Principles of fairness and solidarity in AI ethics regularly overlap, creating obscurity in practice: acting in accordance with one can appear indistinguishable from deciding according to the rules of the other. However, there exist irregular cases where the two concepts split, and so reveal their disparate meanings and uses. This paper explores two cases in AI medical ethics – one that is irregular and the other more conventional – to fully distinguish fairness and solidarity. Then the distinction is applied to (...) the frequently cited COMPAS versus ProPublica dispute in judicial ethics. The application provides a broader model for settling contemporary and topical debates about fairness and solidarity. It also implies a deeper and disorienting truth about AI ethics principles and their justification. (shrink)

Shen et al. (2024) present a new and updated framework on the ethical, social, and legal implications of returning individual research results (IRRs) in digital phenotyping psychiatric research. Th...

The field of AI has undergone a series of transformations, each marking a new phase of development. The initial phase emphasized curation of symbolic models which excelled in capturing reasoning but were fragile and not scalable. The next phase was characterized by machine learning models—most recently large language models (LLMs)—which were more robust and easier to scale but struggled with reasoning. Now, we are witnessing a return to symbolic models as complementing machine learning. Successes of LLMs contrast with their inscrutability, (...) inaccuracy, and hallucinations, which underwrite concerns over the reliability and trustworthiness of these systems, motivating investigations into commonsense reasoning, AI explainability, and formal verification techniques. Moreover, proper assessments of hybrid machine learning/symbolic systems require novel strategies to facilitate comparisons of performance and guide future AI progress. The EDGeS AAAI 2023 Spring symposium brought together researchers focusing on novel assessments and benchmarks for evaluating hybrid and artificial general intelligence (AGI) systems. This symposium revealed what was already suspected: research concerning evaluation of machine learning/symbolic hybrids and AGI is, unfortunately, lacking. Even so, the discussion was fruitful. (shrink)

In recent years, the European Union has advanced towards responsible and sustainable Artificial Intelligence (AI) research, development and innovation. While the Ethics Guidelines for Trustworthy AI released in 2019 and the AI Act in 2021 set the starting point for a European Ethical AI, there are still several challenges to translate such advances into the public debate, education and practical learning. This paper contributes towards closing this gap by reviewing the approaches that can be found in the existing literature and (...) by interviewing 11 experts across five countries to help define educational strategies, competencies and resources needed for the successful implementation of Trustworthy AI in Higher Education (HE) and to reach students from all disciplines. The findings are presented in the form of recommendations both for educators and policy incentives, translating the guidelines into HE teaching and practice, so that the next generation of young people can contribute to an ethical, safe and cutting-edge AI made in Europe. (shrink)

Sovereignty and strategic autonomy are felt to be at risk today, being threatened by the forces of rising international tensions, disruptive digital transformations and explosive growth of cybersecurity incidents. The combination of AI and cybersecurity is at the sharp edge of this development and raises many ethical questions and dilemmas. In this commentary, I analyse how we can understand the ethics of AI and cybersecurity in relation to sovereignty and strategic autonomy. The analysis is followed by policy recommendations, some (...) of which may appear to be controversial, such as the strategic use of ethics. I conclude with a reflection on underlying concepts as an invitation for further research. The goal is to inspire policy-makers, academics and business strategists in their work, and to be an input for public debate. (shrink)

Applications of artificial intelligence (AI) for cybersecurity tasks are attracting greater attention from the private and the public sectors. Estimates indicate that the market for AI in cybersecurity will grow from US$1 billion in 2016 to a US$34.8 billion net worth by 2025. The latest national cybersecurity and defence strategies of several governments explicitly mention AI capabilities. At the same time, initiatives to define new standards and certification procedures to elicit users’ trust in AI are emerging on a global scale. (...) However, trust in AI (both machine learning and neural networks) to deliver cybersecurity tasks is a double edged sword: it can improve substantially cybersecurity practices, but can also facilitate new forms of attacks to the AI applications themselves, which may pose severe security threats. We argue that trust in AI for cybersecurity is unwarranted and that, to reduce security risks, some form of control to ensure the deployment of ‘reliable AI’ for cybersecurity is necessary. To this end, we offer three recommendations focusing on the design, development and deployment of AI for cybersecurity. (shrink)

Sovereignty and strategic autonomy are felt to be at risk today, being threatened by the forces of rising international tensions, disruptive digital transformations and explosive growth of cybersecurity incidents. The combination of AI and cybersecurity is at the sharp edge of this development and raises many ethical questions and dilemmas. In this commentary, I analyse how we can understand the ethics of AI and cybersecurity in relation to sovereignty and strategic autonomy. The analysis is followed by policy recommendations, some (...) of which may appear to be controversial, such as the strategic use of ethics. I conclude with a reflection on underlying concepts as an invitation for further research. The goal is to inspire policy-makers, academics and business strategists in their work, and to be an input for public debate. (shrink)

Sovereignty and strategic autonomy are felt to be at risk today, being threatened by the forces of rising international tensions, disruptive digital transformations and explosive growth of cybersecurity incidents. The combination of AI and cybersecurity is at the sharp edge of this development and raises many ethical questions and dilemmas. In this commentary, I analyse how we can understand the ethics of AI and cybersecurity in relation to sovereignty and strategic autonomy. The analysis is followed by policy recommendations, some (...) of which may appear to be controversial, such as the strategic use of ethics. I conclude with a reflection on underlying concepts as an invitation for further research. The goal is to inspire policy-makers, academics and business strategists in their work, and to be an input for public debate. (shrink)

This book explores the revolutionary intersection of Generative AI (GenAI) and cybersecurity. It presents a comprehensive guide that intertwines theories and practices, aiming to equip cybersecurity professionals, CISOs, AI researchers, developers, architects and college students with an understanding of GenAI’s profound impacts on cybersecurity. The scope of the book ranges from the foundations of GenAI, including underlying principles, advanced architectures, and cutting-edge research, to specific aspects of GenAI security such as data security, model security, application-level security, and the emerging (...) fields of LLMOps and DevSecOps. It explores AI regulations around the globe, ethical considerations, the threat landscape, and privacy preservation. Further, it assesses the transformative potential of GenAI in reshaping the cybersecurity landscape, the ethical implications of using advanced models, and the innovative strategies required to secure GenAI applications. Lastly, the book presents an in-depth analysis of the security challenges and potential solutions specific to GenAI, and a forward-looking view of how it can redefine cybersecurity practices. By addressing these topics, it provides answers to questions on how to secure GenAI applications, as well as vital support with understanding and navigating the complex and ever-evolving regulatory environments, and how to build a resilient GenAI security program. The book offers actionable insights and hands-on resources for anyone engaged in the rapidly evolving world of GenAI and cybersecurity. (shrink)

We present nine facets for the analysis of the past and future evolution of AI. Each facet has also a set of edges that can summarise different trends and contours in AI. With them, we first conduct a quantitative analysis using the information from two decades of AAAI/IJCAI conferences and around 50 years of documents from AI topics, an official database from the AAAI, illustrated by several plots. We then perform a qualitative analysis using the facets and edges, locating AI (...) systems in the intelligence landscape and the discipline as a whole. This analytical framework provides a more structured and systematic way of looking at the shape and boundaries of AI. (shrink)

This groundbreaking proceedings volume explores the integration of Artificial Intelligence (AI) across key domains—healthcare, finance, education, robotics, industrial and other engineering applications —unveiling its transformative potential and practical implications. With a multidisciplinary lens, it transcends technical aspects, fostering a comprehensive understanding while bridging theory and practice. Approaching the subject matter with depth, the book combines theoretical foundations with real-world case studies, empowering researchers, professionals, and enthusiasts with the knowledge and tools to effectively harness AI. Encompassing diverse AI topics—machine learning, natural (...) language processing, computer vision, data analytics and supervisory control — the volume showcases state-of-the-art techniques propelling AI advancements. Structured into four parts: Part 1: Artificial Intelligence (AI), explores evolving deep neural networks, reinforcement learning, and explainable AI, providing a deep dive into the technical foundations of AI advancements. Part 2: Robotics and Control Systems, delves into the integration of AI in robotics and automatic control, addressing supervisory control, automated robotic movement coordination, anomaly detection, dynamic programming, and fault tolerance, offering insights into the evolving landscape of intelligent automation. Part 3: AI and Society, examines the societal impact of AI through chapters on ethical considerations, economic growth, environmental engagements, and hazard management, providing a holistic perspective on AI's role in shaping society. Part 4: PhD Symposium, presents the future of AI through cutting-edge research, covering legal and ethical dimensions, privacy considerations, and computationally efficient solutions, offering a glimpse into the next generation of AI advancements. Catering to a diverse audience—from industry leaders to students—the volume consolidates the expertise of renowned professionals, serving as a comprehensive resource for navigating the ever-evolving AI landscape. An essential reference for those staying at the forefront of AI developments. (shrink)

Any first step in organisational adaptation starts with individuals’ responses and willingness (or otherwise) to change an aspect of themselves given the transcontextual settings in which they are operating (Bateson in Small arcs of larger circles: framing through other patterns, Triarchy Press, Axminster, 2018). This research explores the implications for organisational adaptation strategies when Artificial Intelligence (AI) is being embedded into the ecology of the organisation, and when employees have a dominant fixed or growth mindset (Dweck in Mindset: changing the (...) way you think to fulfil your potential. Robinson, London, 2017). Research participants were supplied with a single scenario based in 2030, where—as a result of Artificial Intelligence technology implementation—employees were going to be displaced. Using Torbert’s (Organizational wisdom and executive courage, New Lexington Press, San Francisco, 1998) ‘first, second and third person’ research theory, participants were asked to independently review their thoughts, sense, and image of the future from a fixed mindset position (considered to be the worst case), then from a growth mindset perspective (best case), and then do the same collectively. Five key findings are outlined which support the principle that having a growth mindset is a key component of adaptive capacity and futures literacy. The five key findings conclude that AI adaptation processes need to include compassion and authenticity, embodiment, fundamental needs and motivations, mutual learning and considering what lies beyond the edges of the organisation (Bateson in Small arcs of larger circles: framing through other patterns, Triarchy Press, Axminster, 2018). (shrink)

October 14, 2007: Studying how a broker's brain works. swissinfo. "To help maintain its competitive edge, the Swiss banking industry is investing heavily in financial engineering. Its latest recruit is economist Peter Bossaerts. swissinfo talked to Bossaerts, a leading expert in neuroeconomics – the study of how we make financial choices - about his recent appointment as professor at the Federal Institute of Technology in Lausanne.... swissinfo: So what exactly is neuroeconomics? Peter Bossaerts: It's a mixture of decisional theory (...) - mathematical theories applied in risk-based decision-making - and neuroscience.... Neurofinance, therefore, tries to understand how choices are made in a risky world. It looks closely at the workings of the brain while taking into account human emotions.... swissinfo: What is the aim of your work? P.B.: Firstly, to make progress on how people make choices when dealing with risk.... Neuroeconomics should also help improve decisional theory, which doesn't work in the real world where rules are vague and probabilities are unknown. The aim is to build up artificial intelligence based on a theory where decision-making is repeated." >>> Neuroscience, Cognitive Science, Finance & Investing, Applications. (shrink)

Broadening access to both computational and educational resources is crit- ical to diffusing machine learning (ML) innovation. However, today, most ML resources and experts are siloed in a few countries and organizations. In this article, we describe our pedagogical approach to increasing access to applied ML through a massive open online course (MOOC) on Tiny Machine Learning (TinyML). We suggest that TinyML, applied ML on resource-constrained embedded devices, is an attractive means to widen access because TinyML leverages low-cost and globally (...) accessible hardware and encourages the development of complete, self-contained applications, from data collection to deployment. To this end, a collaboration between academia and industry produced a four part MOOC that provides application-oriented instruction on how to develop solutions using TinyML. The series is openly available on the edX MOOC platform, has no prerequisites beyond basic programming, and is designed for global learners from a variety of backgrounds. It introduces real-world applications, ML algorithms, data-set engineering, and the ethi- cal considerations of these technologies through hands-on programming and deployment of TinyML applications in both the cloud and on their own microcontrollers. To facili- tate continued learning, community building, and collaboration beyond the courses, we launched a standalone website, a forum, a chat, and an optional course-project com- petition. We also open-sourced the course materials, hoping they will inspire the next generation of ML practitioners and educators and further broaden access to cutting-edge ML technologies. (shrink)

'if AI is outside your field, or you know something of the subject and would like to know more then Artificial Intelligence: The Basics is a brilliant primer.' - Nick Smith, Engineering and Technology Magazine November 2011 Artificial Intelligence: The Basics is a concise and cutting-edge introduction to the fast moving world of AI. The author Kevin Warwick, a pioneer in the field, examines issues of what it means to be man or machine and looks at advances in robotics (...) which have blurred the boundaries. Topics covered include: how intelligence can be defined whether machines can 'think' sensory input in machine systems the nature of consciousness the controversial culturing of human neurons. Exploring issues at the heart of the subject, this book is suitable for anyone interested in AI, and provides an illuminating and accessible introduction to this fascinating subject. (shrink)

This book reports on the results of the third edition of the premier conference in the field of philosophy of artificial intelligence, PT-AI 2017, held on November 4 - 5, 2017 at the University of Leeds, UK. It covers: advanced knowledge on key AI concepts, including complexity, computation, creativity, embodiment, representation and superintelligence; cutting-edge ethical issues, such as the AI impact on human dignity and society, responsibilities and rights of machines, as well as AI threats to humanity and AI (...) safety; and cutting-edge developments in techniques to achieve AI, including machine learning, neural networks, dynamical systems. The book also discusses important applications of AI, including big data analytics, expert systems, cognitive architectures, and robotics. It offers a timely, yet very comprehensive snapshot of what is going on in the field of AI, especially at the interfaces between philosophy, cognitive science, ethics and computing. (shrink)

The paper continues my earlier Chat with OpenAI’s ChatGPT with a Focused LLM Experiment (FLEX). The idea is to conduct Large Language Model (LLM) based explorations of certain areas or concepts. The approach is based on crafting initial guiding prompts and then follow up with user prompts based on the LLMs’ responses. The goals include improving understanding of LLM capabilities and their limitations culminating in optimized prompts. The specific subjects explored as research subject matter include a) diagonalization techniques as practiced (...) by Cantor, Turing, Gödel, and the advances, such as the Forcing techniques introduced by Paul Cohen and later investigators, b) Knowledge Hierarchies & Mapping Exercises, c) Discussions of IJ Good’s Speculations Concerning the First Ultraintelligent Machine, AGI, and Super- intelligence. Results suggest variability between major models like ChatGPT-4, Llama-3, Cohere, Sonnet and Opus. Results also point to strong dependence on users’ preexisting knowledge and skill bases. The paper should be viewed as ’raw data’ rather than a polished authoritative reference. (shrink)

[Müller, Vincent C. (ed.), (2013), Philosophy and theory of artificial intelligence (SAPERE, 5; Berlin: Springer). 429 pp. ] --- Can we make machines that think and act like humans or other natural intelligent agents? The answer to this question depends on how we see ourselves and how we see the machines in question. Classical AI and cognitive science had claimed that cognition is computation, and can thus be reproduced on other computing machines, possibly surpassing the abilities of human intelligence. This (...) consensus has now come under threat and the agenda for the philosophy and theory of AI must be set anew, re-defining the relation between AI and Cognitive Science. We can re-claim the original vision of general AI from the technical AI disciplines; we can reject classical cognitive science and replace it with a new theory (e.g. embodied); or we can try to find new ways to approach AI, for example from neuroscience or from systems theory. To do this, we must go back to the basic questions on computing, cognition and ethics for AI. The 30 papers in this volume provide cutting-edge work from leading researchers that define where we stand and where we should go from here. (shrink)

Artificial intelligence (AI) is the ability of a digital computer or computer-controlled robot to perform tasks commonly associated with intelligent beings. Artificial intelligence can be both a blessing and a curse, and potentially a double-edged sword if not carefully wielded. While it holds massive potential benefits to humans—particularly in healthcare by assisting in treatment of diseases, surgeries, record keeping, and easing the lives of both patients and doctors, its misuse has potential for harm through impact of biases, unemployment, breaches of (...) privacy, and lack of accountability to mention a few. In this article, we discuss the fourth industrial revolution, through a focus on the core of this phenomenon, artificial intelligence. We outline what the fourth industrial revolution is, its basis around AI, and how this infiltrates human lives and society, akin to a transcendence. We focus on the potential dangers of AI and the ethical concerns it brings about particularly in developing countries in general and conflict zones in particular, and we offer potential solutions to such dangers. While we acknowledge the importance and potential of AI, we also call for cautious reservations before plunging straight into the exciting world of the future, one which we long have heard of only in science fiction movies. (shrink)

Background: The introduction of healthcare AI to society as well as the clinical setting will improve individual health statuses and increase the possible medical choices. AI can be, however, regarded as a double-edged sword that might cause medically and socially undesirable situations. In this paper, we attempt to predict several negative situations that may be faced by healthcare professionals, patients and citizens in the healthcare setting, and our society as a whole. Discussion: We would argue that physicians abuse healthcare AI (...) through their excessive and dependent use of it, and they will focus only on the AI services in their office and patient medical data and information, and forget to observe the patient in their clinical encounters. In the era of AI introduction, data from the wearable terminal or AI advice will become the primary target of the physician’s interest, and could be regarded as a patient surrogate. Paternalism would be paradoxically resurrected by the introduction of state-of-the-art AI. A physician’s conflict of interest related to AI as a commercial product could strongly influence his or her actions in clinical settings. We also worry that the general public will become uneasy and hypersensitive slaves to information, compulsively and uninterruptedly requesting healthcare information concerning their own health and advice from AI. An AI system capable of expressing proper and timely empathy to suffering patients could deprive healthcare professionals of their roles in terms of hospitality and emotional exchange. Finally, entire societies would soon share and consolidate healthcare sensitive information from all in the general public as part of a totalitarian healthcontrolled society where individual privacy and personal secrets could be neglected. The advent of the healthcontrolled society could lead to the metamorphosis of the concept of privacy itself into something completely different. Conclusion: Although AI which surpasses human healthcare professionals may never appear, hoping for the best and preparing for the worst is the best approach to take. To this end, we present some potential countermeasures including conducting clinical research and social investigations concerning problems surrounding the introduction of AI and developing guidelines for its appropriate use. (shrink)

: Fodor’s view of the mind is thoroughly computational. This means that the basic kind of mental entity is a “discursive” mental representation and operations over this kind of mental representation have broad architectural scope, extending out to the edges of perception and the motor system. However, in multiple epochs of his work, Fodor attempted to define a functional role for non-discursive, imagistic representation. I describe and critique his two considered proposals. The first view says that images play a particular (...) kind of functional role in certain types of deliberative tasks. The second says that images are solely restricted to the borders of perception, and act as a sort of medium for the fixing of conceptual reference. I argue, against the first proposal, that a broad-scope computationalism such as Fodor’s renders images in principle functionally redundant. I argue, against the second proposal, that empirical evidence suggests that non-discursive representations are learned through perceptual learning, and directly inform category judgments. In each case, I point out extant debates for which the arguments are relevant. The upshot is that there is motivation for limited scope computationalism, in which some, but not all, mental processes operate on discursive mental representations. Keywords: Computational Theory of Mind; Mental Representation; Perception; Mental Image; Jerry Fodor Fodor e le rappresentazioni mentali come immagini Riassunto: La concezione della mente di Fodor è rigorosamente computazionale, ossia le entità mentali di base sono rappresentazioni mentali “discorsive”. Le operazioni su queste rappresentazioni hanno un fine architettonico ampio, che va fino ai confini della percezione e del sistema motorio. In periodi diversi del suo lavoro, Fodor ha proposto due modi per definire un ruolo funzionale per la rappresentazione non-discorsiva come immagine. Tratterò criticamente entrambi. Per il primo, le immagini giocano un particolare tipo di ruolo funzionale in certi tipi di compiti deliberativi, mentre, per il secondo, sono relegate unicamente ai confini della percezione, agendo come medium per fissare il riferimento concettuale. Contro il primo sosterrò che un computazionalismo così ampio come quello di Fodor rende le immagini in principio funzionalmente ridondanti. Contro il secondo sosterrò che l’evidenza empirica suggerisce che le rappresentazioni non-discorsive vengono apprese percettivamente, agendo direttamente sui giudizi di categorizzazione. In entrambi i casi considererò gli argomenti più rilevanti nel dibattito corrente. Si vedrà che ci sono buone ragioni in favore di un computazionalismo più limitato, in cui alcuni processi mentali operano su rappresentazioni mentali discorsive. Parole chiave: Teoria computazionale della mente; Rappresentazione mentale; Percezione; Immagine mentale; Jerry Fodor. (shrink)

The Human Brain Project (HBP) is a massive interdisciplinary project involving hundreds of researchers across more than eighty institutions that seeks to leverage cutting edge information and communication technologies to create a multi-level brain simulation platform (BSP). My worry is that some brain models running on the BSP will be persons. If this is right then not only will the in silico experiments the HBP envisions being carried on the BSP be unethical the mere termination of certain brain models (...) running on the BSP will be unethical. To assess the possible personhood of certain brain simulations I consider John Searle’s critique of strong AI. In arguing that Searle’s critique fails I conclude that the HBP must tread carefully and devise strict rules on how research using the BSP ought to proceed. (shrink)

In this article, I review textual evidence demonstrating that James and Dewey incorporated Kant’s ideas, even while criticizing him. I specifically argue that the pragmatic evolution of the Kantian a priori carried out by James and Dewey is a transition from the mental to the bodily. I further argue that the parallels between pragmatists and Kant, along with the transition from the mental to bodily, relate to scientific contexts in which all developed their outlooks. Though historically grounded, my ultimate goal (...) is to show that pragmatism and by extension Kantianism mesh with and indeed contribute to cutting edge ideas in fields ranging from neuropathology to robotics and AI to cognitive science, whether in the form of Gibsonian theory or enactivism. (shrink)

This edited volume presents an overview of cutting-edge research areas within digital ethics as defined by the Digital Ethics Lab of the University of Oxford. It identifies new challenges and opportunities of influence in setting the research agenda in the field. The yearbook presents research on the following topics: conceptual metaphor theory, cybersecurity governance, cyber conflicts, anthropomorphism in AI, digital technologies for mental healthcare, data ethics in the asylum process, AI’s legitimacy and democratic deficit, digital afterlife industry, automatic prayer (...) bots, foresight analysis and the future of AI. This volume appeals to students, researchers and professionals. (shrink)

In lieu of an abstract, here is a brief excerpt of the content:Global Health Careers:Serving the Navajo CommunityMaricruz Merino, Jonathan Iralu, and Sonya ShinGallup Indian Medical Center (GIMC) sits on a hilltop in Gallup, New Mexico, a town of 20,000 in the four corners region of the Southwestern United States. From its third story windows one can see the red cliffs of the nearby Navajo Nation, a 27,000 square mile reservation that reaches into Arizona, northern New Mexico, and the southern (...) edges of Utah. It is a vast, rural landscape that houses more than 350,000 Navajos. For many on the reservation, healthcare is provided by Indian Health Service hospitals such as GIMC."Are you going to stay?" is a common question for new doctors at GIMC. The Navajo know that their geographic location, while beautiful and attractive to many young providers, will also be the reason they leave. It is hard for doctors to be away from their own homelands. Aging parents get sick, [End Page 86] educational opportunities arise, and children who need to be near extended family are born. But to the Navajo, the story of an individual provider is not so important or memorable. All they know is that providers come and go."Are you here to experiment on us?" is yet another question. Years of exploitation and efforts to destroy traditional ways and language have made many Navajo wary of healthcare providers, no matter how genuine their intentions. Many are so fearful of the hospital—they regard it as "the place to go die."Yet despite this initial suspicion, the Navajo are welcoming people at heart, and tend to develop relationships of trust with their providers. Parents will begin to talk about their grief over a son that has committed suicide or a daughter who died from alcoholic cirrhosis. The elderly will tell you how they care for their five orphaned grandchildren while they can barely take care of their own diabetes. A carpenter tells you he has not worked in a year and feels worthless. An HIV-positive woman will tell you she has been sleeping in a dry river bed because she has no place to go. It quickly becomes apparent that as a physician you will be treating patients with enormous social challenges in addition to complex medical conditions.The origins of the Federal Government's involvement in the healthcare of American Indians and Alaskan Natives (AI/ANs) in the 19th century arose out of both legal obligation and concern for self- preservation. Health services were promised to AI/ ANs in exchange for land, settlements, and agreements. In addition, infectious diseases endemic on reservations as a consequence of crowding and abject poverty, including smallpox and tuberculosis, were seen as a major public health concern. The responsibility of Native American health was first granted to the War Department, then to the Bureau of Indian Affairs, and finally to the Public Health Service in 1955 under the heading of the IHS, or Indian Health Service (U.S. Commission on Civil Rights, 2004; National Library of Medicine, 1994).Since then, the IHS has had many successes. Vaccination rates have gone up, and rates of pneumonia and tuberculosis have gone down significantly. Maternal and infant mortality have declined, and life expectancy has increased (Indian Health Services, 1999). Nonetheless, these improvements remain overshadowed by glaring health disparities among AI/ANs across a broad spectrum of diseases, both communicable and non-communicable, acute and chronic. Native Americans experience higher rates of obesity, diabetes, and cardiovascular disease than the general United States population. They are also more likely to die from alcohol-related causes and in accidents. Life expectancy remains more than five years less than that of the general U.S. population (U.S. Commission on Civil Rights, 2004; U.S. Department of Health and Human Services, 2000).Underlying these health indicators is the continued impoverished status of most AI/ANs. In Navajo, almost half of the population lives below the poverty line. According to the Navajo Nation, the current unemployment rate is 42% (Navajo Nation Department of Economic Development, 2011). Many Navajo on the reservation do not have running water or electricity. They heat with wood, which they chop and haul themselves—regardless... (shrink)

Defence agencies across the globe identify artificial intelligence as a key technology to maintain an edge over adversaries. As a result, efforts to develop or acquire AI capabilities for defence are growing on a global scale. Unfortunately, they remain unmatched by efforts to define ethical frameworks to guide the use of AI in the defence domain. This article provides one such framework. It identifies five principles—justified and overridable uses, just and transparent systems and processes, human moral responsibility, meaningful human (...) control and reliable AI systems—and related recommendations to foster ethically sound uses of AI for national defence purposes. (shrink)

Artificial intelligence is a cutting-edge technology that has been widely applied in tourism operations. To enhance tourists' experience, many tourism suppliers introduced AI devices to interact with tourists. Previous studies classified AI devices as task- and social- oriented based on their functions; however, current models that explain customers' intention to use AI devices did not reflect the discrepancy between the two different types. Therefore, this paper attempts to fill this gap by proposing a theoretical model for the use of (...) task-oriented AI devices. Based on the multi-stage appraisal framework and the Structural Equation Modeling analysis, this paper presents the following findings: utilitarian motivation, interaction convenience, and task-technology fit are the factors appraised in the first stage; perceived competence and flow experience are the factors appraised in the second stage; utilitarian motivation, interaction convenience, and task-technology fit are positively associated with perceived competence. Perceived competence positively influences flow experience, which further affects customers' switching intention from task-oriented AI devices to human service; the serial mediating effect of perceived competence and flow experience between the stimulus mentioned in the first appraisal stage and the switching intention is confirmed. This study reveals the underlying psychological mechanism when customers use task-oriented AI devices, and it provides a theoretical framework for task-oriented AI device adoption. (shrink)

COVID-19 has had a profound impact on the lives of all human beings. Emerging technologies have made significant contributions to the fight against the pandemic. An extensive review of the application of tech- nology will help facilitate future research and technology development to provide better solutions for future pan- demics. In contrast to the extensive surveys of academic communities that have already been conducted, this study explores the IT community of practice. Using GitHub as the study target, we analysed the (...) main functionalities of the projects submitted during the pandemic. This study examines trends in projects with different functionalities and the relationship between functionalities and technolo- gies. The study results show an imbalance in the number of projects with varying functionalities in the GitHub community, i.e., applications account for more than half of the projects. In contrast, other data analysis and AI projects account for a smaller share. This differs significantly from the survey of the academic community, where the findings focus more on cutting-edge technologies while projects in the community of practice use more mature technologies. The spontaneous behavior of developers may lack organization and make it challenging to target needs. Keywords: COVID, communities of practice, technologies, functionalities. (shrink)

Transformer-based language models (TLMs) have widely been recognized to be a cutting-edge technology for the successful development of deep-learning-based solutions to problems and applications that require natural language processing and understanding. Like for other textual domains, TLMs have indeed pushed the state-of-the-art of AI approaches for many tasks of interest in the legal domain. Despite the first Transformer model being proposed about six years ago, there has been a rapid progress of this technology at an unprecedented rate, whereby BERT (...) and related models represent a major reference, also in the legal domain. This article provides the first systematic overview of TLM-based methods for AI-driven problems and tasks in the legal sphere. A major goal is to highlight research advances in this field so as to understand, on the one hand, how the Transformers have contributed to the success of AI in supporting legal processes, and on the other hand, what are the current limitations and opportunities for further research development. (shrink)

Offering a novel and pragmatic perspective, this timely book critically examines the development of a culture of machinist regulation and questions whether this approach is appropriate in an era of rising biological technologies. Adopting an ontological approach, James Griffin considers how current regulatory frameworks favour digital technology and how this may change in the future. Griffin adeptly investigates how regulation can impact the nature of new technologies, especially as biological computing is becoming more commonplace. Chapters provide a wealth of critical (...) analysis, considering cutting-edge technologies such as AI, prosthesis, and biological computing. Griffin outlines a proposed reformative system which focuses on the biological substrate in the creation of cultural works. The book serves to highlight the ever-increasing need for awareness of the importance of biological substrates and for a regulatory system which reflects this. The State of Cultural Biology will be an essential read for academics and students interested in intellectual property law, law and technology, legal philosophy and law's role in society. It will also prove invaluable to policymakers and professionals looking to broaden their knowledge on the regulation of modern technology. (shrink)

This annual edited volume presents an overview of cutting-edge research areas within digital ethics as defined by the Digital Ethics Lab of the University of Oxford. It identifies new challenges and opportunities of influence in setting the research agenda in the field. The 2020 edition of the yearbook presents research on the following topics: governing digital health, visualising governance, the digital afterlife, the possibility of an AI winter, the limits of design theory in philosophy, cyberwarfare, ethics of online behaviour (...) change, governance of AI, trust in AI, and Emotional Self-Awareness as a Digital Literacy. This book appeals to students, researchers and professionals in the field. (shrink)

Herbert Simon’s work presents a curious anomaly to the historian and philosopher trying to understand the development of classic Artificial Intelligence (AI). Simon was one of most influential figures in AI since its birth, and yet it is always with some difficulties that his work can be made to fit within the received canon of AI’s development and goals. In fact, he differed from every other figure in early AI on most counts: in terms of the recognized intellectual heritage of (...) AI, of his own background and training, of the goals he set for his own AI work and the assessment criteria he accepted. I will argue that these differences provide important clues toward a reevaluation of the relationship between Artificial Intelligence and Herbert Simon’s work that may change our current understanding of both. On the one hand, classic Artificial Intelligence (or Complex Information Processing, as Simon preferred to call it for a number of years), provided the tool he needed to pursue a much broader research agenda that strove to encompass human beings in their cognitive, emotional, social, and political dimensions. On the other hand, AI’s curious status as the discipline that straggles the boundaries between engineering, science, and philosophy can be recast as the tool that allowed researchers to pursue philosophy’s old goals with an alternative methodology. From this perspective, Simon’s version of Artificial Intelligence becomes a full-fledged form of ”anti-philosophy” as ambitious and broad-ranging as old-fashioned metaphysics and as revolutionary as the latter in the radical refashioning of its methodology. It follows that a philosophical assessment of AI, at in least in its Simonian incarnation, must be more farreaching than it is usually thought. At the methodological level, it must discuss whether AI’s invention of computer simulation as the tool that overcomes the a-priori/a-posteriori distinction by actually producing the behavior it wants to explain is really adequate to the job at hand.. (shrink)

Can we make machines that think and act like humans or other natural intelligent agents? The answer to this question depends on how we see ourselves and how we see the machines in question. Classical AI and cognitive science had claimed that cognition is computation, and can thus be reproduced on other computing machines, possibly surpassing the abilities of human intelligence. This consensus has now come under threat and the agenda for the philosophy and theory of AI must be set (...) anew, re-defining the relation between AI and Cognitive Science. We can re-claim the original vision of general AI from the technical AI disciplines; we can reject classical cognitive science and replace it with a new theory (e.g. embodied); or we can try to find new ways to approach AI, for example from neuroscience or from systems theory. To do this, we must go back to the basic questions on computing, cognition and ethics for AI. The 30 papers in this volume provide cutting-edge work from leading researchers that define where we stand and where we should go from here. (shrink)

With the progress of artificial intelligence, the digitalization of the lifeworld, and the reduction of the mind to neuronal processes, the human being appears more and more as a product of data and algorithms. Thus, we conceive ourselves “in the image of our machines,” and conversely, we elevate our machines and our brains to new subjects. At the same time, demands for an enhancement of human nature culminate in transhumanist visions of taking human evolution to a new stage. Against this (...) self-reification of the human being, the present book defends a humanism of embodiment: our corporeality, vitality, and embodied freedom are the foundations of a self-determined existence, which uses the new technologies only as means instead of submitting to them. The book offers an array of interventions directed against a reductionist naturalism in various areas of science and society. As an alternative, it offers an embodied and enactive account of the human person: we are neither pure minds nor brains, but primarily embodied, living beings in relation with others. This general concept is applied to issues such as artificial intelligence (AI), transhumanism and enhancement, virtual reality, neuroscience, embodied freedom, psychiatry, and finally to the accelerating dynamics of current society which lead to an increasing disembodiment of our everyday life. The book thus applies cutting-edge concepts of embodiment and enactivism to current scientific, technological, and cultural tendencies that will crucially influence our society’s development in the twenty-first century. (shrink)

Humanity has reached a critical moment. Our world is unsettled and rapidly changing, and we face existential risks over the next century. Various outcomes--good and bad--are possible. Yet our approach to the future is characterized by short-term thinking, polarizing debates, alarmist rhetoric, and pessimism. In this short, exhilarating book, renowned scientist and bestselling author Martin Rees argues that humanity's prospects depend on our taking a very different approach to planning for tomorrow. The future of humanity is bound to the future (...) of science and hinges on how successfully we harness technological advances to address our challenges. If we are to use science to solve our problems while avoiding its dystopian risks, we must think rationally, globally, collectively, and optimistically about the long term. Advances in biotechnology, cybertechnology, robotics, and artificial intelligence--if pursued and applied wisely--could empower us to boost the developing and developed world and overcome the threats humanity faces on Earth, from climate change to nuclear war. At the same time, further advances in space science will allow humans to explore the solar system and beyond with robots and AI. But there is no "Plan B" for Earth--no viable alternative within reach if we do not care for our home planet. Rich with fascinating insights into cutting-edge science and technology, this accessible book will captivate anyone who wants to understand the critical issues that will define the future of humanity on Earth and beyond."-- Provided by publisher. (shrink)

Can we make machines that think and act like humans or other natural intelligent agents? The answer to this question depends on how we see ourselves and how we see the machines in question. Classical AI and cognitive science had claimed that cognition is computation, and can thus be reproduced on other computing machines, possibly surpassing the abilities of human intelligence. This consensus has now come under threat and the agenda for the philosophy and theory of AI must be set (...) anew, re-defining the relation between AI and Cognitive Science. We can re-claim the original vision of general AI from the technical AI disciplines; we can reject classical cognitive science and replace it with a new theory ; or we can try to find new ways to approach AI, for example from neuroscience or from systems theory. To do this, we must go back to the basic questions on computing, cognition and ethics for AI. The 30 papers in this volume provide cutting-edge work from leading researchers that define where we stand and where we should go from here. (shrink)

Intelligence augmentation was one of the original goals of computing. Artificial Intelligence (AI) inherits this project and is at the leading edge of computing today. Computing can be considered an extension of brain and body, with mathematical prowess and logic fundamental to the infrastructure of computing. Multimedia computing—sensing, analyzing, and translating data to and from visual images, animation, sound and music, touch and haptics, as well as smell—is based on our human senses and is now commonplace. We use data (...) visualization and sonification, as well as data mining and analysis, to sort through the complexity and vast volume of data coming from the world inside and around us. It helps us ‘see’ in new ways. We can think of this capacity as a new kind of “digital glasses”. The Internet of Living Things (IOLT) is potentially an even more profound extension of ourselves to the world: a network of electronic devices embedded into objects, but now with subcutaneous, ingestible devices, and embedded sensors that include people and other living things. Like the Internet of Things (IOT), living things are connected; we call those connections “ecology”. As the IOT becomes increasingly synonymous with the IOLT, the question of ethics that is at the centre of aesthetics and the arts will move to the forefront of our experience of and regard for the world in and around us. (shrink)

Get the science facts, not science fiction, on the cutting-edge developments that are already changing the course of our future. Every day, scientists conduct pioneering experiments with the potential to transform how we live. Yet it isn’t every day you hear from the scientists themselves! Now, award–winning author Jim Al–Khalili and his team of top-notch experts explain how today’s earthshaking discoveries will shape our world tomorrow—and beyond. Pull back the curtain on: genomics robotics AI the “Internet of Things” synthetic (...) biology transhumanism interstellar travel colonization of the solar system teleportation and much more And find insight into big–picture questions such as: Will we find a cure to all diseases? The answer to climate change? And will bionics one day turn us into superheroes? The scientists in these pages are interested only in the truth—reality-based and speculation-free. The future they conjure is by turns tantalizing and sobering: There’s plenty to look forward to, but also plenty to dread. And undoubtedly the best way to for us to face tomorrow’s greatest challenges is to learn what the future looks like—today. Praise for What the Future Looks Like “A collection of mind-boggling essays that are just the thing for firing up your brain cells.” —Saga Magazine “The predictions and impacts are global... [and] the book contains far more fascinating information than can be covered in this review.” —Choice “This book is filled with essays from experts offering their informed opinions on what the science and technology of today will look like in the future, from smart materials to artificial intelligence to genetic editing.” —Popular Science “Fun is an understatement. This is a great collection to get the summer book season started.” —Forbes.com “The focus on sincere, factual presentation of current and future possibilities by leading experts is particularly welcome in this era of fake news and anti-science rhetoric.” —Library Journal. (shrink)

In some languages every statement must contain a specification of the type of evidence on which it is based: for example, whether the speaker saw it, or heard it, or inferred it from indirect evidence, or learnt it from someone else. This grammatical reference to information source is called 'evidentiality', and is one of the least described grammatical categories. Evidentiality systems differ in how complex they are: some distinguish just two terms (eyewitness and noneyewitness, or reported and everything else), while (...) others have six or even more terms. Evidentiality is a category in its own right, and not a subcategory of epistemic or some other modality, nor of tense-aspect. Every language has some way of referring to the source of information, but not every language has grammatical evidentiality. In English expressions such as I guess, they say, I hear that, the alleged are not obligatory and do not constitute a grammatical system. Similar expressions in other languages may provide historical sources for evidentials. True evidentials, by contrast, form a grammatical system. In the North Arawak language Tariana an expression such as "the dog bit the man" must be augmented by a grammatical suffix indicating whether the event was seen, or heard, or assumed, or reported. This book provides the first exhaustive cross-linguistic typological study of how languages deal with the marking of information source. Examples are drawn from over 500 languages from all over the world, several of them based on the author's original fieldwork. Professor Aikhenvald also considers the role evidentiality plays in human cognition, and the ways in which evidentiality influences human perception of the world.. This is an important book on an intriguing subject. It will interest anthropologists, cognitive psychologists and philosophers, as well as linguists. (shrink)

Civics and Moral Educationwas implemented as a new moral education programme in Singapore schools in 1992. This paper argues that the underlying theme is that of citizenship training and that new measures are under way to strengthen the capacity of the school system to transmit national values for economic and political socialisation. The motives and motivation for retaining a formal moral education programme have remained strong. A discussion of the structure and content of key modules in Civics and Moral Education (...) shows how curriculum writers have attempted to integrate separate strands of civics and moral education from earlier programmes and present them in a less divisive manner. The paper also assesses the impact of the written civics and moral education programme on teachers and pupils, and the way in which strategies have been used by curriculum agencies to overcome possible obstacles at the curriculum implementation phase. (shrink)

This collection of quotes demonstrates the elegant simplicity of Ai Weiwei's thoughts on key aspects of his art, politics, and life. A master at communicating powerful ideas in astonishingly few words, Ai Weiwei is known for his innovative use of social media to disseminate his views. The book is organized into six categories: freedom of expression; art and activism; government, power, and moral choices; the digital world; history, the historical moment, and the future; and personal reflections. Together, these quotes span (...) some of the most revealing moments of Ai Weiwei's eventful career-from his risky investigation into student deaths in the 2008 Sichuan earthquake to his arbitrary arrest in 2011-providing a window into the mind of one of the world's most electrifying and courageous contemporary artists. Ai Weiwei is one of China's most influential and inspiring figures. Artist, architect, curator, and activist, he has been an outspoken critic of the Chinese government's stance on human rights and democracy. (shrink)

Big data and Machine learning Techniques are reshaping the way in which food safety risk assessment is conducted. The ongoing ‘datafication’ of food safety risk assessment activities and the progressive deployment of probabilistic models in their practices requires a discussion on the advantages and disadvantages of these advances. In particular, the low level of trust in EU food safety risk assessment framework highlighted in 2019 by an EU-funded survey could be exacerbated by novel methods of analysis. The variety of processed (...) data raises unique questions regarding the interplay of multiple regulatory systems alongside food safety legislation. Provisions aiming to preserve the confidentiality of data and protect personal information are juxtaposed to norms prescribing the public disclosure of scientific information. This research is intended to provide guidance for data governance and data ownership issues that unfold from the ongoing transformation of the technical and legal domains of food safety risk assessment. Following the reconstruction of technological advances in data collection and analysis and the description of recent amendments to food safety legislation, emerging concerns are discussed in light of the individual, collective and social implications of the deployment of cutting-edge Big Data collection and analysis techniques. Then, a set of principle-based recommendations is proposed by adapting high-level principles enshrined in institutional documents about Artificial Intelligence to the realm of food safety risk assessment. The proposed set of recommendations adopts Safety, Accountability, Fairness, Explainability, Transparency as core principles (SAFETY), whereas Privacy and data protection are used as a meta-principle. (shrink)

Robotics is currently not only a cutting-edge research area, but is potentially disruptive to all domains of our lives—for better and worse. While legislation is struggling to keep pace with the development of these new artifacts, our intellectual limitations and physical laws seem to present the only hard demarcation lines, when it comes to state-of-the-art R&D. To better understand the possible implications, the paper at hand critically investigates underlying processes and structures of robotics in the context of Heidegger’s and (...) Nishitani’s accounts of science and technology. Furthermore, the analysis draws on Bauman’s theory of modernity in an attempt to assess the potential risk of large-scale robot integration. The paper will highlight undergirding mechanisms and severe challenges imposed upon our socio-cultural lifeworlds by massive robotic integration. Admittedly, presenting a mainly melancholic account, it will, however, also explore the possibility of robotics forcing us to reassess our position and to solve problems, which we seem unable to tackle without facing existential crises. (shrink)