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Biometric technologies are becoming more pervasive in the workplace, augmenting managerial processes such as hiring, monitoring and terminating employees. Until recently, these devices consisted mainly of GPS tools that track location, software that scrutinizes browser activity and keyboard strokes, and heat/motion sensors that monitor workstation presence. Today, however, a new generation of biometric devices has emerged that can sense, read, monitor and evaluate the affective state of a worker. More popularly known by its commercial moniker, Emotional AI, the technology stems from advancements in affective computing. But whereas previous generations of biometric monitoring targeted the exterior physical body of the worker, concurrent with the writings of Foucault and Hardt, we argue that emotion-recognition tools signal a far more invasive disciplinary gaze that exposes and makes vulnerable the inner regions of the worker-self. Our paper explores attitudes towards empathic surveillance by analyzing a survey of 1015 responses of future job-seekers from 48 countries with Bayesian statistics. Our findings reveal affect tools, left unregulated in the workplace, may lead to heightened stress and anxiety among disadvantaged ethnicities, gender and income class. We also discuss a stark cross-cultural discrepancy whereby East Asians, compared to Western subjects, are more likely to profess a trusting attitude toward EAI-enabled automated management. While this emerging technology is driven by neoliberal incentives to optimize the worksite and increase productivity, ultimately, empathic surveillance may create more problems in terms of algorithmic bias, opaque decisionism, and the erosion of employment relations. Thus, this paper nuances and extends emerging literature on emotion-sensing technologies in the workplace, particularly through its highly original cross-cultural study. Supplementary Information The online version contains supplementary material available at 10.1007/s00146-021-01290-1.

This paper reflects on the qualities of living and learning in digital cultures, the design of digital technologies and the philosophical history that has informed that design. It takes as its critical perspective the field of embodied cognition as it has developed over the last three decades, in concert with emerging neurophysiology and neurocognitive research. From this perspective the paper considers cognitive, neurological and physiological effects that are increasingly becoming noticed in user populations, especially young populations. I call this class of conditions ‘sensorimotor debility’, to distinguish it from other psychological, social, cultural and political symptoms associated with computer, internet and social media use.

This paper inquiries into the complex issue of informed consent applying artificial intelligence in medical diagnostic consultations. The aim is to expose the main ethical and legal concerns of the New Health phenomenon, powered by intelligent machines. To achieve this objective, the first part of the paper analyzes ethical aspects of the alleged right to explanation, privacy, and informed consent, applying artificial intelligence in medical diagnostic consultations. This analysis is followed by a legal analysis of the limits and requirements for the explainability of artificial intelligence. Followed by this analysis, recommendations for action are given in the concluding remarks of the paper.

Significant technological advancements over the last two decades have led to enhanced accessibility to computing devices and the Internet. Our society is experiencing an ever-growing integration of the Internet into everyday lives, and this has transformed the way we obtain and exchange information, communicate and interact with one another as well as conduct business. However, the term ‘Internet addiction’ (IA) has emerged from problematic and excessive Internet usage which leads to the development of addictive cyber-behaviours, causing health and social problems. The most commonly used intervention treatments such as motivational interviewing, cognitive-behavioural therapy, and retreat or inpatient care mix a variety of psychotherapy theories to treat such addictive behaviour and try to address underlying psychosocial issues that are often coexistent with IA, but the efficacy of these approaches is not yet proved. The aim of this paper is to address the question of whether it is possible to cure IA with the Internet. After detailing the current state-of-the-art including various IA definitions, risk factors, assessment methods and IA treatments, we outline the main research challenges that need to be solved. Moreover, we propose an Internet-based IA Recovery Framework (IARF) which uses AI to closely observe, visualize and analyse patient’s Internet usage behaviour for possible staged intervention. The proposal to use smart Internet-based systems to control IA can be expected to be controversial. This paper is intended to stimulate further discussion and research in IA recovery through Internet-based frameworks.

A major stumbling block in understanding the full significance of embodiment is the reflexive self-conception characterised by free-floating nature. The paper, in the initial sections, looks into the sensory motor approach to phenomenal consciousness and the approach to the study of vision where the world is treated as an external memory. Subsequently, the paper argues that the difficulty in exploring the sensory motor approach to phenomenal consciousness stems from the free-floating self-conception humans is endowed with. The assumption that experiences are internal can make us closed to the role external factors play in constituting experience. Accordingly, a revision in the self-conception carries the possibility of conceptualising experience in a different manner.

The aim of this paper was to provide a background review to assist experimental, survey and field studies that will start emerging on the effects of robot crime interviewers on children and on forensic investigations. The paper captures topics such as describing how, historically, technology has determined our legal systems, criminal investigations and, of course, children's forensic testimonies. It discusses studies that have already explored the idea of robot crime interviewers in the context of relevant ethical concerns as well as experimental studies on the different ways in which children react in an interview elicited by a human compared with a robot interviewer. The article continues by suggesting research methodological designs that could benefit studies exploring robot interviews with children such as a robot exposure phase prior to the main data collection, the robot's "personality" and the instructions given to children for semi-autonomous interviewers. This is based on the available literature on human---robot interactions. There is an attempt here to provide a literature review and methodological suggestions to form future studies on robot crime interviewers.

Marketing communication has recently become increasingly interactive due to the widespread use of social media and requires wider participation by consumers. One method that facilitates this interaction is Shikake, which is defined as a trigger for behavior change. The aim of this paper is to demonstrate the effectiveness of Shikake with respect to enhancing customer engagement behavior, which is defined as customers' behavioral manifestations that have a brand or firm focus, beyond purchase, resulting from motivational drivers. This paper introduces various approaches that can be used to trigger customer engagement behavior, such as brand relationships, behavioral economics, and human---computer interaction, emphasizes the power of design framing and triggers, and attempts to classify Shikake in the field of marketing according to participants' motivation and consciousness. Finally, the paper attempts to reveal Shikake's key success factor in the field of marketing and discusses future research opportunities.

A growing body of research can be found in which roboticists are designing for reciprocity as a key construct for successful human–robot interaction (HRI). Given the centrality of reciprocity as a component for our moral lives (for moral development and maintaining the just society), this paper confronts the possibility of what things would look like if the benchmark to achieve perceived reciprocity were accomplished. Through an analysis of the value of reciprocity from the care ethics tradition the richness of reciprocity as an inherent value is revealed: on the micro-level, as mutual care for immediate care givers, and on the macro-level, as foundational for a just society. Taking this understanding of reciprocity into consideration, it becomes clear that HRI cannot achieve this bidirectional value of reciprocity; a robot must deceive users into believing it is capable of reciprocating to humans or is deserving of reciprocation from humans. Moreover, on the macro-level, designing social robots for reciprocity threatens the ability and willingness to reciprocate to human care workers across society. Because of these concerns, I suggest re-thinking the goals of reciprocity in social robotics. Designing for reciprocity in social robotics should be dedicated to the design of robots to enhance the ability to mutually care for those that provide us with care, as opposed to designing for reciprocity between human and robot.

We have examined the attitude and moral perception of 228 college students (63 Japanese and 165 non-Japanese) towards artificial intelligence (AI) in an international university in Japan. The students were asked to select a single most significant ethical issue associated with AI in the future from a list of nine ethical issues suggested by the World Economic Forum, and to explain why they believed that their chosen issues were most important. The majority of students (n = 149, 65%) chose unemployment as the major ethical issue related to AI. The second largest group of students (n = 29, 13%) were concerned with ethical issues related to emotional AI, including the impact of AI on human behavior and emotion. The paper discusses the results in detail and concludes that, while policymakers must consider how to ameliorate the impact of AI on employment, AI engineers need to consider the emotional aspects of AI in research and development, as well.

In this paper, I develop a view about machine autonomy grounded in the theoretical frameworks of 4E cognition and PF Strawson’s reactive attitudes. I begin with critical discussion of White (this issue), and conclude that his view is strongly committed to functionalism as it has developed in mainstream analytic philosophy since the 1950s. After suggesting that there is good reason to resist this view by appeal to developments in 4E cognition, I propose an alternative view of machine autonomy. Namely, machines count as autonomous when we members of the moral community adopt reactive attitudes in response to their actions. I distinguish this view from White’s and suggest assets and liabilities of this approach.

The increasing use of geographic information systems (GIS) in everyday life is profoundly shaping how humans navigate and interact with their surroundings. Behavioural and ethnographic experimental research indicates that increased usage of GPS devices is having a significant impact on human neurocognitive systems, especially memory and perception (Gramann et al. 2017). Despite this, there has only been a limited investigation of the implications of the spread of GIS technologies. In this paper, we explore how habitual reliance on GPS technology undermines autonomous decision-making through “nudging” (Sunstein and Thaler 2008)—that is, the alteration of psychological behaviour without the explicit forbidding of choice. In particular, we make a novel distinction between what we refer to as “suggestive nudging”—the suggesting of certain routes to take to get to a destination—and “disclosure nudging”—the normalisation of constant tracking and disclosing of our locations to government and corporate actors. We shall argue that although suggestive and disclosure nudging are in principle separate, that in practice they are intertwined in the design of modern GPS devices. Additionally, since human spatial cognition is highly plastic and susceptible to being sculpted by cultural practices (Hutchins 1995; Levinson 2003), this exacerbates the negative implications of the ‘in practice’ link of suggestive and disclosure nudging by making the latter harder to avoid and opt-out of. We argue that this state of affairs necessitates re-designing GPS devices.

Advances in artificial intelligence, as well as its increased presence in everyday life, have brought the emergence of many new phenomena, including an intriguing appearance of what seems to be a variant of body dysmorphic disorder, coined “Snapchat dysmorphia”. Body dysmorphic disorder is a DSM-5 psychiatric disorder defined as a preoccupation with one or more perceived defects or flaws in physical appearance that are not observable or appear slight to others. Snapchat dysmorphia is fueled by automated selfie filters that reflect unrealistic sociocultural standard. In this paper, we discuss how body dysmorphic disorder and related body image distortions could arise, using the conceptual resources provided by the active inference framework. We suggest that these disorders involve dysfunctional self-modelling which entails maladaptive internalization of sociocultural preferences during adolescent identity formation. Identity formation is hereby described as cycles of interpersonal active inference that arbitrate between identity exploration and commitment. We propose that impaired self-modelling is unable to reduce interpersonal uncertainty during identity exploration, which, over time, degenerates into uncontrollable epistemic habits that isolate the body image from corrective sensory evidence. In light of these insights, we subsequently explore some of the consequences of image-centered social media platforms on the identity formation process. We conclude that heightened interpersonal uncertainty in this novel context could precipitate the onset of body dysmorphic disorder and related body image distortions, particularly when selfie filters are involved.

While philosophers have been debating for decades on whether different entities—including severely disabled human beings, embryos, animals, objects of nature, and even works of art—can legitimately be considered as having moral status, this question has gained a new dimension in the wake of artificial intelligence (AI). One of the more imminent concerns in the context of AI is that of the moral rights and status of social robots, such as robotic caregivers and artificial companions, that are built to interact with human beings. In recent years, some approaches to moral consideration have been proposed that would include social robots as proper objects of moral concern, even though it seems unlikely that these machines are conscious beings. In the present paper, I argue against these approaches by advocating the “consciousness criterion,” which proposes phenomenal consciousness as a necessary condition for accrediting moral status. First, I explain why it is generally supposed that consciousness underlies the morally relevant properties (such as sentience) and then, I respond to some of the common objections against this view. Then, I examine three inclusive alternative approaches to moral consideration that could accommodate social robots and point out why they are ultimately implausible. Finally, I conclude that social robots should not be regarded as proper objects of moral concern unless and until they become capable of having conscious experience. While that does not entail that they should be excluded from our moral reasoning and decision-making altogether, it does suggest that humans do not owe direct moral duties to them.

The goal of this paper is to describe the mechanism of the public perception of risk of artificial intelligence. For that we apply the social amplification of risk framework to the public perception of artificial intelligence using data collected from Twitter from 2007 to 2018. We analyzed when and how there appeared a significant representation of the association between risk and artificial intelligence in the public awareness of artificial intelligence. A significant finding is that the image of the risk of AI is mostly associated with existential risks that became popular after the fourth quarter of 2014. The source of that was the public positioning of experts who happen to be the real movers of the risk perception of AI so far instead of actual disasters. We analyze here how this kind of risk was amplified, its secondary effects, what are the varieties of risk unrelated to existential risk, and what is the dynamics of the experts in addressing their concerns to the audience of lay people.

Children continue to be overlooked as a topic of concern in discussions around the ethical use of people’s data and information. Where children are the subject of such discussions, the focus is often primarily on privacy concerns and consent relating to the use of their data. This paper highlights the unique challenges children face when it comes to online interferences with their decision-making, primarily due to their vulnerability, impressionability, the increased likelihood of disclosing personal information online, and their developmental capacities. These traits allow for practices such as hypernudging to be executed on them more accurately and with more serious consequences, specifically by potentially undermining their autonomy. We argue that children are autonomous agents in the making and thus require additional special protections to ensure that the development of their autonomy is safeguarded. This means that measures should be taken to prohibit most forms of hypernudging children and thus ensure that they are protected from this powerful technique of digital manipulation.

Causal reasoning is an aspect of learning, reasoning, and decision-making that involves the cognitive ability to discover relationships between causal relata, learn and understand these causal relationships, and make use of this causal knowledge in prediction, explanation, decision-making, and reasoning in terms of counterfactuals. Can we fully automate causal reasoning? One might feel inclined, on the basis of certain groundbreaking advances in causal epistemology, to reply in the affirmative. The aim of this paper is to demonstrate that one still has good skeptical grounds for resisting any conclusions in favour of the automation of causal reasoning. If by causal reasoning is meant the entirety of the process through which we discover causal relationships and make use of this knowledge in prediction, explanation, decision-making, and reasoning in terms of counterfactuals, then one relies besides on tacit knowledge, as might be constituted by or derived from the epistemic faculty virtues and abilities of the causal reasoner, the value systems and character traits of the causal reasoner, the implicit knowledge base available to the causal reasoner, and the habits that sustain our causal reasoning practices. While certain aspects of causal reasoning may be axiomatized and formalized and algorithms may be implemented to approximate causal reasoning, one has to remain skeptical about whether causal reasoning may be fully automated. This demonstration will involve an engagement with Meno’s Paradox. Nanyang Technological University Published version This research is part of a Medical AI project that is generously supported by the intramural Nanyang Technological University ACE Grant (Award Number: NTU–ACE2018-05).

Can an Artificial Intelligence make distinctions among major works of politics, philosophy, and fiction without human assistance? In this paper, latent semantic analysis (LSA) is used to find patterns in a relatively small sample of notable works archived by Project Gutenberg. It is shown that an LSA-equipped AI can distinguish quite sharply between fiction and non-fiction works, and can detect some differences between political philosophy and history, and between conventional fiction and fantasy/science fiction. It is conjectured that this capability is a step in the direction of “M-comprehension” (or “machine comprehension”) by AIs.

In this paper, we present a formal interpretive account of Jean Piaget’s theory of the morality that regulates social exchanges, which we call interactional morality. First, we place Piaget’s conception in the context of his epistemological and sociological works. Then, we review the core of that conception: the two types of interactional moralities (autonomous and heteronomous) that Piaget identified to be usual in social exchanges, and the role that the notion of respect-for-the-other plays in their definition. Next, we analyze the main features of social exchanges that are subject to each of those two types of interactional moralities. Following, we formalize Piaget’s account of how the two types of interactional moralities can be put to regulate social exchanges in which values, norms, beliefs, and goals are exchanged (besides objects and services), so that interactional commitments can be established among the participants. Then, we sketch a moral reasoning system able to support formal reasonings about interactional moralities. Finally, we illustrate the usefulness of the overall formal model of interactional moralities that resulted from our study by applying it to the explication of some of the conclusions achieved by Piaget in his moral studies about children games.

This paper discusses means for promoting artificial intelligence (AI) that is designed to be safe and beneficial for society (or simply “beneficial AI”). The promotion of beneficial AI is a social challenge because it seeks to motivate AI developers to choose beneficial AI designs. Currently, the AI field is focused mainly on building AIs that are more capable, with little regard to social impacts. Two types of measures are available for encouraging the AI field to shift more towards building beneficial AI. Extrinsic measures impose constraints or incentives on AI researchers to induce them to pursue beneficial AI even if they do not want to. Intrinsic measures encourage AI researchers to want to pursue beneficial AI. Prior research focuses on extrinsic measures, but intrinsic measures are at least as important. Indeed, intrinsic factors can determine the success of extrinsic measures. Efforts to promote beneficial AI must consider intrinsic factors by studying the social psychology of AI research communities.

The present paper aims to review the value of Action Research (AR) in the evolution of sustainable mHealth. On the one hand, mHealth is a medically and economically massively expanding domain. On the other hand, the mHealth development suffers from a serious lack of sustainability, which has become particularly evident through the concept of “pilotitis.” The proposed methodological remedy shows a high congruence to the principle of AR. A quantitative and qualitative literature research is performed. Each result from the qualitative literature research is analyzed with regard to aim, main focuses of AR methodology, study results and AR contribution to mHealth development. The principles of AR with regard to mHealth development are described, showing a strong connection between corresponding methodology and effects in health care. We analyze the quantitative contribution of AR to health care in general and show the typical phases of AR healthcare implementation. Furthermore, a quantitative literature research reveals that AR contributes to 6 % of mHealth publications. Our qualitative literature research discovers 27 studies dealing with AR contributions (54 % direct, 46 % methodological) to mHealth. Main subjects of the direct contributions are Health Information Systems (38 %), Surgery (23 %), Conservative/internal medicine (15 %), Self-help (15 %) and Medical Education (8 %). In summary, our review shows that AR contributes qualitatively and quantitatively to the mHealth development and that AR has a special potential to generate sustainable mHealth solutions.

In this paper I describe a future in which persons in advanced old age are cared for entirely by robots and suggest that this would be a dystopia, which we would be well advised to avoid if we can. Paying attention to the objective elements of welfare rather than to people's happiness reveals the central importance of respect and recognition, which robots cannot provide, to the practice of aged care. A realistic appreciation of the current economics of the aged care sector suggests that the introduction of robots into an aged care setting will most likely threaten rather than enhance these goods. I argue that, as a result, robotics for aged care is likely to transform aged care in accordance with a trajectory that leads towards this dystopian future even when this is not the intention of the engineers involved. While an argument can be made for the use of robots in aged care where the people being cared for have chosen to allow robots in this role, I suggest that overemphasising this possibility risks rendering it a self-fulfilling prophecy, depriving those being cared for of valuable social recognition, and failing to provide respect for older persons by allowing the options available to them to be shaped by the design choices of others.

This paper reports the results of a cross-cultural study on facial regions as cues to recognize facial expressions of virtual agents. The experiment was conducted between Japan and Hungary using 30 facial expressions of cartoonish faces designed by Hungarians. The results suggest the following: (1) cultural differences exist when using facial regions as cues to recognize cartoonish facial expressions between Hungary and Japan. Japanese weighed facial cues more heavily in the eye region than Hungarians, who weighed facial cues more heavily in the mouth region than Japanese. (2) The mouth region is more effective for conveying the emotions of facial expressions than the eye region, regardless of country. Our findings can be used not only to derive design guidelines for virtual agent facial expressions when aiming at users of a single culture, but as adaptation strategies in applications with users from various cultures.