Intelligent personal assistants own anthropomorphic features which enable users’ perception of anthropomorphism. Adopting the perspective of mind-based anthropomorphism, the purpose of this paper is to investigate how mind-based anthropomorphism influences users’ exploratory usage of IPAs. Based on the notion that anthropomorphism can satisfy people’s sociality and effectance motivation, we hypothesize that mind-based anthropomorphism can enhance people’s social connection with IPAs and IPA self-efficacy, which can in turn influence their exploratory usage of IPAs. Questionnaires were developed and distributed (...) to users who had experience in smart speaker-based IPAs on Wenjuanxing and 551 valid questionnaires were collected to test the research model. The results revealed that cognitive and affective anthropomorphism exerted common and differential impacts on IPA self-efficacy and social connection. Cognitive anthropomorphism versus affective anthropomorphism had stronger influences on IPA self-efficacy, while affective anthropomorphism had stronger impacts on social connection. Both IPA self-efficacy and social connection enhanced users’ intentions to explore IPAs. This study enriches previous studies on IPA adoption or post-adoption by investigating exploratory usage which captures how users are deeply engaged with IPAs. (shrink)

The emergence of personal assistants in the form of smart speakers has begun to significantly alter people’s everyday experiences with technology. The rate at which household Intelligent Personal Assistants such as Amazon’s Echo and Google Home emerged in household spaces has been rapid. They have begun to move human–computer interaction from text-based to voice-activated input, offering a multiplicity of features through speech. The supporting infrastructure connects with artificial intelligence and the internet of things, allowing digital (...) interfaces with domestic appliances, lighting systems, thermostats, media devices and more. Yet this also constitutes a significant new production of situated and sensitive data. This study focuses on how users negotiate and make choices about household Intelligent Personal Assistant use in connection with their data. This study is based on empirical research in Europe with early adopters in Germany and potential users in the Netherlands. This examination of users’ early stage technology acceptance considerations highlights particular practices and choices of users to either preserve their privacy or determine what is acceptable use for their data. Drawing on a simplified version of Unified Theory of Acceptance and Use of Technology 2, a quantitative model for technology acceptance, we demonstrate how acceptance of a household Intelligent Personal Assistants does not imply access to all household data, how users see usefulness in relation to a proliferation of devices, and note the recognition by users regarding the efforts needed for full use and acceptance. The study highlights the complexity of data production at a household level and how these devices produce myopic views of users for platforms. (shrink)

Mark Coeckelbergh (Int J Soc Robot 1:217–221, 2009) argues that robot ethics should investigate what interaction with robots can do to humans rather than focusing on the robot’s moral status. We should ask what robots do to our sociality and whether human–robot interaction can contribute to the human good and human flourishing. This paper extends Coeckelbergh’s call and investigate what it means to live with disembodied AI-powered agents. We address the following question: Can the human–AI interaction contribute to our moral (...) development? We present an empirically informed philosophical analysis of how the AI personal assistant Siri changes its users’ way of life, based on the responses obtained from 20 semi-directive individual interviews with Siri users. We identify changes in the users’ social interaction associated with the adoption of Siri. These changes include: (1) the indirect effect of reducing opportunities of human interaction, (2) the second-order effect of diminished expectations toward each other in a community, and (3) the acquired preference to obtain hassle-free interaction with Siri over human interaction. We examine them in relation to concerns that are voiced in the current debates over the rise of AI, namely the suspicion that humans could become overly reliant on AI (Danaher 2019) and the worry that social AI could impede on moral development (Fröding and Peterson, Ethics Inf Technol 23:207–214, 2012; Li, Ethics Inf Technol 23:543–550, 2021). We analyze the ethical costs that come from these changes in light of virtue ethics and address potential objections along the way. We end by offering directions for thinking about how to live with AI personal assistant while preserving favorable conditions for moral development. (shrink)

Traditional medical practices and relationships are changing given the widespread adoption of AI-driven technologies across the various domains of health and healthcare. In many cases, these new technologies are not specific to the field of healthcare. Still, they are existent, ubiquitous, and commercially available systems upskilled to integrate these novel care practices. Given the widespread adoption, coupled with the dramatic changes in practices, new ethical and social issues emerge due to how these systems nudge users into making decisions and changing (...) behaviours. This article discusses how these AI-driven systems pose particular ethical challenges with regards to nudging. To confront these issues, the value sensitive design approach is adopted as a principled methodology that designers can adopt to design these systems to avoid harming and contribute to the social good. The AI for Social Good factors are adopted as the norms constraining maleficence. In contrast, higher-order values specific to AI, such as those from the EU High-Level Expert Group on AI and the United Nations Sustainable Development Goals, are adopted as the values to be promoted as much as possible in design. The use case of Amazon Alexa's Healthcare Skills is used to illustrate this design approach. It provides an exemplar of how designers and engineers can begin to orientate their design programs of these technologies towards the social good. (shrink)

The rapid advancement of artificial (computer) intelligence systems (CIS) has generated a means whereby assistive bionic prosthetics can become both more effective and practical for the patients who rely upon the use of such machines in their daily lives. However, de lege lata remains relatively unspoken as to the legal status of patients whose devices contain self-learning CIS that can interface directly with the peripheral nervous system. As a means to reconcile for this lack of legal foresight, this article approaches (...) the topic of CIS-nervous system interaction and the impacts it may have on the legal definition of “persons” under the law. While other literature of this nature centres upon notions of transhumanism or self-enhancement, the approach herein approached is designed to focus solely upon the legal nature of independent CIS actions when operating alongside human subjects. To this end, it is hoped that further discussion on the topic can be garnered outside of transhumanist discourse to expedite legal consideration for how these emerging relationships ought to be received by law-generating bodies internationally. (shrink)

Artificial Intelligence is supposed to perform tasks autonomously, make competent decisions, and interact socially with people. From a psychological perspective, AI can thus be expected to impact users’ three Basic Psychological Needs, namely autonomy, competence, and relatedness to others. While research highlights the fulfillment of these needs as central to human motivation and well-being, their role in the acceptance of AI applications has hitherto received little consideration. Addressing this research gap, our study examined the influence of BPN Satisfaction on Intention (...) to Use an AI assistant for personal banking. In a 2×2 factorial online experiment, 282 participants watched a video of an AI finance coach with a female or male synthetic voice that exhibited either high or low agency. In combination, these factors resulted either in AI assistants conforming to traditional gender stereotypes or in non-conforming conditions. Although the experimental manipulations had no significant influence on participants’ relatedness and competence satisfaction, a strong effect on autonomy satisfaction was found. As further analyses revealed, this effect was attributable only to male participants, who felt their autonomy need significantly more satisfied by the low-agency female assistant, consistent with stereotypical images of women, than by the high-agency female assistant. A significant indirect effects model showed that the greater autonomy satisfaction that men, unlike women, experienced from the low-agency female assistant led to higher ITU. The findings are discussed in terms of their practical relevance and the risk of reproducing traditional gender stereotypes through technology design. (shrink)

There has recently been a surge of development in augmented reality (AR) technologies that has led to an ecosystem of hardware and software for AR, including tools for artists and designers to accelerate the design of AR content and experiences without requiring complex programming. AR is viewed as a key “disruptive technology” and future display technologies (such as digital eyewear) will provide seamless continuity between reality and the digitally augmented. This article will argue that the technologization of human perception and (...) experience of reality, coupled with the development of artificial intelligence (AI)–based natural language assistants, may lead to a secular re‐enchantment of the world, in the sense outlined by Charles Taylor, where human existence is shaped through AR inhabited by advanced personal and social AI agents in the form of digital avatars and daemons, and that enchantment has been persistent throughout the formation of modernity and is being rekindled by the integration of AI in the plane of AR. (shrink)

With the emergence of big data, cloud computing, and other technologies, artificial intelligence technology has set off a new wave in the field of education. The application of AI technology to deep learning in university teachers' teaching and students' learning processes is an innovative way to promote the quality of teaching and learning. This study proposed the deep learning-based assessment to measure whether students experienced an improvement in terms of their mastery of knowledge, development of abilities, and emotional experiences. It (...) also used comparative analysis of pre-tests and post-tests through online questionnaires to test the results. The impact of technology on teachers' teaching and students' learning processes, identified the problems in the teaching and learning processes in the context of the application of AI technology, and proposed strategies for reforming and optimizing teaching and learning. It recommends the application of software and platforms, such as Waston and Knewton, under the orientation of AI technology to improve efficiency in teaching and learning, optimize course design, and engage students in deep learning. The contribution of this research is that the teaching and learning processes will be enhanced by the use of intelligent and efficient teaching models on the teachers' side and personalized and in-depth learning on the students' side. On the one hand, the findings are helpful for teachers to better grasp the actual conditions of in-class teaching in real time, carry out intelligent lesson preparations, enrich teaching methods, improve teaching efficiency, and achieve personalized and precision teaching. On the other hand, it also provides a space of intelligent support for students with different traits in terms of learning and effectively improves students' innovation ability, ultimately achieving the purpose of “artificial intelligence + education.”. (shrink)

Digitalisation and emerging technologies affect our lives and are increasingly present in a growing number of fields. Ethical implications of the digitalisation process have therefore long been discussed by the scholars. The rapid development of artificial intelligence has taken the legal and ethical discussion to another level. There is no doubt that AI can have a positive impact on the society. The focus here, however, is on its more negative impact. This article will specifically consider how the law and ethics (...) in their interaction can be applied in a situation where a disabled person needs some kind of assistive technology to participate in the society as an equal member. This article intends to investigate whether the EU Guidelines for Trustworthy AI, as a milestone of ethics concerning technology, has the power to change the current practice of how social and economic rights are applied. The main focus of the article is the ethical requirements ‘Human agency and oversight’ and, more specifically, fundamental rights. (shrink)

Conversational artificial agents and artificially intelligent voice assistants are becoming increasingly popular. Digital virtual assistants such as Siri, or conversational devices such as Amazon Echo or Google Home are permeating everyday life, and are designed to be more and more humanlike in their speech. This study investigates the effect this can have on one’s conformity with an AI assistant. In the 1950s, Solomon Asch’s already demonstrated the power and danger of conformity amongst people. In these classical experiments (...) test persons were asked to answer relatively simple questions, whilst others pretending to be participants tried to convince the test person to give wrong answers. These studies were later replicated with embodied robots, but these physical robots are still rare. In light of our increasing reliance on AI assistants, this study investigates to what extent an individual will conform to a disembodied virtual assistant. We also investigate if there is a difference between a group that interacts with an assistant that communicates through text, one that has a robotic voice and one that has a humanlike voice. The assistant attempts to subtly influence participants’ final responses in a general knowledge quiz, and we measure how often participants change their answer after having been given advice. Results show that participants conformed significantly more often to the assistant with a human voice than the one that communicated through text. (shrink)

Can Artificial Intelligence be more effective than human instruction for the moral enhancement of people? The author argues that it only would be if the use of this technology were aimed at increasing the individual's capacity to reflectively decide for themselves, rather than at directly influencing behaviour. To support this, it is shown how a disregard for personal autonomy, in particular, invalidates the main proposals for applying new technologies, both biomedical and AI-based, to moral enhancement. As an alternative to (...) these proposals, this article proposes a virtual assistant that, through dialogue, neutrality and virtual reality technologies, can teach users to make better moral decisions on their own. The author concludes that, as long as certain precautions are taken in its design, such an assistant could do this better than a human instructor adopting the same educational methodology. (shrink)

Resumen: El presente trabajo analiza si los Sistemas de apoyo a la decisión (DSSs) y otros asistentes para su uso, como las Reflection machines o los Personal Assistants that Learn (PAL), contribuyen de hecho a una mejora cognitiva, como habitualmente se tiende a asumir. Es decir, se examina si su potencial para expandir e impulsar la acción de las facultades cognoscitivas se ve efectivamente actualizado y, en consecuencia, si sirven para reafirmar el sentido capacitante de la IA y (...) la extensión de la agencia del sujeto a través de ella. Para ello, se pone de manifiesto que el diseño y aplicación de estos sistemas están mediados por una comprensión del conocimiento que actúa a modo de marco que limita sus posibilidades de mejorar las capacidades cognoscitivas humanas. Se analizan las condiciones en que la mejora cognitiva es posible a través del uso de estos sistemas, que remiten a una aproximación integradora que no tiene en cuenta solo el factor tecnológico, sino que repara en cómo, en su uso, intervienen factores gnoseológicos, así como psicológicos y sociológicos, que median en la capacidad efectiva de estos sistemas de ampliar las facultades de conocimiento, y de los que las tecnologías se sirven para ejercer su influencia. Abstract: The present article questions whether Decision Support Systems (DSSs) and other assistants for their use, such as Reflection machines or Personal Assistants that Learn (PAL), do in fact contribute to cognitive enhancement, as it is usually taken for granted. In other words, it is analysed whether their potential to effectively expand or augment cognitive capacities is actualised and, therefore, if the capabilities and the agency of the person appear in fact extended through artificial intelligence. For that purpose, it is highlighted that the design and implementation of AI systems are dependent on a certain understanding of human knowledge that acts as a framework that limits their actual capacity to enhance the cognitive faculties of the mind. The conditions under which this cognitive enhancement is possible through these systems are analysed and require an integrative approach that not only takes technology into account but realises that, in its use, gnoseological, as well as psychological and sociological factors are involved and mediate in the actual capacity of these systems to extend cognitive functions. These factors are also crucial for these technologies to exert their influence. (shrink)

Ambient assisted living technologies can provide assistance and support to persons with dementia. They might allow them the possibility of living at home for longer whilst maintaining their comfort and security as well as offering a way towards reducing the huge economic and personal costs forecast as the incidence of dementia increases worldwide over coming decades. However, the development, introduction and use of AAL technologies also trigger serious ethical issues. This paper is a systematic literature review of the on-going (...) scholarly debate about these issues. More specifically, we look at the ethical issues involved in research and development, clinical experimentation, and clinical application of AAL technologies for people with dementia and related stakeholders. In the discussion we focus on: the value of the goals of AAL technologies, the special vulnerability of persons with dementia in their private homes, the complex question of informed consent for the usage of AAL technologies. (shrink)

Intelligent Guided Learning System is a computer system that uses computers to imitate the experience and methods of teaching experts to assist in teaching; ITS provides learners with personalized learning resources and adaptive teaching methods, thus reducing students’ dependence on teachers and realizing independent learning. After years of research and development, and with the help of artificial intelligence technology, ITS has basically formed a stable structure and unified implementation specifications and has given birth to many excellent products in disciplines (...) such as basic computer, language, medicine, and mathematics. Based on the above background, this paper takes the system structure of universal ITS as the basis, combines the characteristics of music sight-singing subject in teaching contents and teaching methods, researches the intelligent guidance system model of music sight-singing, and completes the design of the overall system architecture. The specific strategies and implementation methods of the teaching methods, resource recommendation, and ability assessment components of the teaching model are studied. The research includes the definition of the difficulty characteristics of the score, the design of the score recommendation algorithm, the design of the sight-singing scoring algorithm, and the experimental analysis of each algorithm. It is proposed that the difficulty feature-based score recommendation algorithm is the core component of resource recommendation in the teacher model, and the sight-singing scoring algorithm is the basis for ability assessment and learner model update. (shrink)

Voice-assistants are becoming increasingly popular and can be deployed to offers a low-cost tool that can support and potentially reduce falls, injuries, and accidents faced by older people within the age of 65 and older. But, irrespective of the mobility and walkability challenges faced by the aging population, studies that employed Artificial Intelligence (AI)-based voice-assistants to reduce risks faced by older people when they use public transportation and walk in built environment are scarce. This is because the development (...) of AI-based voice-assistants suitable for the mobility domain presents several techno–social challenges. Accordingly, this study aims to identify _user-centered_ service design and functional requirements, techno–social factors, and further design an architectural model for an AI-based voice-assistants that provide personalized recommendation to reduce falls, injuries, and accidents faced by older people. Accordingly, a scoping review of the literature grounded on secondary data from 59 studies was conducted and descriptive analysis of the literature and content-related analysis of the literature was carried out. Findings from this study presents the perceived techno-socio factors that may influences older people use of AI-based voice-assistants. More importantly, this study presents user-centred service design and functional requirements needed to be considered in developing voice-assistants suitable for older people. Implications from this study provides AI techniques for implementing voice-assistants that provide safe mobility, walkability, and wayfinding for older people in urban areas. (shrink)

Rapid advancements in artificial intelligence and machine learning (AI/ML) in healthcare raise pressing questions about how much users should trust AI/ML systems, particularly for high stakes clinical decision-making. Ensuring that user trust is properly calibrated to a tool’s computational capacities and limitations has both practical and ethical implications, given that overtrust or undertrust can influence over-reliance or under-reliance on algorithmic tools, with significant implications for patient safety and health outcomes. It is, thus, important to better understand how variability in trust (...) criteria across stakeholders, settings, tools and use cases may influence approaches to using AI/ML tools in real settings. As part of a 5-year, multi-institutional Agency for Health Care Research and Quality-funded study, we identify trust criteria for a survival prediction algorithm intended to support clinical decision-making for left ventricular assist device therapy, using semistructured interviews (n=40) with patients and physicians, analysed via thematic analysis. Findings suggest that physicians and patients share similar empirical considerations for trust, which were primarilyepistemicin nature, focused on accuracy and validity of AI/ML estimates. Trust evaluations considered the nature, integrity and relevance of training data rather than the computational nature of algorithms themselves, suggesting a need to distinguish ‘source’ from ‘functional’ explainability. To a lesser extent, trust criteria were also relational (endorsement from others) and sometimes based on personal beliefs and experience. We discuss implications for promoting appropriate and responsible trust calibration for clinical decision-making use AI/ML. (shrink)

Many of our daily activities are now made more convenient and efficient by virtual assistants, and the day when they can be designed to instruct us in certain skills, such as those needed to make moral judgements, is not far off. In this paper we ask to what extent it would be ethically acceptable for these so-called virtual assistants for moral enhancement to use subtle strategies, known as “nudges”, to influence our decisions. To achieve our goal, we will (...) first characterise nudges in their standard use and discuss the debate they have generated around their possible manipulative character, establishing three conditions of manipulation. Secondly, we ask whether nudges can occur in moral virtual assistants that are not manipulative. After critically analysing some proposed virtual assistants, we argue in favour of one of them, given that by pursuing an open and neutral moral enhancement, it promotes and respects the autonomy of the person as much as possible. Thirdly, we analyse how nudges could enhance the functioning of such an assistant, and evaluate them in terms of their degree of threat to the subject’s autonomy and their level of transparency. Finally, we consider the possibility of using motivational nudges, which not only help us in the formation of moral judgements but also in our moral behaviour. (shrink)

The purpose of this study was to measure professional and personal values among nurses, and to identify the factors affecting these values. The participants were 323 Israeli nurses, who were asked about 36 personal values and 20 professional values. The three fundamental professional nursing values of human dignity, equality among patients, and prevention of suffering, were rated first. The top 10 rated values all concerned nurses' responsibility towards patients. Altruism and confidentiality were not highly rated, and health promotion (...) and nursing research were rated among the last three professional values. For personal (instrumental) values, honesty, responsibility and intelligence were rated first, while ambition and imagination were rated 14th and 16th respectively out of 18. Significant differences (P < 0.05) were found among some personal and professional values rated as functions of culture, education, professional seniority, position and field of expertise. The results may assist in understanding the motives of nurses with different characteristics and help to promote their work according to professional ethical values. (shrink)

Personal AI assistants are now nearly ubiquitous. Every leading smartphone operating system comes with a personal AI assistant that promises to help you with basic cognitive tasks: searching, planning, messaging, scheduling and so on. Usage of such devices is effectively a form of algorithmic outsourcing: getting a smart algorithm to do something on your behalf. Many have expressed concerns about this algorithmic outsourcing. They claim that it is dehumanising, leads to cognitive degeneration, and robs us of our (...) freedom and autonomy. Some people have a more subtle view, arguing that it is problematic in those cases where its use may degrade important interpersonal virtues. In this article, I assess these objections to the use of AI assistants. I will argue that the ethics of their use is complex. There are no quick fixes or knockdown objections to the practice, but there are some legitimate concerns. By carefully analysing and evaluating the objections that have been lodged to date, we can begin to articulate an ethics of personal AI use that navigates those concerns. In the process, we can locate some paradoxes in our thinking about outsourcing and technological dependence, and we can think more clearly about what it means to live a good life in the age of smart machines. (shrink)

Set aside fanciful doomsday speculations about AI. Even lower-level AIs, while otherwise friendly and providing us a universal basic income, would be able to do all our jobs. Also, we would over-rely upon AI assistants even in our personal lives. Thus, John Danaher argues that a human crisis of moral passivity would result However, I argue firstly that if AIs are posited to lack the potential to become unfriendly, they may not be intelligent enough to replace us (...) in all our jobs. If instead they are intelligent enough to replace us, the risk they become unfriendly increases, given that they would not need us and humans would just compete for valuable resources. Their hostility will not promote our moral passivity. Secondly, the use of AI assistants in our personal lives will become a problem only if we rely on them for almost all our decision-making and motivation. But such a (maximally) pervasive level of dependence raises the question of whether humans would accept it, and consequently whether the crisis of passivity will arise. (shrink)

ABSTRACT I argue that this examination and appreciation for the shift to abductive reasoning should be extended to the intersection of neuroscience and novel brain-computer interfaces too. This paper highlights the implications of applying abductive reasoning to personalized implantable neurotechnologies. Then, it explores whether abductive reasoning is sufficient to justify insurance coverage for devices absent widespread clinical trials, which are better applied to one-size-fits-all treatments. INTRODUCTION In contrast to the classic model of randomized-control trials, often with a large number of (...) subjects enrolled, precision medicine attempts to optimize therapeutic outcomes by focusing on the individual.[i] A recent publication highlights the strengths and weakness of both traditional evidence-based medicine and precision medicine.[ii] Plus, it outlines a tension in the shift from evidence-based medicine’s inductive reasoning style (the collection of data to postulate general theories) to precision medicine’s abductive reasoning style (the generation of an idea from the limited data available).[iii] The paper’s main example is the application of precision medicine for the treatment of cancer.[iv] I argue that this examination and appreciation for the shift to abductive reasoning should be extended to the intersection of neuroscience and novel brain-computer interfaces too. As the name suggests, brain-computer interfaces are a significant advancement in neurotechnology that directly connects someone’s brain to external or implanted devices.[v] Among the various kinds of brain-computer interfaces, adaptive deep brain stimulation devices require numerous personalized adjustments to their settings during the implantation and computation stages in order to provide adequate relief to patients with treatment-resistant disorders. What makes these devices unique is how adaptive deep brain stimulation integrates a sensory component to initiate the stimulation. While not commonly at the level of sophistication as self-supervising or generative large language models,[vi] they currently allow for a semi-autonomous form of neuromodulation. This paper highlights the implications of applying abductive reasoning to personalized implantable neurotechnologies. Then, it explores whether abductive reasoning is sufficient to justify insurance coverage for devices absent widespread clinical trials, which are better applied to one-size-fits-all treatments.[vii] ANALYSIS I. The State of Precision Medicine in Oncology and the Epistemological Shift While a thorough overview of precision medicine for the treatment of cancer is beyond the scope of this article, its practice can be roughly summarized as identifying clinically significant characteristics a patient possesses (e.g., genetic traits) to land on a specialized treatment option that, theoretically, should benefit the patient the most.[viii] However, in such a practice of stratification patients fall into smaller and smaller populations and the quality of evidence that can be applied to anyone outside these decreases in turn.[ix] As inductive logic helps to articulate, the greater the number of patients that respond to a particular therapy the higher the probability of its efficacy. By straying from this logical framework, precision medicine opens the treatment of cancer to more uncertainty about the validity of these approaches to the resulting disease subcategories.[x] Thus, while contemporary medical practices explicitly describe some treatments as “personalized”, they ought not be viewed as inherently better founded than other therapies.[xi] A relevant contemporary case of precision medicine out of Norway focuses on the care of a patient with cancer between the ventricles of the heart and esophagus, which had failed to respond to the standard regimen of therapies over four years.[xii] In a last-ditch effort, the patient elected to pay out-of-pocket for an experimental immunotherapy (nivolumab) at a private hospital. He experienced marked improvements and a reduction in the size of the tumor. Understandably, the patient tried to pursue further rounds of nivolumab at a public hospital. However, the hospital initially declined to pay for it given the “lack of evidence from randomised clinical trials for this drug relating to this [patient’s] condition.”[xiii] In rebuttal to this claim, the patient countered that he was actually similar to a subpopulation of patients who responded in “open‐label, single arm, phase 2 studies on another immune therapy drug” (pembrolizumab).[xiv] Given this interpretation of the prior studies and the patient’s response, further rounds of nivolumab were approved. Had the patient not had improvements in the tumor’s size following a round of nivolumab, then pembrolizumab’s prior empirical evidence in isolation would have been insufficient, inductively speaking, to justify his continued use of nivolumab.[xv] The case demonstrates a shift in reasoning from the traditional induction to abduction. The phenomenon of ‘cancer improvement’ is considered causally linked to nivolumab and its underlying physiological mechanisms.[xvi] However, “the weakness of abductions is that there may always be some other better, unknown explanation for an effect. The patient may for example belong to a special subgroup that spontaneously improves, or the change may be a placebo effect. This does not mean, however, that abductive inferences cannot be strong or reasonable, in the sense that they can make a conclusion probable.”[xvii] To demonstrate the limitations of relying on the abductive standard in isolation, commentators have pointed out that side effects in precision medicine are hard to rule out as being related to the initial intervention itself unless trends from a group of patients are taken into consideration.[xviii] As artificial intelligence (AI) assists the development of precision medicine for oncology, this uncertainty ought to be taken into consideration. The implementation of AI has been crucial to the development of precision medicine by providing a way to combine large patient datasets or a single patient with a large number of unique variables with machine learning to recommend matches based on statistics and probability of success upon which practitioners can base medical recommendations.[xix] The AI is usually not establishing a causal relationship[xx] – it is predicting. So, as AI bleeds into medical devices, like brain-computer interfaces, the same cautions about using abductive reasoning alone should be carried over. II. Responsive Neurostimulation, AI, and Personalized Medicine Like precision medicine in cancer treatment, computer-brain interface technology similarly focuses on the individual patient through personalized settings. In order to properly expose the intersection of AI, precision medicine, abductive reasoning, and implantable neurotechnologies, the descriptions of adaptive deep brain stimulation systems need to deepen.[xxi] As a broad summary of adaptive deep brain stimulation, to provide a patient with the therapeutic stimulation, a neural signal, typically referred to as a local field potential,[xxii] must first be detected and then interpreted by the device. The main adaptive deep brain stimulation device with premarket approval, the NeuroPace Responsive Neurostimulation system, is used to treat epilepsy by detecting and storing “programmer-defined phenomena.”[xxiii] Providers can optimize the detection settings of the device to align with the patient’s unique electrographic seizures as well as personalize the reacting stimulation’s parameters.[xxiv] The provider adjusts the technology based on trial and error. One day machine learning algorithms will be able to regularly aid this process in myriad ways, such as by identifying the specific stimulation settings a patient may respond to ahead of time based on their electrophysiological signatures.[xxv] Either way, with AI or programmers, adaptive neurostimulation technologies are individualized and therefore operate in line with precision medicine rather than standard treatments based on large clinical trials. Contemporary neurostimulation devices are not usually sophisticated enough to be prominent in AI discussions where the topics of neural networks, deep learning, generative models, and self-attention dominate the conversation. However, implantable high-density electrocorticography arrays (a much more sensitive version than adaptive deep brain stimulation systems use) have been used in combination with neural networks to help patients with neurologic deficits from a prior stroke “speak” through a virtual avatar.[xxvi] In some experimental situations, algorithms are optimizing stimulation parameters with increasing levels of independence.[xxvii] An example of neurostimulation that is analogous to the use of nivolumab in Norway surrounds a patient in the United States who was experiencing both treatment-resistant OCD and temporal lobe epilepsy.[xxviii]Given the refractory nature of her epilepsy, implantation of an adaptive deep brain stimulation system was indicated. As a form of experimental therapy, her treatment-resistant OCD was also indicated for the off-label use of an adaptive deep brain stimulation set-up. Another deep brain stimulation lead, other than the one implanted for epilepsy, was placed in the patient’s right nucleus accumbens and ventral pallidum region given the correlation these nuclei had with OCD symptoms in prior research. Following this, the patient underwent “1) ambulatory, patient-initiated magnet-swipe storage of data during moments of obsessive thoughts; (2) lab-based, naturalistic provocation of OCD-related distress (naturalistic provocation task); and (3) lab-based, VR [virtual reality] provocation of OCD-related distress (VR provocation task).”[xxix] Such signals were used to identify when to deliver the therapeutic stimulation in order to counter the OCD symptoms. Thankfully, following the procedure and calibration the patient exhibited marked improvements in their OCD symptoms and recently shared her results publicly.[xxx] In both cases, there is a similar level of abductive justification for the efficacy of the delivered therapy. In the case study in which the patient was treated with adaptive deep brain stimulation, they at least had their neural activity tested in various settings to determine the optimum parameters for treatment to avoid them being based on guesswork. Additionally, the adaptive deep brain stimulation lead was already placed before the calibration trials were conducted, meaning that the patient had already taken on the bulk of the procedural risk before the efficacy could be determined. Such an efficacy test could have been replicated in the first patient’s cancer treatment, had it been biopsied and tested against the remaining immunotherapies in vitro. Yet, in the case of cancer with few options, one previous dose of a drug that appeared to work on the patient may justify further doses. However, as the Norwegian case presents, corroboration with known responses to a similar drug (from a clinical trial) could be helpful to validate the treatment strategy. (It should be noted that both patients were resigned to these last resort options regardless of the efficacy of treatment.) There are some elements of inductive logic seen with adaptive deep brain stimulation research in general. For example, abductively the focus could be that patient X’s stimulation parameters are different from patient Y’s and patient Z’s. In contrast, when grouped as subjects who obtained personalized stimulation, patients X, Y, and Z demonstrate an inductive aspect to this approach’s safety and/or efficacy. The OCD case holds plenty of abductive characteristics in line with precision medicine’s approach to treating cancer and as more individuals try the method, there will be additional data. With the gradual integration of AI into brain-computer interfaces in the name of efficacy, this reliance on abduction will continue, if not grow, over time. Moving forward, if a responsive deep brain stimulation treatment is novel and individualized (like the dose of nivolumab) and there is some other suggestion of efficacy (like clinical similarities to other patients in the literature), then it may justify insurance coverage for the investigative intervention, absent other unrelated reasons to deny it. III. Ethical Implications and Next Steps While AI’s use in oncology and neurology is not yet as prominent as its use in other fields (e.g., radiology), it appears to be on the horizon for both.[xxxi] AI can be found in both the functioning of the neurotechnologies as well as the implementation of precision medicine. The increasing use of AI may serve to further individualize both oncologic and neurological therapies. Given these implications and the handful of publications cited in this article, it is important to have a nuanced evaluation of how these treatments, which heavily rely on abductive justification, ought to be managed. The just use an abductive approach may be difficult as AI infused precision medicine is further pursued. At baseline, such technology relies on a level of advanced technology literacy among the general public and could exclude populations who lack access to basic technological infrastructure or know-how from participation.[xxxii] Even among nations with adequate infrastructure, as more patients seek out implantable neurotechnologies, which require robust healthcare resources, the market will favor patient populations that can afford this complex care.[xxxiii] If patients already have the means to pay for an initial dose/use of a precision medicine product out of pocket, should insurance providers be required to cover subsequent treatments?[xxxiv] That is, if a first dose of a cancer drug or a deep brain stimulator over its initial battery life is successful, patients may feel justified in having the costs of further treatments covered. The Norwegian patient’s experience implies there is a precedent for the idea that some public insurance companies ought to cover successful cancer therapies, however, insurance companies may not all see themselves as obligated to cover neurotechnologies that rely on personalized settings or that are based on precision/abductive research more than on clinical trials. CONCLUSION The fact that the cases outlined above rely on abductive style of reasoning implies that there may not be as strong a justification for coverage by insurance, as they are both experimental and individualized, when compared to the more traditional large clinical trials in which groups have the same or a standardized protocol (settings/doses). If a study is examining the efficacy of a treatment with a large cohort of patients or with different experimental groups/phases, insurance companies may conclude that the resulting symptom improvements are more likely to be coming from the devices themselves. A preference for inductive justification may take priority when ruling in favor of funding someone’s continued use of an implantable neurostimulator. There are further nuances to this discussion surrounding the classifications of these interventions as research versus clinical care that warrant future exploration, since such a distinction is more of a scale[xxxv] than binary and could have significant impacts on the “right-to-try” approach to experimental therapies in the United States.[xxxvi] Namely, given the inherent limitations of conducting large cohort trials for deep brain stimulation interventions on patients with neuropsychiatric disorders, surgically innovative frameworks that blend abductive and inductive methodologies, like with sham stimulation phases, have traditionally been used.[xxxvii] Similarly, for adaptive brain-computer interface systems, if there are no large clinical trials and instead only publications that demonstrate that something similar worked for someone else, then, in addition to the evidence that the first treatment/dose worked for the patient in question, the balance of reasoning would be valid and arguably justify insurance coverage. As precision approaches to neurotechnology become more common, frameworks for evaluating efficacy will be crucial both for insurance coverage and for clinical decision making. ACKNOWLEDGEMENT This article was originally written as an assignment for Dr. Francis Shen’s “Bioethics & AI” course at Harvard’s Center for Bioethics. I would like to thank Dr. Shen for his comments as well as my colleagues in the Lázaro-Muñoz Lab for their feedback. - [i] Jonathan Kimmelman and Ian Tannock, “The Paradox of Precision Medicine,” Nature Reviews. Clinical Oncology 15, no. 6 (June 2018): 341–42, https://doi.org/10.1038/s41571-018-0016-0. [ii] Henrik Vogt and Bjørn Hofmann, “How Precision Medicine Changes Medical Epistemology: A Formative Case from Norway,” Journal of Evaluation in Clinical Practice 28, no. 6 (December 2022): 1205–12, https://doi.org/10.1111/jep.13649. [iii] David Barrett and Ahtisham Younas, “Induction, Deduction and Abduction,” Evidence-Based Nursing 27, no. 1 (January 1, 2024): 6–7, https://doi.org/10.1136/ebnurs-2023-103873. [iv] Vogt and Hofmann, “How Precision Medicine Changes Medical Epistemology,” 1208. [v] Wireko Andrew Awuah et al., “Bridging Minds and Machines: The Recent Advances of Brain-Computer Interfaces in Neurological and Neurosurgical Applications,” World Neurosurgery, May 22, 2024, S1878-8750(24)00867-2, https://doi.org/10.1016/j.wneu.2024.05.104. [vi] Mark Riedl, “A Very Gentle Introduction to Large Language Models without the Hype,” Medium (blog), May 25, 2023, https://mark-riedl.medium.com/a-very-gentle-introduction-to-large-language-models-without-the-hype-5 f67941fa59e. [vii] David E. Burdette and Barbara E. Swartz, “Chapter 4 - Responsive Neurostimulation,” in Neurostimulation for Epilepsy, ed. Vikram R. Rao (Academic Press, 2023), 97–132, https://doi.org/10.1016/B978-0-323-91702-5.00002-5. [viii] Kimmelman and Tannock, 2018. [ix] Kimmelman and Tannock, 2018. [x] Simon Lohse, “Mapping Uncertainty in Precision Medicine: A Systematic Scoping Review,” Journal of Evaluation in Clinical Practice 29, no. 3 (April 2023): 554–64, https://doi.org/10.1111/jep.13789. [xi] Kimmelman and Tannock, “The Paradox of Precision Medicine.” [xii] Vogt and Hofmann, 1206. [xiii] Vogt and Hofmann, 1206. [xiv] Vogt and Hofmann, 1206. [xv] Vogt and Hofmann, 1207. [xvi] Vogt and Hofmann, 1207. [xvii] Vogt and Hofmann, 1207. [xviii] Vogt and Hofmann, 1210. [xix] Mehar Sahu et al., “Chapter Three - Artificial Intelligence and Machine Learning in Precision Medicine: A Paradigm Shift in Big Data Analysis,” in Progress in Molecular Biology and Translational Science, ed. David B. Teplow, vol. 190, 1 vols., Precision Medicine (Academic Press, 2022), 57–100, https://doi.org/10.1016/bs.pmbts.2022.03.002. [xx] Stefan Feuerriegel et al., “Causal Machine Learning for Predicting Treatment Outcomes,” Nature Medicine 30, no. 4 (April 2024): 958–68, https://doi.org/10.1038/s41591-024-02902-1. [xxi] Sunderland Baker et al., “Ethical Considerations in Closed Loop Deep Brain Stimulation,” Deep Brain Stimulation 3 (October 1, 2023): 8–15, https://doi.org/10.1016/j.jdbs.2023.11.001. [xxii] David Haslacher et al., “AI for Brain-Computer Interfaces,” 2024, 7, https://doi.org/10.1016/bs.dnb.2024.02.003. [xxiii] Burdette and Swartz, “Chapter 4 - Responsive Neurostimulation,” 103–4; “Premarket Approval (PMA),” https://www.accessdata.fda.gov/scripts/cdrh/cfdocs/cfpma/pma.cfm?id=P100026. [xxiv] Burdette and Swartz, “Chapter 4 - Responsive Neurostimulation,” 104. [xxv] Burdette and Swartz, 126. [xxvi] Sean L. Metzger et al., “A High-Performance Neuroprosthesis for Speech Decoding and Avatar Control,” Nature 620, no. 7976 (August 2023): 1037–46, https://doi.org/10.1038/s41586-023-06443-4. [xxvii] Hao Fang and Yuxiao Yang, “Predictive Neuromodulation of Cingulo-Frontal Neural Dynamics in Major Depressive Disorder Using a Brain-Computer Interface System: A Simulation Study,” Frontiers in Computational Neuroscience 17 (March 6, 2023), https://doi.org/10.3389/fncom.2023.1119685; Mahsa Malekmohammadi et al., “Kinematic Adaptive Deep Brain Stimulation for Resting Tremor in Parkinson’s Disease,” Movement Disorders 31, no. 3 (2016): 426–28, https://doi.org/10.1002/mds.26482. [xxviii] Young-Hoon Nho et al., “Responsive Deep Brain Stimulation Guided by Ventral Striatal Electrophysiology of Obsession Durably Ameliorates Compulsion,” Neuron 0, no. 0 (October 20, 2023), https://doi.org/10.1016/j.neuron.2023.09.034. [xxix] Nho et al. [xxx] Nho et al.; Erik Robinson, “Brain Implant at OHSU Successfully Controls Both Seizures and OCD,” OHSU News, accessed March 3, 2024, https://news.ohsu.edu/2023/10/25/brain-implant-at-ohsu-successfully-controls-both-seizures-and-ocd. [xxxi] Awuah et al., “Bridging Minds and Machines”; Haslacher et al., “AI for Brain-Computer Interfaces.” [xxxii] Awuah et al., “Bridging Minds and Machines.” [xxxiii] Sara Green, Barbara Prainsack, and Maya Sabatello, “The Roots of (in)Equity in Precision Medicine: Gaps in the Discourse,” Personalized Medicine 21, no. 1 (January 2024): 5–9, https://doi.org/10.2217/pme-2023-0097. [xxxiv] Green, Prainsack, and Sabatello, 7. [xxxv] Robyn Bluhm and Kirstin Borgerson, “An Epistemic Argument for Research-Practice Integration in Medicine,” The Journal of Medicine and Philosophy: A Forum for Bioethics and Philosophy of Medicine 43, no. 4 (July 9, 2018): 469–84, https://doi.org/10.1093/jmp/jhy009. [xxxvi] Vijay Mahant, “‘Right-to-Try’ Experimental Drugs: An Overview,” Journal of Translational Medicine 18 (June 23, 2020): 253, https://doi.org/10.1186/s12967-020-02427-4. [xxxvii] Michael S. Okun et al., “Deep Brain Stimulation in the Internal Capsule and Nucleus Accumbens Region: Responses Observed during Active and Sham Programming,” Journal of Neurology, Neurosurgery & Psychiatry 78, no. 3 (March 1, 2007): 310–14, https://doi.org/10.1136/jnnp.2006.095315. (shrink)

The use of autonomous and intelligent personal social robots raises questions concerning their moral standing. Moving away from the discussion about direct moral standing and exploring the normative implications of a relational approach to moral standing, this paper offers four arguments that justify giving indirect moral standing to robots under specific conditions based on some of the ways humans—as social, feeling, playing, and doubting beings—relate to them. The analogy of “the Kantian dog” is used to assist reasoning about (...) this. The paper also discusses the implications of this approach for thinking about the moral standing of animals and humans, showing why, when, and how an indirect approach can also be helpful in these fields, and using Levinas and Dewey as sources of inspiration to discuss some challenges raised by this approach. (shrink)

In this paper, we identify the way in which various forms of legal personhood can be differentiated from one another by comparing these entities with a—not too farfetched—hypothetical situation in which intelligence spontaneously evolves within the internet: spontaneous intelligence. In these terms, we consider the challenges that may arise where SI as an entity: has no owner, no designer, and no controller; has evolved into existence as a non-human created intelligence; is autonomous; has no physical form; and, although it exists (...) around the world, exists in no particular jurisdiction. Based on this refined notion of SI, we consider issues related to the recognition of such an entity’s legal personhood. By briefly exploring the attribution of legal personality to various entities—including, humans, corporations, artificial intelligence and higher forms of animal life—we differentiate SI from these other forms of intelligence whilst illustrating it shares most characteristics with human intelligence and not, as may intuitively be thought, with various forms of AI. After critically evaluating the classification of these various forms of intelligence, we briefly suggest some ramifications of these differences and suggest that the approach adopted may assist in drawing more effective boundaries between the entities that are already recognised as legal persons, as well as between sub-categories of entities, such as various forms of AI. (shrink)

Current research in artificial intelligence (AI) sheds light on algorithmic bias embedded in AI systems. The underrepresentation of women in the AI design sector of the tech industry, as well as in training datasets, results in technological products that encode gender bias, reinforce stereotypes and reproduce normative notions of gender and femininity. Biased behaviour is notably reflected in anthropomorphic AI systems, such as personal intelligent assistants (PIAs) and chatbots, that are usually feminized through various design parameters, such (...) as names, voices and traits. Gendering of AI entities, however, is often reduced to the encoding of stereotypical behavioural patterns that perpetuate normative assumptions about the role of women in society. The impact of this behaviour on social life increases, as human-to-(anthropomorphic)machine interactions are mirrored in human-to-human social interactions. This article presents current critical research on AI bias, focusing on anthropomorphic systems. Moreover, it discusses the significance of women’s engagement in AI design and programming, by presenting selected case studies of contemporary female media artists and designers. Finally, it suggests that women, through their creative practice, provide feminist and critical approaches to AI design which are essential for imagining alternative, inclusive, ethic and de-biased futures for anthropomorphic AIs. (shrink)

BackgroundDespite the recognition that developing artificial intelligence (AI) that is trustworthy is necessary for public acceptability and the successful implementation of AI in healthcare contexts, perspectives from key stakeholders are often absent from discourse on the ethical design, development, and deployment of AI. This study explores the perspectives of birth parents and mothers on the introduction of AI-based cardiotocography (CTG) in the context of intrapartum care, focusing on issues pertaining to trust and trustworthiness.MethodsSeventeen semi-structured interviews were conducted with birth parents (...) and mothers based on a speculative case study. Interviewees were based in England and were pregnant and/or had given birth in the last two years. Thematic analysis was used to analyze transcribed interviews with the use of NVivo. Major recurring themes acted as the basis for identifying the values most important to this population group for evaluating the trustworthiness of AI.ResultsThree themes pertaining to the perceived trustworthiness of AI emerged from interviews: (1) trustworthy AI-developing institutions, (2) trustworthy data from which AI is built, and (3) trustworthy decisions made with the assistance of AI. We found that birth parents and mothers trusted public institutions over private companies to develop AI, that they evaluated the trustworthiness of data by how representative it is of all population groups, and that they perceived trustworthy decisions as being mediated by humans even when supported by AI.ConclusionsThe ethical values that underscore birth parents and mothers’ perceptions of trustworthy AI include fairness and reliability, as well as practices like patient-centered care, the promotion of publicly funded healthcare, holistic care, and personalized medicine. Ultimately, these are also the ethical values that people want to protect in the healthcare system. Therefore, trustworthy AI is best understood not as a list of design features but in relation to how it undermines or promotes the ethical values that matter most to its end users. An ethical commitment to these values when creating AI in healthcare contexts opens up new challenges and possibilities for the design and deployment of AI. (shrink)

Human organizations’ adoption of the paradigm of the Fourth Industrial Revolution is associated with the growth of techno-empowerment, which is the process of transferring autonomy in decision-making to intelligent machines. Particular persuasive strategies have been identified that may coax people to use intelligent devices. However, there is a substantial research gap regarding what antecedents influence human intention to assign decision-making autonomy to artificial agents. In this study, ethological and evolutionary concepts are applied to explain the drivers for autonomous (...) assistants’ techno-empowerment. The method used in the study was a 4 × 2 between-subject experiment made with 278 persons. The research tool used to collect the data was an online survey. The results show that more positive attitudes and higher trust, perceived usefulness, and perceived ease of use are correlated with higher intention to allow the autonomous assistant independence in decision-making. Second, the results suggest that the more human-like a non-human agent is, the higher the intention to empower it—but only if this agent simultaneously provides functional and visual anthropomorphic cues explainable by the mimicry effect. (shrink)

It is a matter of fact that Europe is facing more and more crucial challenges regarding health and social care due to the demographic change and the current economic context. The recent COVID-19 pandemic has stressed this situation even further, thus highlighting the need for taking action. Active and Assisted Living technologies come as a viable approach to help facing these challenges, thanks to the high potential they have in enabling remote care and support. Broadly speaking, AAL can be referred (...) to as the use of innovative and advanced Information and Communication Technologies to create supportive, inclusive and empowering applications and environments that enable older, impaired or frail people to live independently and stay active longer in society. AAL capitalizes on the growing pervasiveness and effectiveness of sensing and computing facilities to supply the persons in need with smart assistance, by responding to their necessities of autonomy, independence, comfort, security and safety. The application scenarios addressed by AAL are complex, due to the inherent heterogeneity of the end-user population, their living arrangements, and their physical conditions or impairment. Despite aiming at diverse goals, AAL systems should share some common characteristics. They are designed to provide support in daily life in an invisible, unobtrusive and user-friendly manner. Moreover, they are conceived to be intelligent, to be able to learn and adapt to the requirements and requests of the assisted people, and to synchronise with their specific needs. Nevertheless, to ensure the uptake of AAL in society, potential users must be willing to use AAL applications and to integrate them in their daily environments and lives. In this respect, video- and audio-based AAL applications have several advantages, in terms of unobtrusiveness and information richness. Indeed, cameras and microphones are far less obtrusive with respect to the hindrance other wearable sensors may cause to one’s activities. In addition, a single camera placed in a room can record most of the activities performed in the room, thus replacing many other non-visual sensors. Currently, video-based applications are effective in recognising and monitoring the activities, the movements, and the overall conditions of the assisted individuals as well as to assess their vital parameters. Similarly, audio sensors have the potential to become one of the most important modalities for interaction with AAL systems, as they can have a large range of sensing, do not require physical presence at a particular location and are physically intangible. Moreover, relevant information about individuals’ activities and health status can derive from processing audio signals. Nevertheless, as the other side of the coin, cameras and microphones are often perceived as the most intrusive technologies from the viewpoint of the privacy of the monitored individuals. This is due to the richness of the information these technologies convey and the intimate setting where they may be deployed. Solutions able to ensure privacy preservation by context and by design, as well as to ensure high legal and ethical standards are in high demand. After the review of the current state of play and the discussion in GoodBrother, we may claim that the first solutions in this direction are starting to appear in the literature. A multidisciplinary debate among experts and stakeholders is paving the way towards AAL ensuring ergonomics, usability, acceptance and privacy preservation. The DIANA, PAAL, and VisuAAL projects are examples of this fresh approach. This report provides the reader with a review of the most recent advances in audio- and video-based monitoring technologies for AAL. It has been drafted as a collective effort of WG3 to supply an introduction to AAL, its evolution over time and its main functional and technological underpinnings. In this respect, the report contributes to the field with the outline of a new generation of ethical-aware AAL technologies and a proposal for a novel comprehensive taxonomy of AAL systems and applications. Moreover, the report allows non-technical readers to gather an overview of the main components of an AAL system and how these function and interact with the end-users. The report illustrates the state of the art of the most successful AAL applications and functions based on audio and video data, namely lifelogging and self-monitoring, remote monitoring of vital signs, emotional state recognition, food intake monitoring, activity and behaviour recognition, activity and personal assistance, gesture recognition, fall detection and prevention, mobility assessment and frailty recognition, and cognitive and motor rehabilitation. For these application scenarios, the report illustrates the state of play in terms of scientific advances, available products and research project. The open challenges are also highlighted. The report ends with an overview of the challenges, the hindrances and the opportunities posed by the uptake in real world settings of AAL technologies. In this respect, the report illustrates the current procedural and technological approaches to cope with acceptability, usability and trust in the AAL technology, by surveying strategies and approaches to co-design, to privacy preservation in video and audio data, to transparency and explainability in data processing, and to data transmission and communication. User acceptance and ethical considerations are also debated. Finally, the potentials coming from the silver economy are overviewed. (shrink)

Mental model ascription – also called mindreading – is the process of inferring the mental states of others, which happens as a matter of course in social interactions. But although ubiquitous, mindreading is presumably a highly variable process: people mindread to different extents and with _different results._ We hypothesize that human mindreading ability relies on a large number of personal and contextual features: the inherent abilities of specific individuals, their current physical and mental states, their knowledge of the domain (...) of discourse, their familiarity with the interlocutor, the risks associated with an incorrect assessment of intent, and so on. This paper presents a theory of mindreading that models diverse artificial intelligent agents using an inventory of parameters and value sets that represent traits of humans and features of discourse contexts. Examples are drawn from Maryland Virtual Patient, a prototype system that will permit medical trainees to diagnose and treat cognitively modeled virtual patients with the optional assistance of a virtual tutor. Since real patients vary greatly with respect to physiological and cognitive features, so must a society of virtual patients. Modeling such variation is one of the goals of the overall OntoAgent program of research and development. (shrink)

Monitoring and assistive technologies (MATs) are being used more frequently in healthcare. A central ethical concern is the compatibility of these systems with the moral preferences of their users—an issue especially relevant to participatory approaches within the ethics-by-design debate. However, users’ incapacity to communicate preferences or to participate in design processes, e.g., due to dementia, presents a hurdle for participatory ethics-by-design approaches. In this paper, we explore the question of how the value preferences of users in the field of dementia (...) care can be integrated into AI-based MATs. First, we briefly introduce different ethics-by-design approaches and explain the challenges they face in dementia care. Next, we introduce a novel approach for addressing these challenges. Through a qualitative content analysis of interviews with persons with dementia and their family caregivers (n = 27), we identified multiple ideal–typical value preference profiles. We then applied these profiles in a computer simulation, by which we also introduce the concept of ethical compliance quantification to scale the moral preferences of the interviewees for the simulation. Finally, we discuss study results, the advantages of using computer simulations, and general study limitations before drawing conclusions for further research. The study contributes to the ongoing debate on participatory ethics-by-design by defining on the basis of empirical data ideal–typical value preference frameworks that can be used to guide MAT actions and their outcomes. Going forward, MAT end-users with dementia and other communication-impaired persons could be enabled to choose a value profile that best fits their moral preferences. (shrink)

The average lifetime of people in advanced countries is significantly increased in the XXI century. The number of old and dependent people is rising due many innovations in health care: new technologies, medicine, and a lot of innovative devices that allow people to monitor their health and consult with a doctor in case of problems. In the last years, a number of information systems have been developed in the health-care area to assist people in living. Modern systems increase their mobility (...) by using personal mobile devices that allows them to interact with the system at any point of time. Smart space is a technology that allows developing such systems. It is an aggregation of devices that can share their resources and cooperate with each other. Sharing personal information between different devices requires ensuring privacy support. For these purposes, a dynamic access control support for information that is shared by devices is needed. In particular, a new access control model for accessing resources is needed. The model should describe the current situation via a context. This paper proposes a model of the context-aware access control for smart systems based on smart space technology. (shrink)

The article endeavours to understand and explain the position of AI humanoids in society. It further makes a unique attempt to describe humanoid robots as “artificial persons,” and while doing so, it sheds light on intriguing, less-debated topics like relationships between humans and artificially intelligent humanoids (AI) and the identity of AI humanoids. The goal of this manuscript is to present the argument that suggests that artificially intelligent humanoid robots are a remarkable creation of human ingenuity and are (...) distinct from typical machines, as they exhibit qualities that extend beyond mere mechanics and aim to reach a degree of complexity akin to humans. These humanoids can form strong connections with humans and possess the ability to communicate, learn, generate information, and assist humans in a multitude of tasks. Therefore, it seems logical to attempt to describe these humanoids as “artificial persons” and try giving them a unique identification or digital signature that may be related in some manner to their owner’s biometric identity. The manuscript employs text analysis to support its arguments and, in the process, delves into the solutions to the aforementioned issues by exploring the concepts proposed by renowned theorists, classical philosophers, and psychologists. (shrink)

Our everyday life is increasingly permeated with digital objects that carry out smart and complex functions. The latest (but certainly not final) advancement of smart digital applications – is to be identified the creation of a field, at once conceptual and material, of things denominated smart objects (henceforth SOs). This technological evolution is so pervasive that it is referred to as smartification. Smart objects have some distinctive features including in particular varying degrees of agency, autonomy and authority. There is no (...) doubt that the SO category is extremely broad, various and intrinsically fuzzy, it is evident that the phenomenon is by no means easy to define: which objects are really smart and which are not? But above all: what do we mean in semio-linguistic, and not psychological nor merely phenomenological terms, when we attribute the qualifier smart to an artifact? What is clear is that a new, or at least different (and controversial) relationship is developing between objects and subjects, or rather between human beings and objects inhabiting the spaces of social action: that is, a new system of objects, to cite Baudrillard (1968), or a new “society of objects” (see Landowski and Marrone 2002). In this paper we will focus on a type of smart physical device designed to interact with its users in the domestic sphere, assisting them in a variety of tasks – such as for example Amazon Echo, capable of connecting to Alexa, an intelligent personal assistant based on machine learning, or the more recent Google Assistant. Our semiotic-oriented – or, more precisely, potentially socio-semiotic/ethno-semiotic – analysis will deal with these issues theoretically by concentrating on the problem of identity, which is anthropologically, but also and above all philosophically, sensitive. We shall look at the impact of technological devices on the perceptive/cognitive systems of human beings, starting with a reflection on the practices of interaction, signification and interpretation that also involve digital objects with a possible impact on everyday life. (shrink)

Neuromarketing relies on Brain Computer Interface (BCI) technology to gain insight into how customers react to marketing stimuli. Marketers spend about$750 billion annually on traditional marketing camping. They use traditional marketing research procedures such as Personal Depth Interviews, Surveys, Focused Group Discussions, and so on, which are frequently criticized for failing to extract true consumer preferences. On the other hand, Neuromarketing promises to overcome such constraints. This work proposes a machine learning framework for predicting consumers' purchase intention (PI) and (...) affective attitude (AA) from analyzing EEG signals. In this work, EEG signals are collected from 20 healthy participants while administering three advertising stimuli settings: product, endorsement, and promotion. After preprocessing, features are extracted in three domains (time, frequency, and time-frequency). Then, after selecting features using wrapper-based methods Recursive Feature Elimination, Support Vector Machine is used for categorizing positive and negative (AA and PI). The experimental results show that proposed framework achieves an accuracy of 84 and 87.00% for PI and AA ensuring the simulation of real-life results. In addition, AA and PI signals show N200 and N400 components when people tend to take decision after visualizing static advertisement. Moreover, negative AA signals shows more dispersion than positive AA signals. Furthermore, this work paves the way for implementing such a neuromarketing framework using consumer-grade EEG devices in a real-life setting. Therefore, it is evident that BCI-based neuromarketing technology can help brands and businesses effectively predict future consumer preferences. Hence, EEG-based neuromarketing technologies can assist brands and enterprizes in accurately forecasting future consumer preferences. (shrink)

Elon Musk famously predicted that an artificial intelligence superior to the smartest individual human would arrive by the year 2025. In response, Gary Marcus offered Musk a $1 million bet to the effect that he would be proved wrong. In specifying the conditions of this bet (which Musk did not take) Marcus lists the following ‘tasks that ordinary people can perform’ which, he claimed, AI will not be able to perform by the end of 2025. • Reliably drive a car (...) in a novel location that they haven’t previously encountered, even in the face of unusual circumstances like hand lettered signs, without the assistance of other humans. • Learn to ride a mountain bike off-road through forest trails. • Babysit children in an unfamiliar home and keep them safe. • Tend to the physical and psychological needs of an elderly or infirm person. Each of these tasks involves the application of practical or tacit knowledge, or what is also called ‘knowing how’, which is to say knowledge of a sort that is captured not by means of sentences or propositions or explicit rules, but rather through the expertise demonstrated in human actions. The talk addresses the puzzle that nowhere in the AI literature do we find a discussion of knowing how as a feature of human intelligence. (shrink)

In 2014, the worldwide context is that the population is increasingly both expanding and aging in industrial countries. In contrast, the personal health levels of individuals could decrease. Although retirement homes and health-care centers assume most of the demand, they will most probably overflow in the next few years. One of the current solutions is e-Health, which involves biomedical monitoring but also home automation functions to compensate for disabilities that tend to increase with age. In this context, several domains (...) have to be merged while respecting the entire ecosystem: the users, their needs and environment, but also all the various actors/experts involved in this process. The issue, however, is that enormous effort is required to combine the multiple expert domains because these can be antinomic. Hence, this paper proposes a collaborative workflow that brings together these different actors and generates the control/command application. Applying model-driven engineering, this workflow makes a clear distinction between people’s health requirements, the home automation functions, and the user interface points of view. Thus, it allows experts in each field to adapt their system in terms of the user’s needs, disability, and health state. (shrink)

Dialogue systems, from Virtual Personal Assistants such as Siri, Cortana, and Alexa to state-of-the-art systems such as BlenderBot3 and ChatGPT, are already widely available, used in a variety of applications, and are increasingly part of many people’s lives. However, the task of enabling them to use empathetic language more convincingly is still an emerging research topic. Such systems generally make use of complex neural networks to learn the patterns of typical human language use, and the interactions in which (...) the systems participate are usually mediated either via interactive text-based or speech-based interfaces. In human–human interaction, empathy has been shown to promote prosocial behaviour and improve interaction. In the context of dialogue systems, to advance the understanding of how perceptions of empathy affect interactions, it is necessary to bring greater clarity to how empathy is measured and assessed. Assessing the way dialogue systems create perceptions of empathy brings together a range of technological, psychological, and ethical considerations that merit greater scrutiny than they have received so far. However, there is currently no widely accepted evaluation method for determining the degree of empathy that any given system possesses (or, at least, appears to possess). Currently, different research teams use a variety of automated metrics, alongside different forms of subjective human assessment such as questionnaires, self-assessment measures and narrative engagement scales. This diversity of evaluation practice means that, given two DSs, it is usually impossible to determine which of them conveys the greater degree of empathy in its dialogic exchanges with human users. Acknowledging this problem, the present article provides an overview of how empathy is measured in human–human interactions and considers some of the ways it is currently measured in human–DS interactions. Finally, it introduces a novel third-person analytical framework, called the Empathy Scale for Human–Computer Communication (ESHCC), to support greater uniformity in how perceived empathy is measured during interactions with state-of-the-art DSs. (shrink)

Debates the difficult moral issues of today such as abortion and euthanasia. Explores the nature of ethics and how we make moral decisions.

This polemical book argues that philosophy's silencing of religion as irrational thinking is wrong and that only religion can offer cogent answers when it comes to understanding life.

Artificial intelligence and robotic technologies have become nearly ubiquitous. In some ways, the developments have likely helped us, but in other ways sophisticated technologies set back our interests. Among the latter sort is what has been dubbed the ‘severance problem’—the idea that technologies sever our connection to the world, a connection which is necessary for us to flourish and live meaningful lives. I grant that the severance problem is a threat we should mitigate and I ask: how can we stave (...) it off? In particular, the fact that some technologies exhibit behavior that is unclear to us seems to constitute a kind of severance. Building upon contemporary work on moral responsibility, I argue for a mechanism I refer to as ‘technological answerability’, namely the capacity to recognize human demands for answers and to respond accordingly. By designing select devices—such as robotic assistants and personal AI programs—for increased answerability, we see at least one way of satisfying our demands for answers and thereby retaining our connection to a world increasingly occupied by technology. (shrink)

Health is on of those subjects that seems easy to define and then, the closer one gets, is more and more difficult to understand. Does the health of a schizophrenic really improve by being sedated and kept in an asylum? Is a course of Prozac or psychotherapy aimed to make someone happy really a medicine? These incompatible views are most visible in the NHS which has over the decades become the focus of all these projections of health. At the expense (...) of the taxpayer many are being cured while there is no money for some of those who have physical ailments in a real sense. In this book, Theodore Dalrymple sets out to tear into the myths that he believes our politicians have created, with anecdotes from his own experience as a doctor. (shrink)

The aim of this study was to investigate the experiences of persons with severe functional disabilities who receive personal assistance in their homes, the focus being on their daily life in relation to the ethical principles represented in the Swedish Disability Act: autonomy, integrity, influence and participation. Qualitative interviews were performed with 26 persons and thereafter subjected to qualitative latent content analysis. The experiences of personal assistance were very much in accordance with the said principles, the most important (...) factor being that one is met with understanding. The participants described situations in which their integrity was violated in that they were not treated as competent adults. This indicates the importance of future efforts in nursing to support personal assistants with ethical knowledge and supervision so that they can empower people with disabilities and thereby enable them to maintain their self-esteem and dignity. (shrink)

The prevalence of technology-embedded products, services, and cities, described colloquially as ‘smart’ technologies and ‘smart’ cities, has seen a spate of unprecedented growth in recent years. South Africa (SA) has not been left behind, with smartphones, smart watches, and smart voice-controlled virtual personal assistants such as Amazon’s Alexa now frequently used. But while these technologies hold great promise to revolutionise homes, offices and cities, their adoption poses challenges to individual and collective interests and wellbeing. After demonstrating the legal (...) and ethical difficulties brought about by the introduction of these technologies, this article explores whether SA legislation is sufficiently robust to address these challenges. While the current legislative landscape addresses certain crucial difficulties – such as the safeguarding of personal data by the Protection of Personal Information Act No. 4 of 2013 (‘POPIA’) – it is suggested that the position regulating other aspects of smart technology adoption is, in large part, fragmented and ill-equipped to deal with some of the more pressing legal and ethical questions. Our contention is that, not dissimilar to the issues arising from artificial intelligence-based technological adoption, the extant legislative and regulatory frameworks do not go far enough in addressing the many concerns emerging from recent novel technological design, development, and deployment. Not only do smart technologies give rise to unique challenges, so does their deployment within the Global South and in South Africa, in particular. We suggest that appropriate and effective regulatory reform measures be undertaken in SA to provide better ethical guidance and policy prescriptions buttressed by rigorous regulatory oversight. (shrink)

Stimulating discussion of the fundamental concepts we employ in every day consideration of moral questions for the general reader.

When someone hosts a party, when governments choose an aid program, or when assistive robots decide what meal to serve to a family, decision‐makers must determine how to help even when their recipients have very different preferences. Which combination of people’s desires should a decision‐maker serve? To provide a potential answer, we turned to psychology: What do people think is best when multiple people have different utilities over options? We developed a quantitative model of what people consider desirable behavior, characterizing (...) participants’ preferences by inferring which combination of “metrics” (maximax, maxsum, maximin, or inequality aversion [IA]) best explained participants’ decisions in a drink‐choosing task. We found that participants’ behavior was best described by the maximin metric, describing the desire to maximize the happiness of the worst‐off person, though participant behavior was also consistent with maximizing group utility (the maxsum metric) and the IA metric to a lesser extent. Participant behavior was consistent across variation in the agents involved and tended to become more maxsum‐oriented when participants were told they were players in the task (Experiment 1). In later experiments, participants maintained maximin behavior across multi‐step tasks rather than shortsightedly focusing on the individual steps therein (Experiment 2, Experiment 3). By repeatedly asking participants what choices they would hope for in an optimal, just decision‐maker, and carefully disambiguating which quantitative metrics describe these nuanced choices, we help constrain the space of what behavior we desire in leaders, artificial intelligence systems helping decision‐makers, and the assistive robots and decision‐makers of the future. (shrink)

A modern philosopher and author of Modern Philosophy presents a useful, refreshing guide for "doing" rather than "studying" philosophy, making the subject accessible and real to the layperson. 10,000 first printing.