can be used to guide communication efforts aimed at increasing public trust in AVs, and ultimately enhance integration of AVs into transport systems. (shrink)

Ethicists, policy-makers, and the general public have questioned whether artificial entities such as robots warrant rights or other forms of moral consideration. There is little synthesis of the research on this topic so far. We identify 294 relevant research or discussion items in our literature review of this topic. There is widespread agreement among scholars that some artificial entities could warrant moral consideration in the future, if not also the present. The reasoning varies, such as concern for the effects on (...) artificial entities and concern for the effects on human society. Beyond the conventional consequentialist, deontological, and virtue ethicist ethical frameworks, some scholars encourage “information ethics” and “social-relational” approaches, though there are opportunities for more in-depth ethical research on the nuances of moral consideration of artificial entities. There is limited relevant empirical data collection, primarily in a few psychological studies on current moral and social attitudes of humans towards robots and other artificial entities. This suggests an important gap for psychological, sociological, economic, and organizational research on how artificial entities will be integrated into society and the factors that will determine how the interests of artificial entities are considered. (shrink)

The anticipated social capabilities of robots may allow them to serve in authority roles as part of human-machine teams. To date, it is unclear if, and to what extent, human team members will comply with requests from their robotic teammates, and how such compliance compares to requests from human teammates. This research examined how the human-likeness and physical embodiment of a robot affect compliance to a robot's request to perseverate utilizing a novel task paradigm. Across a set of two studies, (...) participants performed a visual search task while receiving ambiguous performance feedback. Compliance was evaluated when the participant requested to stop the task and the coach urged the participant to keep practicing multiple times. In the first study, the coach was either physically co-located with the participant or located remotely via a live-video. Coach type varied in human-likeness and included either a real human, a Nao robot, or a modified Roomba robot. The second study expanded on the first by including a Baxter robot as a coach and replicated the findings in a different sample population with a strict chain of command culture. Results from both studies showed that participants comply with the requests of a robot for up to 11 min. Compliance is less than to a human and embodiment and human-likeness on had weak effects on compliance. (shrink)

I describe a suite of reinforcement learning environments in which artificial agents learn to value and respond to moral content and contexts. I illustrate the core principles of the framework by characterizing one such environment, or “gridworld,” in which an agent learns to trade-off between monetary profit and fair dealing, as applied in a standard behavioral economic paradigm. I then highlight the core technical and philosophical advantages of the learning approach for modeling moral cognition, and for addressing the so-called value (...) alignment problem in AI. (shrink)

Seminal work by Knobe, Prasada, and Newman (2013) distinguished a set of concepts, which they named “dual‐character concepts.” Unlike traditional concepts, they require two distinct criteria for determining category membership. For example, the prototypical dual‐character concept “artist” has both a concrete dimension of artistic skills, and an abstract dimension of aesthetic sensibility and values. Therefore, someone can be a good artist on the concrete dimension but not truly an artist on the abstract dimension. Does this analysis capture people's understanding of (...) cornerstone social categories, such as gender, around which society and everyday life have traditionally been organized? Gender, too, may be conceived as having not only a concrete dimension but also a distinct dimension of abstract norms and values. As with dual‐character concepts, violations of abstract norms and values may result in someone being judged as not truly a man/woman. Here, we provide the first empirical assessment of applying the dual‐character framework to people's conception of gender. We found that, on some measures that primarily relied on metalinguistic cues, gender concepts did indeed resemble dual‐character concepts. However, on other measures that depicted transgressions of traditional gender norms, neither “man” nor “woman” appeared dual‐character‐like, in that participants did not disqualify people from being truly a man or truly a woman. In a series of follow‐up studies, we examined whether moral norms have come to replace gender role norms for the abstract dimension. Implications for the evolution of concepts and categories are explored. (shrink)

Several technological developments, such as self-service technologies and artificial intelligence, are disrupting the retailing industry by changing consumption and purchase habits and the overall retail experience. Although AI represents extraordinary opportunities for businesses, companies must avoid the dangers and risks associated with the adoption of such systems. Integrating perspectives from emerging research on AI, morality of machines, and norm activation, we examine how individuals morally behave toward AI agents and self-service machines. Across three studies, we demonstrate that consumers’ moral concerns (...) and behaviors differ when interacting with technologies versus humans. We show that moral intention is less likely to emerge for AI checkout and self-checkout machines compared with human checkout. In addition, moral intention decreases as people consider the machine less humanlike. We further document that the decline in morality is caused by less guilt displayed toward new technologies. The non-human nature of the interaction evokes a decreased feeling of guilt and ultimately reduces moral behavior. These findings offer insights into how technological developments influence consumer behaviors and provide guidance for businesses and retailers in understanding moral intentions related to the different types of interactions in a shopping environment. (shrink)

The transfer of tasks with sometimes far-reaching implications to autonomous systems raises a number of ethical questions. In addition to fundamental questions about the moral agency of these systems, behavioral issues arise. We investigate the empirically accessible question of whether the imposition of harm by an agent is systematically judged differently when the agent is artificial and not human. The results of a laboratory experiment suggest that decision-makers can actually avoid punishment more easily by delegating to machines than by delegating (...) to other people. Our results imply that the availability of artificial agents could provide stronger incentives for decision-makers to delegate sensitive decisions. (shrink)

When people interact with social robots, they treat them as real social agents. How people depict robots is fun to consider, but when people are confronted with embodied entities that move and talk – whether humans or robots – they interact with them as authentic social agents with minds, and not as mere representations.