As systems based on opaque Artificial Intelligence (AI) continue to flourish in diverse real-world applications, understanding these black box models has become paramount. In response, Explainable AI (XAI) has emerged as a field of research with practical and ethical benefits across various domains. This paper not only highlights the advancements in XAI and its application in real-world scenarios but also addresses the ongoing challenges within XAI, emphasizing the need for broader perspectives and collaborative efforts. We bring together experts from (...) diverse fields to identify open problems, striving to synchronize research agendas and accelerate XAI in practical applications. By fostering collaborative discussion and interdisciplinary cooperation, we aim to propel XAI forward, contributing to its continued success. Our goal is to put forward a comprehensive proposal for advancing XAI. To achieve this goal, we present a manifesto of 27 open problems categorized into nine categories. These challenges encapsulate the complexities and nuances of XAI and offer a road map for future research. For each problem, we provide promising research directions in the hope of harnessing the collective intelligence of interested stakeholders. (shrink)

This paper explores the theological and philosophical implications of artificial intelligence (AI) and Neuroscience research on the Christian’s notion of the human person. The paschal mystery of Christ is the intuitive foundation of Christian anthropology. In the intellectual history of the Christianity, Platonism and Aristotelianism have been employed to articulate the Christian philosophical anthropology. The Aristotelian systematization has endured to this era. Since the modern period of the Western intellectual history, Aristotelianism has been supplanted by the positive sciences as (...) the standard scientific and philosophical interpretative framework for many. This paper argues that there is need for a new Christian anthropology based on the interpretation of the paschal mystery of Christ that is consistent with contemporary science and philosophy, especially as informed by research in AI and neuroscience. Christian anthropology today ought to be fully aware of the theological and philosophical implications of AI and neuroscience research. This paper denotes this new Christian anthropology as neuro-theological Christian anthropology. (shrink)

This paper discusses two opposing views about the relation between artificial intelligence (AI) and human intelligence: on the one hand, a worry that heavy reliance on AI technologies might make people less intelligent and, on the other, a hope that AI technologies might serve as a form of cognitive enhancement. The worry relates to the notion that if we hand over too many intelligence-requiring tasks to AI technologies, we might end up with fewer opportunities to train our own intelligence. (...) Concerning AI as a potential form of cognitive enhancement, the paper explores two possibilities: (1) AI as extending—and thereby enhancing—people’s minds, and (2) AI as enabling people to behave in artificially intelligent ways. That is, using AI technologies might enable people to behave as if they have been cognitively enhanced. The paper considers such enhancements both on the level of individuals and on the level of groups. (shrink)

This article links three rarely considered dimensions related to the implementation of artificial intelligence (AI)-based technologies in the form of predictive policing and discusses them in relation to liberal democratic societies. The three dimensions are the theoretical embedding and the workings of AI within anomic conditions (1), potential normative disorders emerging from them in the form of thinking errors and discriminatory practices (2) as well as the consequences of these disorders on the psychosocial, and emotional level (3). Against this (...) background, AI-induced anomie is conceptualized as a field of tension that refers to a systematic deterioration of democratic norms that are supposed to create ‘normative orders’, but which, when implemented through AI-supported measures, can reproduce existing discriminations, and establish new kinds of discriminatory relations. In future, these AI-based measures have the potential to lead to opposing normative disorders by emerging in the form of false social norms to an equally false Second Nature. They deprive persons involved of the possibility of individual appropriation of social norms and the specific emotional development associated with it. (shrink)

_Purpose._ The study aims to understand artificial intelligence as a socio-cultural phenomenon and its impact on education, where the spiritual sphere of humanity, moral norms, values, and human cognitive abilities are preserved, transferred as well as reproduced. A new discourse on the interaction of artificial and authentic human intelligence becomes inevitable, which has led to a situation of uncertainty. Changes in the socio-cultural environment under the influence of artificial intelligence increase potential threats to the educational space, which (...) stimulates to find the ways to eliminate them. _Theoretical basis._ Various approaches of classical and postmodern philosophical heritage were taken as a theoretical basis for the research. _The originality_ of the study is in the interpretation of artificial intelligence as a modern form of alienation of essential human characteristics in the socio-cultural context of information technology. The expansion of artificial intelligence raises awareness of the existential threat to the basic socio-cultural, moral and ethical principles of humanism. It is proved that various forms of alienation in the current existing socio-cultural space are typical of our reality, which changes the system of values, moral principles, and social organization of the community. _Conclusions._ In conclusion, it is proved that AI is a natural stage of scientific and technological progress, which reflects its secondary, derivative nature from human (authentic) intelligence. Human intelligence will always have advantages over AI due to its ability to create, communicate socially and culturally, and be emotional. The dilemma of the counterbalance between human and artificial intelligence is perceived mainly at the emotional level of people. The millennial understanding of the primacy of the creator over his creation can traditionally overcome this contradiction. The universality of human thinking is an undeniable advantage of human intelligence and a guarantee of its, i.e. our, priority. (shrink)

Background The use of Artificial Intelligence (AI) has the potential to provide relief in the challenging and often stressful clinical setting for physicians. So far, however, the actual changes in work for physicians remain a prediction for the future, including new demands on the social level of medical practice. Thus, the question of how the requirements for physicians will change due to the implementation of AI is addressed. Methods The question is approached through conceptual considerations based on the potentials (...) that AI already offer and the focus on central normative concepts of trust, explainability, and responsibility which play an important role when implementing AI in everyday clinical practice. Conclusion Interpersonal communication will not disappear upon implementation of AI. Instead, it is much more likely that the exchange between various actors in medical practice will become increasingly important. This adds another level of complexity to practical concepts such as Shared-Decision-Making, which must be addressed in empirical research, including the involvement of AI systems as actors in communication. (shrink)

This short article is a “conversation” in which an android, Mort, replies to Richard Marc Rubin’s android named Sol in “The Robot Sol Explains Laughter to His Android Brethren” (The Philosophy of Humor Yearbook, 2022). There Sol offers an explanation for how androids can laugh--largely a reaction to frustration and unmet expectations: “my account says that laughter is one of four ways of dealing with frustration, difficulties, and insults. It is a way of getting by. If you need to label (...) my conception of humor, you might call it an adjustment theory, or perhaps an accommodation theory” (Rubin 256). Mort is intrigued but has his doubts. Mort contends that synesthesia likely has something to do with how humans develop humor. Perhaps, he considers, human designers crossed the androids' sensory wires, allowing them to be able to smash up concepts that do not otherwise seem to fit together, reconstruct incongruities in a manner that is not nonsensical, express the aha-eureka moment of a serendipitous discovery, and even feel blue when they fail at a given task that we were expected to complete. (shrink)

The recent appearance of generative artificial intelligence (AI) platforms has been seen by many as disruptive for education. In this paper I attempt to locate the source of tension between educational goals and new information technologies including AI. I argue that this tension arises from new conceptions of epistemic agency that are incompatible with educational aims. I describe three competing theories of epistemic agency which I refer to as Makers, Managers, and Inforgs. I contend that educators are correct in (...) maintaining the first of these, which is rooted in the educational theories of Locke and Dewey, as their main educational purpose. Competing theories do not serve the goals of learners, even as they must prepare for life in a very different epistemic environment. (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)

Artificial Intelligence (AI) is increasingly adopted in society, creating numerous opportunities but at the same time posing ethical challenges. Many of these are familiar, such as issues of fairness, responsibility and privacy, but are presented in a new and challenging guise due to our limited ability to steer and predict the outputs of AI systems. This chapter first introduces these ethical challenges, stressing that overviews of values are a good starting point but frequently fail to suffice due to the (...) context sensitivity of ethical challenges. Frequently, additional (ethical) values emerge for specific applications, as e.g. challenges with fraud detection are very different from those around language technologies. Second, methods to tackle these challenges are discussed. Main ethical theories (virtue ethics, consequentialism, and deontology) are shown to provide a starting point, but often lack the details needed for actionable AI Ethics. Instead, mid-level philosophical theories coupled to design-approaches such as Design for Values, together with interdisciplinary working methods, offer the best way forwards. The chapter aims to show how these approaches can lead to an ethics of AI that is actionable and that can be proactively integrated in the design of AI systems. (shrink)

Puritanism may evolve into a technological variant based on norms of delegation of actions and perceptions to artificial intelligence. Instead of training self-control, people may be expected to cede their agency to self-controlled machines. The cost–benefit balance of this machine puritanism may be less aversive to wealthy individualistic democracies than the old puritanism they have abandoned.

Machine-based automation has long been a key factor in the modern era. However, lately, many people have been shocked by artificial intelligence (AI) applications, such as ChatGPT (OpenAI), that can perform tasks previously thought to be human-exclusive. With recent advances in natural language processing (NLP) technologies, AI can generate written content that is similar to human-made products, and this ability has a variety of applications. As the technology of large language models continues to progress by making use of colossal (...) reservoirs of digital information, AI is becoming more capable of recognizing patterns and associations within given contexts, making it especially helpful in assisting with various professional writing tasks [1]. In this paper, we will discuss several key points regarding the current state and future of AI in academia. Furthermore, since in certain aspects, acts can speak louder than words, we will also present some of our hands-on experiences of working with ChatGPT. (shrink)

This article is an update of our previous article in this SGJ journal, titled: On Gödel's Incompleteness Theorem, Artificial Intelligence & Human Mind. We provide some commentary on the latest developments around AI, humanoid robotics, and future scenario. Basically, we argue that a more thoughtful approach to the future is "techno-realism.".

This hands-on guide offers clear explanations of fuzzy logic along with practical uses and detailed examples. Written by an award-winning engineer and experienced author, Fuzzy Logic: Applications in Artificial Intelligence, Big Data, and Machine Learning is aimed at improving competence and skills in students and professionals alike. Inside, you will discover how to apply fuzzy logic and migrate to a new man-machine relationship in the context of pervasive digitization and big data across emerging technologies. The book lays out real-world (...) applications in intelligent energy systems with demand response, smart homes, electrification of transportation, supply chain efficiencies, smart cities, e-commerce, education, healthcare, and decarbonization. (shrink)

This book presents the reader with a comprehensive and structured understanding of the ethics of Artificial Intelligence (AI). It describes the main ethical questions that arise from the use of AI in different areas, as well as the contribution of various academic disciplines such as legal policy, environmental sciences, and philosophy of technology to the study of AI. AI has become ubiquitous and is significantly changing our lives, in many cases, for the better, but it comes with ethical challenges. (...) These challenges include issues with the possibility and consequences of autonomous AI systems, privacy and data protection, the development of a surveillance society, problems with the design of these technologies and inequalities in access to AI technologies. This book offers specialists an instrument to develop a rigorous understanding of the main debates in emerging ethical questions around AI. The book will be of great relevance to experts in applied and technology ethics and to students pursuing degrees in applied ethics and, more specifically, in AI ethics. (shrink)

The present paper looks at one of the most thorough articles on the intelligence of GPT, research conducted by engineers at Microsoft. Although there is a great deal of value in their work, I will argue that, for familiar philosophical reasons, their methodology, ‘Black-box Interpretability’ is wrongheaded. But there is a better way. There is an exciting and emerging discipline of ‘Inner Interpretability’ (also sometimes called ‘White-box Interpretability’) that aims to uncover the internal activations and weights of models in order (...) to understand what they represent and the algorithms they implement. In my view, a crucial mistake in Black-box Interpretability is the failure to appreciate that how processes are carried out matters when it comes to intelligence and understanding. I can’t pretend to have a full story that provides both necessary and sufficient conditions for being intelligent, but I do think that Inner Interpretability dovetails nicely with plausible philosophical views of what intelligence requires. So the conclusion is modest, but the important point in my view is seeing how to get the research on the right track. Towards the end of the paper, I will show how some of the philosophical concepts can be used to further refine how Inner Interpretability is approached, so the paper helps draw out a profitable, future two-way exchange between Philosophers and Computer Scientists. (shrink)

LANGUAGE NOTE | Document text in English; abstract also in Chinese. 腦機介面 (BCIs) 是大腦和電腦無需人工交互即可直接交流的一系列技術。隨著人工智能 (AI) 時代的到來，我們需要更多地關注腦機介面和人工智能的融合所帶來的倫理問題。那麼，與機器一起思考會帶來什麼樣的倫理問題？在本文中，圍繞這一主題，我們將重點關注以下問題：自主性、完整性、身分認同、隱私，以及 作為一種增強的方式，該技術在兒科領域的應用會帶來怎樣的風險和潛在收益。我們的結論是，雖然該技術存在多種令人擔憂的問題，同時也有可能帶來好處，但仍存在很大的不確定性。如果生命倫理學家想在這一領域有所建樹 ，他們就應該做好準備來迎接我們對醫學和醫療保健領域中一些我們視為核心價值的理解的重大轉變。 Brain-Computer Interfaces – BCIs – are a set of technologies with which brains and computers can communicate directly, without the need for manual interaction. As we are witnessing the dawn of an era in which Artificial Intelligence (AI) quite possibly will come to dominate the technological innovation landscape, we are compelled to ask questions about the ethical issues which the convergence of BCIs and (...) AI is poised to bring about. What are the ethics of thinking with machines? In this paper, we explore this question, focusing on some of the main arenas of ethical debate and contention, ranging from autonomy and integrity to identity and privacy, and discuss the risks and potential benefits of the technology in the domains of paediatric populations, and as a means of human enhancement. We conclude that, while there are multiple concerns as well as possibilities for the technology to do good, there are great uncertainties at play. If bioethicists want to stay relevant in this field, they ought to prepare themselves for seismic shift in how we conceptualise much of what we take to be core values in medicine and healthcare. (shrink)

McCarthy and Howard (2023) present a “Non-Domination” approach to supported decision-making, specially to help intellectually and developmentally disabled (IDD) patients rather than “Mental Prosthe...

Artificial Intelligence (AI) must be directed at humane ends. The development of AI has produced great uncertainties of ensuring AI alignment with human values (AI value alignment) through AI operations from design to use. For the purposes of addressing this problem, we adopt the phenomenological theories of material values and technological mediation to be that beginning step. In this paper, we first discuss the AI value alignment from the relevant AI studies. Second, we briefly present what are material values (...) and technological mediation and reflect on the AI value alignment through the lenses of these theories. We conclude that a set of finite human values can be defined and adapted to the stable life tasks that AI systems will be called upon to accomplish. The AI value alignment can also be fostered between designers and users through technological mediation. Upon that foundation, we propose a set of common principles to understand the AI value alignment through phenomenological theories. This paper contributes the unique knowledge of phenomenological theories to the discourse on AI alignment with human values. (shrink)

Highly sophisticated capabilities of artificial intelligence (AI) have skyrocketed its popularity across many industry sectors globally. The public sector is one of these. Many cities around the world are trying to position themselves as leaders of urban innovation through the development and deployment of AI systems. Likewise, increasing numbers of local government agencies are attempting to utilise AI technologies in their operations to deliver policy and generate efficiencies in highly uncertain and complex urban environments. While the popularity of AI (...) is on the rise in urban policy circles, there is limited understanding and lack of empirical studies on the city manager perceptions concerning urban AI systems. Bridging this gap is the rationale of this study. The methodological approach adopted in this study is twofold. First, the study collects data through semi-structured interviews with city managers from Australia and the US. Then, the study analyses the data using the summative content analysis technique with two data analysis software. The analysis identifies the following themes and generates insights into local government services: AI adoption areas, cautionary areas, challenges, effects, impacts, knowledge basis, plans, preparedness, roadblocks, technologies, deployment timeframes, and usefulness. The study findings inform city managers in their efforts to deploy AI in their local government operations, and offer directions for prospective research. (shrink)

The debate over the ethical repercussions of Artificial Intelligence (AI) cannot disregard the “sum total of ideas that bring into evidence a system of ethical reference that justifies that profound dimension of technology as a central element in the attainment of a ‘finalized’ perfection of man”(Galvan 2001). This implies an analysis of the ancient processes that might help to understand the complexities of contemporary society and the new challenges posed to human development. Being at the core of the dichotomy (...) between the human and the machine, biometrics will be central to the analysis carried out in this paper. Its measurement of physiological characteristics and behavioural patterns has politico-philosophical and legal consequences in terms of recognition and personal identity, as the use of artificial intelligence has shown. In information society, customs and traditions, cultural and communication processes, language and the self-determination of the individual have gradually acquired a stretched dimension that has led to a re-definition of the social structures within which the exchange of knowledge and data takes place, with AI-based technological devices playing a key role in such a scenario. The issue of biometric identity becomes highly complex when combined with the potential of digital services, as it is at this level that it shows the large number of interconnections deriving from social and political choices. The benefits of increased interconnection are limited by the risk of intrusion into the (social, personal or private) human sphere, which might pose a threat to both the physical, biological body, with its related freedoms (habeas corpus), and the digital body, in its multiple forms and media representations (habeas data). (shrink)

: Artificial intelligences and robots increasingly mimic human mental powers and intelligent behaviour. However, many authors claim that ascribing human mental powers to them is both conceptually mistaken and morally dangerous. This article defends the view that artificial intelligences can have human-like mental powers, by claiming that both human and artificial minds can be seen as extended minds – along the lines of Chalmers and Clark’s view of mind and cognition. The main idea of this article is (...) that the Extended Mind Model is independently plausible and can easily be extended to artificial intelligences, providing a solid base for concluding that artificial intelligences possess minds. This may warrant viewing them as morally responsible agents. Keywords: Artificial Intelligence; Mind; Moral Responsibility; Extended Cognition Intelligenze artificiali come menti estese. Perché no? Riassunto: Intelligenze artificiali e robot simulano in misura sempre crescente le capacità mentali e i comportamenti intelligenti umani. Molti autori, tuttavia, sostengono che attribuire loro capacità mentali umane sia concettualmente errato e moralmente pericoloso. In questo lavoro si difende l’idea per cui le intelligenze artificiali possano avere capacità mentali simili a quelle umane, sostenendo che menti umane e artificiali possano essere considerate come menti estese – sulla scorta della prospettiva di Chalmers e Clark circa la mente e la cognizione. L’idea principale alla base di questo lavoro è che il Modello della Mente Estesa abbia plausibilità a prescindere e che possa essere facilmente esteso alle intelligenze artificiali, fornendo una base solida per concludere che le intelligenze artificiali possiedano delle menti e si possano considerare come agenti moralmente responsabili. Parole chiave: Intelligenza artificiale; Mente; Responsabilità morale; Conoscenza estesa. (shrink)

Nurses have traditionally been regarded as clinicians that deliver compassionate, safe, and empathetic health care (Nurses again outpace other professions for honesty & ethics, 2018). Caring is a fundamental characteristic, expectation, and moral obligation of the nursing and caregiving professions (Nursing: Scope and standards of practice, American Nurses Association, Silver Spring, MD, 2015). Along with caring, nurses are expected to undertake ever‐expanding duties and complex tasks. In part because of the growing physical, intellectual and emotional demandingness, of nursing as well (...) as technological advances, artificial intelligence (AI) and AI care robots are rapidly changing the healthcare landscape. As technology becomes more advanced, efficient, and economical, opportunities and pressure to introduce AI into nursing care will only increase. In the first part of the article, we review recent and existing applications of AI in nursing and speculate on future use. Second, situate our project within the recent literature on the ethics of nursing and AI. Third, we explore three dominant theories of caring and the two paradigmatic expressions of caring (touch and presence) and conclude that AI—at least for the foreseeable future—is incapable of caring in the sense central to nursing and caregiving ethics. We conclude that for AI to be implemented ethically, it cannot transgress the core values of nursing, usurp aspects of caring that can only meaningfully be carried out by human beings, and it must support, open, or improve opportunities for nurses to provide the uniquely human aspects of care. (shrink)

Artificial intelligence (AI) based clinical decision support systems (CDSS) are becoming ever more widespread in healthcare and could play an important role in diagnostic and treatment processes. For this reason, AI‐based CDSS has an impact on the doctor–patient relationship, shaping their decisions with its suggestions. We may be on the verge of a paradigm shift, where the doctor–patient relationship is no longer a dual relationship, but a triad. This paper analyses the role of AI‐based CDSS for shared decision‐making to (...) better comprehend its promises and associated ethical issues. Moreover, it investigates how certain AI implementations may instead foster the inappropriate paradigm of paternalism. Understanding how AI relates to doctors and influences doctor–patient communication is essential to promote more ethical medical practice. Both doctors' and patients' autonomy need to be considered in the light of AI. (shrink)

Artificial intelligence (AI) national strategies provide countries with a framework for the development and implementation of AI technologies. Sixty countries worldwide published their AI national strategies. The majority of these countries with more than 70% are developed countries. The approach of AI national strategies differentiates between developed and developing countries in several aspects including scientific research, education, talent development, and ethics. This paper examined AI readiness assessment in a developing country (Palestine) to help develop and identify the main pillars (...) of the AI national strategy. AI readiness assessment was applied across education, entrepreneurship, government, and research and development sectors in Palestine (case of a developing country). In addition, it examined the legal framework and whether it is coping with trending technologies. The results revealed that Palestinians have low awareness of AI. Moreover, AI is barely used across several sectors and the legal framework is not coping with trending technologies. The results helped develop and identify the following five main pillars that Palestine’s AI national strategy should focus on: AI for Government, AI for Development, AI for Capacity Building in the private, public and technical and governmental sectors, AI and Legal Framework, and international Activities. (shrink)

It has become a truism that the ethics of artificial intelligence (AI) is necessary and must help guide technological developments. Numerous ethical guidelines have emerged from academia, industry, government and civil society in recent years. While they provide a basis for discussion on appropriate regulation of AI, it is not always clear how these ethical guidelines were developed, and by whom. Using content analysis, we surveyed a sample of the major documents (_n_ = 47) and analyzed the accessible information (...) regarding their methodology and stakeholder engagement. Surprisingly, only 38% report some form of stakeholder engagement (with 9% involving citizens) and most do not report their methodology for developing normative insights (15%). Our results show that documents with stakeholder engagement develop more comprehensive ethical guidance with greater applicability, and that the private sector is least likely to engage stakeholders. We argue that the current trend for enunciating AI ethical guidance not only poses widely discussed challenges of applicability in practice, but also of transparent development (as it rather behaves as a black box) and of active engagement of diversified, independent and trustworthy stakeholders. While most of these documents consider people and the common good as central to their telos, engagement with the general public is significantly lacking. As AI ethics moves from the initial race for enunciating general principles to more sustainable, inclusive and practical guidance, stakeholder engagement and citizen involvement will need to be embedded into the framing of ethical and societal expectations towards this technology. (shrink)

The enduring innovations in artificial intelligence and robotics offer the promised capacity of computer consciousness, sentience and rationality. The development of these advanced technologies have been considered to merit rights, however these can only be ascribed in the context of commensurate responsibilities and duties. This represents the discernable next-step for evolution in this field. Addressing these needs requires attention to the philosophical perspectives of moral responsibility for artificial intelligence and robotics. A contrast to the moral status of animals (...) may be considered. At a practical level, the attainment of responsibilities by artificial intelligence and robots can benefit from the established responsibilities and duties of human society, as their subsistence exists within this domain. These responsibilities can be further interpreted and crystalized through legal principles, many of which have been conserved from ancient Roman law. The ultimate and unified goal of stipulating these responsibilities resides through the advancement of mankind and the enduring preservation of the core tenets of humanity. (shrink)

In March 2016, DeepMind's computer programme AlphaGo surprised the world by defeating the world‐champion Go player, Lee Sedol. AlphaGo exhibits a novel, surprising and valuable style of play and has been recognised as “creative” by the artificial intelligence (AI) and Go communities. This article examines whether AlphaGo engages in creative problem solving according to the standards of comparative psychology. I argue that AlphaGo displays one important aspect of creative problem solving (namely mental scenario building in the form of Monte (...) Carlo tree search), while lacking another (domain generality). This analysis has consequences for how we think about creativity in humans and AI. (shrink)

Review of Mitchell, Melanie. Artificial Intelligence: A guide for thinking humans. New York: Macmillan, 2019.

The difficulty of explaining the outputs of artificial intelligence (AI) models and what has led to them is a notorious ethical problem wherever these technologies are applied, including in the medical domain, and one that has no obvious solution. This paper examines the proposal, made by Luciano Floridi and colleagues, to include a new ‘principle of explicability’ alongside the traditional four principles of bioethics that make up the theory of ‘principlism’. It specifically responds to a recent set of criticisms (...) that challenge the supposed need for such a principle to perform an enabling role in relation to the traditional four principles and therefore suggest that these four are sufficient without the addition of explicability. The paper challenges the critics’ premise that explicability cannot be an ethical principle like the classic four because it is explicitly subordinate to them. It argues instead that principlism in its original formulation locates the justification for ethical principles in a midlevel position such that they mediate between the most general moral norms and the contextual requirements of medicine. This conception of an ethical principle then provides a mold for an approach to explicability on which it functions as an enabling principle that unifies technical/epistemic demands on AI and the requirements of high-level ethical theories. The paper finishes by anticipating an objection that decision-making by clinicians and AI fall equally, but implausibly, under the principle of explicability’s scope, which it rejects on the grounds that human decisions, unlike AI’s, can be explained by their social environments. (shrink)

Artificial intelligence (AI) profoundly influences a number of societal structures today, including religious dynamics. Using Bernard Lonergan’s critical realism as a lens, this article investigates the intersections of AI and religious traditions in their shared pursuit of the common good. Beginning with Lonergan’s principle that humans construct their understanding through cognitive processes, we examine how AI-mediated realities align with or challenge traditional religious tenets. By delving into specific cases, we spotlight AI’s role in reshaping religious symbols, rituals, and even (...) creating novel spiritual meanings. Using Lonergan’s insights on the balance between subjectivity and objectivity, I analyze AI’s potential to both create new sacred spaces and challenge religious orthodoxy. The crux of the discussion centers on the negotiation between religious values and technological innovation, assessing how AI can bolster religious life while maintaining its core essence. Ultimately, this article underscores the importance of the common good in the age of AI-driven religious evolution. (shrink)

The world’s current model for economic development is unsustainable. It encourages high levels of resource extraction, consumption, and waste that undermine positive environmental outcomes. Transitioning to a circular economy (CE) model of development has been proposed as a sustainable alternative. Artificial intelligence (AI) is a crucial enabler for CE. It can aid in designing robust and sustainable products, facilitate new circular business models, and support the broader infrastructures needed to scale circularity. However, to date, considerations of the ethical implications (...) of using AI to achieve a transition to CE have been limited. This article addresses this gap. It outlines how AI is and can be used to transition towards CE, analyzes the ethical risks associated with using AI for this purpose, and supports some recommendations to policymakers and industry on how to minimise these risks. (shrink)

The development of the mind follows the path of biological evolution towards the accumulation and transmission of information with increasing efficiency. In addition to the cognitive constants of speech (Solntsev, 1974), which greatly improved the transmission of information, people have created computing devices, from the abacus to the quantum computer. The capabilities of computers classified as artificial intelligence are developing at a rapid pace. However, at the present stage, artificial intelligence (AI) lacks an emotion module, and this makes (...) AI fundamentally different from human intelligence, since the life of the mind in humans cannot be separated from their feelings (Damasio, 2010; Panksepp, 1997). Consciousness itself is formed through the sensory and motor systems, that is, it is embodied (Foglia & Wilson, 2013), which means that our mental life is inseparable from our sensory motor experience (Wellsby & Pexman, 2014). Evolutionarily, our minds rely on ancient survival mechanisms that influence our decisions and choices. Hence, for example, the question whether the choice of Artificial Intelligence will always be favorable for humanity. (shrink)

Current AI policy recommendations differ on what the risks to human autonomy are. To systematically address risks to autonomy, we need to confront the complexity of the concept itself and adapt governance solutions accordingly.

Some recent developments in Artificial Intelligence—especially the use of machine learning systems, trained on big data sets and deployed in socially significant and ethically weighty contexts—have led to a number of calls for “transparency”. This paper explores the epistemological and ethical dimensions of that concept, as well as surveying and taxonomising the variety of ways in which it has been invoked in recent discussions. Whilst “outward” forms of transparency may be straightforwardly achieved, what I call “functional” transparency about the (...) inner workings of a system is, in many cases, much harder to attain. In those situations, I argue that contestability may be a possible, acceptable, and useful alternative so that even if we cannot understand how a system came up with a particular output, we at least have the means to challenge it. (shrink)

Artificial Intelligence and Scientific Method examines the remarkable advances made in the field of AI over the past twenty years, discussing their profound implications for philosophy. Taking a clear, non-technical approach, Donald Gillies shows how current views on scientific method are challenged by this recent research, and suggests a new framework for the study of logic. Finally, he draws on work by such seminal thinkers as Bacon, Gdel, Popper, Penrose, and Lucas, to address the hotly-contested question of whether computers (...) might become intellectually superior to human beings. (shrink)

Ethically significant consequences of artificially intelligent artifacts will stem from their effects on existing social relations. Artifacts will serve in a variety of socially important roles—as personal companions, in the service of elderly and infirm people, in commercial, educational, and other socially sensitive contexts. The inevitable disruptions that these technologies will cause to social norms, institutions, and communities warrant careful consideration. As we begin to assess these effects, reflection on degrees and kinds of social agency will be required to make (...) properly informed decisions concerning the deployment of artificially intelligent artifacts in important settings. The social agency of these systems is unlike a human social agency, and this paper provides a methodological framework that is more suited for inquiry into artificial social agents than conventional philosophical treatments of the concept of agency. Separate aspects and dimensions of agency can be studied without assuming that agency must always look like adult human agency. This revised approach to the agency of artifacts is conducive to progress in the topics studied by AI ethics. (shrink)

Whether copyrights should exist in content generated by an artificial intelligence is a frequently discussed issue in the legal literature. Most of the discussion focuses on economic rights, whereas the relationship of artificial intelligence and moral rights remains relatively obscure. However, as moral rights traditionally aim at protecting the author’s “personal sphere”, the question whether the law should recognize such protection in the content produced by machines is pressing; this is especially true considering that artificial intelligence is (...) continuously further developed and increasingly hard to comprehend for human beings. This paper first provides the background on the protection of moral rights under existing international, U.S. and European copyright laws. On this basis, the paper then proceeds to highlight special issues in connection with moral rights and content produced by artificial intelligence, in particular whether an artificial intelligence itself, the creator or users of an artificial intelligence should be considered as owners of moral rights. Finally, the present research discusses possible future solutions, in particular alternative forms of attribution rights or the introduction of related rights. (shrink)

Artificial Intelligence Applications in Higher Education offers direct examples of how artificial intelligence systems can be applied in today's higher education contexts. As use of AI rapidly advances within colleges and universities worldwide, there is a pressing need to showcase the challenges, opportunities, and ethical considerations inherent in deploying these advanced computational tools. This book highlights the multifaceted roles of AI across teaching and learning, institutional administration, student data management, and beyond. Its collected case studies furnish actionable insights (...) into enhancing academic institutions and addressing diverse learning priorities such as motivation, engagement, feedback, and achievement goals. This valuable reference for researchers, designers, administrators, teaching faculty, and graduate students across various university programs offers fresh perspectives on generative AI, adaptive learning, intelligent tutoring systems, chatbots, predictive technologies, remote learning, and more. (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)

Increasing concerns have been raised regarding artificial intelligence (AI) bias, and in response, efforts have been made to pursue AI fairness. In this paper, we argue that the idea of structural injustice serves as a helpful framework for clarifying the ethical concerns surrounding AI bias—including the nature of its moral problem and the responsibility for addressing it—and reconceptualizing the approach to pursuing AI fairness. Using AI in healthcare as a case study, we argue that AI bias is a form (...) of structural injustice that exists when AI systems interact with other social factors to exacerbate existing social inequalities, making some groups of people more vulnerable to undeserved burdens while conferring unearned benefits to others. The goal of AI fairness, understood this way, is about pursuing a more just social structure with the development and usage of AI systems when appropriate. We further argue that all participating agents in the unjust social structure associated with AI bias bear a shared responsibility to join collective action with the goal of reforming the social structure, and we provide a list of practical recommendations for agents in various social positions to contribute to this collective action. (shrink)

Artificially intelligent systems (AISs) are being created by software developing companies (SDCs) to influence clinical decision‐making. Historically, clinicians have led healthcare decision‐making, and the introduction of AISs makes SDCs novel actors in the clinical decision‐making space. Although these AISs are intended to influence a clinician's decision‐making, SDCs have been clear that clinicians are in fact the final decision‐makers in clinical care, and that AISs can only inform their decisions. As such, the default position is that clinicians should hold responsibility for (...) the outcomes of the use of AISs. This is not the case when an AIS has influenced a clinician's judgement and their subsequent decision. In this paper, we argue that this is an imbalanced and unjust position, and that careful thought needs to go into how personal moral responsibility for the use of AISs in clinical decision‐making should be attributed. This paper employs and examines the difference between prospective and retrospective responsibility and considers foreseeability as key in determining how personal moral responsibility can be justly attributed. This leads us to the view that moral responsibility for the outcomes of using AISs in healthcare ought to be shared by the clinical users and SDCs. (shrink)

Under what circumstances if ever ought we to grant that Artificial Intelligences (AI) are persons? The question of whether AI could have the high degree of moral status that is attributed to human persons has received little attention. What little work there is employs western conceptions of personhood, while non-western approaches are neglected. In this article, I discuss African conceptions of personhood and their implications for the possibility of AI persons. I focus on an African account of personhood that (...) is prima facie inimical to the idea that AI could ever be ‘persons’ in the sense typically attributed to humans. I argue that despite its apparent anthropocentrism, this African account could admit AI as persons. (shrink)

The development of the systems of artificial intelligence (AI) and digital transformation in general lead to the formation of multitude of autonomous agents of artificial and mixed genealogy, as well as to complex structures in the information and regulatory environment with many opportunities and pathologies and a growing level of uncertainty in making managerial decisions. The situation is complicated by the continuing plurality of understanding of the essence of AI systems. The modern expanded understanding of AI goes back (...) to ideas formulated more than 100 years ago. In official national policy documents on the development of AI, working definitions of AI are preferred. The current stage of AI systems life cycle can be assessed as the completion of the initial period in the development of systems associated with weak AI. The ability of artificial systems to realize themselves as a separate person becomes one of the serious scientific and practical challenges. Attention to the issues of the ethics of AIS indicates the expansion of the diversity of its forms and the beginning of the work in the field of goal-setting. New moral and ethical problems also arise in connection with the possibility of the creation of genuine conscious subjects in the foreseeable future. There is an increasing phenomenon of degradation of natural intelligence. It is required to take into account the issue of the heterogeneity of data generated by humans, electronic sensors and network devices in the dynamic complex environments of the digital economy, the issue of the complexity of the process of co-evolution of AI systems, collective and individual natural consciousness. A special area of opportunities and risks is the development of neurotechnologies. The object of control is digital twins, through which there can be manipulation of real attitudes, preferences, and behavior of individuals. As a result, there are the development of technological capabilities that provoke destructive phenomena as well as the formation of a new class of mass addictions. (shrink)

This book is a call to expand and diversify our approach to the study of the human mind in relation to the Theory of Mind. It proposes that it is necessary to combine cross-disciplinary methods to arrive at a more complete understanding of how our minds work. Seeking to expand the discussion surrounding the Theory of Mind beyond the field of psychology, and its focus on our capacity to ascribe mental states to other people, this volume collects evidence and research (...) to point to a more holistic understanding of our own minds, the minds of others, behavior, language, and reasoning. This book therefore illuminates the conceptual intricacy underlying the Theory of Mind. It posits that a wide scope is necessary to make a breakthrough in scientific research towards a full understanding of the nature, function, and development of our capacity to converge on biological processes of the brain towards consciousness, emotion, awareness, and cognition. The volume presents methods, results, critiques, and models intended to provoke debates in various academic disciplines. It is of interest to scholars working in psychology, neuroscience, philosophy of mind, and artificial intelligence. (shrink)

In this article the central philosophical issues concerning human-level artificial intelligence (AI) are presented. AI largely changed direction in the 1980s and 1990s, concentrating on building domain-specific systems and on sub-goals such as self-organization, self-repair, and reliability. Computer scientists aimed to construct intelligence amplifiers for human beings, rather than imitation humans. Turing based his test on a computer-imitates-human game, describing three versions of this game in 1948, 1950, and 1952. The famous version appears in a 1950 article in Mind, (...) ‘Computing Machinery and Intelligence’ (Turing 1950). The interpretation of Turing's test is that it provides an operational definition of intelligence (or thinking) in machines, in terms of behavior. ‘Intelligent Machinery’ sets out the thesis that whether an entity is intelligent is determined in part by our responses to the entity's behavior. Wittgenstein frequently employed the idea of a human being acting like a reliable machine. A ‘living reading-machine’ is a human being or other creature that is given written signs, for example Chinese characters, arithmetical symbols, logical symbols, or musical notation, and who produces text spoken aloud, solutions to arithmetical problems, and proofs of logical theorems. Wittgenstein mentions that an entity that manipulates symbols genuinely reads only if he or she has a particular history, involving learning and training, and participates in a social environment that includes normative constraints and further uses of the symbols. (shrink)

Jecker et al critically analysed the predominant focus on existential risk (X-Risk) in artificial intelligence (AI) ethics, advocating for a balanced communication of AI’s risks and benefits and urging serious consideration of other urgent ethical issues alongside X-Risk.1 Building on this analysis, we argue for the necessity of acknowledging the unique attention-grabbing attributes of X-Risk and leveraging these traits to foster a comprehensive focus on AI ethics. First, we need to consider a discontinuous situation that is overlooked in the (...) article by Jecker et al. This discontinuity refers to the phenomenon where X-Risk is perceived as dominating the discourse, yet contrary to expectations, it does not lead to a significant allocation of social resources for specific risk management and practical initiatives. In both the specific realm of ethical AI initiatives and the broader scope of AI risk management, the responses to X-Risk do not have the advantage of prioritising the allocation of resources over other related risks.2 This discrepancy suggests that, in terms of actual social resource allocation, X-Risks do not receive commensurate resources relative to the attention they attract. Unlike other types of risks, X-Risk is perceived as a distant threat, which does not correspond with actual initiatives in terms of media exposure. Despite the prominence of the longtermism view in various media and public discourse, the X-Risk of AI often serves merely as a cautionary note or opinion about the current situation. This suggests that concerns about an AI-driven catastrophe have not been effectively translated into practical initiatives. The gap between the attention drawn and …. (shrink)