This essay introduces this special issue on virtue ethics in relation to military AI. It describes the current situation of military AI ethics as following that of AI ethics in general, caught between consequentialism and deontology. Virtue ethics serves as an alternative that can address some of the weaknesses of these dominant forms of ethics. The essay describes how the articles in the issue exemplify the value of virtue-related approaches for these questions, before ending with thoughts for further research.

One of the most common contemporary approaches for developing an ethics of artificial intelligence (AI) involves elaborating guiding principles. This essay explores the limitations of this approach, using the history of bioethics as a comparative case. The examples of bioethics and recent AI ethics suggest that principles are difficult to implement in everyday practice, fail to direct individual action, and can frequently result in a pure proceduralism. The essay encourages an additional attention to virtue, which forms the (...) dispositions of actors, directs them to valued ends, and encourages right action in particular situation to complement principles. Practices and professions like medicine or warfighting that already have rich traditions of reflection on virtue ethics will be especially fruitful fields for developing an AI ethics of virtue. (shrink)

Artificial intelligence is developing rapidly. There are technologies available that fulfil several tasks better than humans can and even behave like humans to some extent. Thus, the situation prompts the question whether AI should be granted legal person- and/or agenthood? There have been similar situations in history where the legal status of slaves or indigenous peoples was discussed. Still, in those historical questions, the subjects under study were always natural persons, i.e., they were living beings belonging to (...) the species Homo sapiens. We analyse the situation from moral-ethical and practical perspectives. The final conclusion is that the currently existing AIs are still so far removed from humans that there is simply no need to think seriously about legal person- or agenthood. Doing so would mean imposing obligations on the AI to follow. This, in turn, would mean that certain rights in relation to those obligations would have to be granted as well. By all evidence, this is something that humans are not ready to do yet and might never get that far. (shrink)

Our fascination with artificial intelligence (AI), robots and sentient machines has a long history, and references to such humanoids are present even in ancient myths and folklore. The advancements in digital and computational technology have turned this fascination into apprehension, with the machines often being depicted as a binary to the human. However, the recent domains of academic enquiry such as transhumanism and posthumanism have produced many a literature in the genre of science fiction (SF) that endeavours (...) to alter this antagonistic notion of AI. In his novel Klara and the Sun, Kazuo Ishiguro explores this notion of AI as a caring machine capable of nursing an ailing young girl back to health. Through this portrayal of AI as a sentient being capable of empathy and cognition, Ishiguro is attempting to usher in a new perception of AI: a posthuman perception that challenges the conventional notions of AI as a machine devoid of emotions. The novel further expands on the idea of self, soul and human consciousness and ponders on the question, what makes humans human, and if it is possible to imbibe these qualities onto an AI. Owing to the novelty of this notion, an unexplored avenue that deserves further exploration, this paper examines the plausibility of this new notion of AI through a careful exegesis of the novel. The paper also attempts to chart the impact of SF in society and culture. The study reveals a positive shift in perception towards AI, and there seems to be much scope for interdisciplinary and transdisciplinary research. (shrink)

The following paper presents both a historical and personal account of the societal and ethical issues arising in the development of artificial intelligence, tracking, where I was involved, the issues from the nineteen seventies onward. My own involvement in the AI narrative begins with the early discussions around whether machines can think. These first discussions, in time, evolved secondly, with the rise of the internet in the nineties, into perceptions of AI as distributed intelligence, addressing its impact (...) on social structures including basic ethical issues arising in daily life. Thirdly, in the sweeping application of AI to all kinds of societal goals and contexts, the awareness that all natural and artificial things might be digitally connected with each other and to human agents led my further involvement in the AI narrative. Tracing this evolution from start to finish, I conclude my own narrative in the history of AI by presenting some of the future challenges for the development and use of artificial intelligences. Through the application of recent research in academia, scientific associations and political bodies, I address the possibilities for the good life, both with and without artificial intelligences. (shrink)

We are obsessed with self-improvement; it’s a billion-dollar industry. But apps, workshops, speakers, retreats, and life hacks have not made us happier. Obsessed with the endless task of perfecting ourselves, we have become restless, anxious, and desperate. We are improving ourselves to death. The culture of self-improvement stems from philosophical classics, perfectionist religions, and a ruthless strain of capitalism—but today, new technologies shape what it means to improve the self. The old humanist culture has given way to artificial (...) class='Hi'>intelligence, social media, and big data: powerful tools that do not only inform us but also measure, compare, and perhaps change us forever. This book shows how self-improvement culture became so toxic—and why we need both a new concept of the self and a mission of social change in order to escape it. Mark Coeckelbergh delves into the history of the ideas that shaped this culture, critically analyzes the role of technology, and explores surprising paths out of the self-improvement trap. Digital detox is no longer a viable option and advice based on ancient wisdom sounds like yet more self-help memes: The only way out is to transform our social and technological environment. Coeckelbergh advocates new “narrative technologies” that help us tell different and better stories about ourselves. However, he cautions, there is no shortcut that avoids the ancient philosophical quest to know yourself, or the obligation to cultivate the good life and the good society. (shrink)

This article argued the following points. Firstly, the challenge posed by artificial intelligence (AI) to the essence of humanity is serious. Secondly, it is important to analyse the external context and internal dynamics of the history of interaction between knowledge and power. Thirdly, it is necessary to trace the intellectual history of humanity becoming god-like. Finally, by combining Martin Luther’s anthropology with insights from social science and philosophical theology, this article advocated for guiding human beings to (...) use their capabilities for good rather than evil through ethical and legal constraints. Efforts in Chinese context should be made to resolve the conflict between humanity’s pursuit of omnipotence and its failure to develop towards complete goodness, so as to avoid catastrophic consequences for humanity.Contribution: The present article’s special contribution was the theological reflection referring to AI’s challenges to the essence of humanity from Luther’s anthropology in Chinese context. The conflict between omnipotence and omnibenevolence has been highlighted as the key problem which human beings need to solve in the face of AI’s challenge. (shrink)

As artificial intelligence (AI) systems continue their rapid advancement, a framework for contextualising the major transitional phases in the development of machine intellect becomes increasingly vital. This paper proposes a novel chronological classification scheme to characterise the key temporal stages in AI evolution. The Prenoëtic era, spanning all of history prior to the year 2020, is defined as the preliminary phase before substantive artificial intellect manifestations. The Protonoëtic period, which humanity has recently entered, denotes the initial (...) emergence of advanced foundation models exceeding human capacities within specialised domains. The forthcoming Mesonoëtic epoch is anticipated to commence with the advent of Artificial General Intelligence (AGI), potentially facilitated by quantum computing capabilities. Ultimately, the Kainonoëtic age is posited to begin upon the rise of superintelligent systems, likely catalysed by an AGI undergoing recursive self-improvement. This novel period taxonomy provides a structured conceptualisation for the key milestones in the evolution towards advanced artificial intellect. This classification framework offers significant value across various disciplines, researchers and stakeholders in the AI landscape, by providing a clearly defined chronological nomenclature. AI policy-makers and regulators will find it instrumental in crafting stage-appropriate policy and legal interventions. Scientists and academics will benefit from a standardised terminology in the approach to AI periodisation, facilitating unambiguous communication and collaborative research. Finally, this proposed taxonomy can serve as an accessible tool for public understanding, offering a clearer roadmap of AI development that can inform open discourse and decision-making. (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 explores and ultimately affirms the surprising claim that artificial intelligence (AI) can become part of the person, in a robust sense, and examines three ethical and legal implications. The argument is based on a rich, legally inspired conception of persons as free and independent rightholders and objects of heightened protection, but it is construed so broadly that it should also apply to mainstream philosophical conceptions of personhood. The claim is exemplified by a specific technology, devices that (...) connect human brains with computers and operate by AI-algorithms. Under philosophically reasonable and empirically realistic conditions, these devices and the AI running them become parts of the person, in the same way as arms, hearts, or mental capacities are. This transformation shall be called empersonification. It has normative and especially legal consequences because people have broader and stronger duties regarding other persons (and parts of them) than regarding things. Three consequences with practical implications are: (i) AI-devices cease to exist as independent legal entities and come to enjoy the special legal protection of persons; (ii) therefore, third parties such as manufacturers or authors of software lose (intellectual) property rights in device and software; (iii) persons become responsible for the outputs of the empersonified AI-devices to the same degree that they are for desires or intentions arising from the depths of their unconscious. More generally, empersonification marks a new step in the long history of human–machine interaction that deserves critical ethical reflection and calls for a stronger value-aligned development of these technologies. (shrink)

This article contributes to the philosophical inquiry of Artificial Intelligence (AI) by reframing the question “Where is the intelligence of Artificial Intelligence?” into “Where does AI intelligently operate?”. This rephrasing challenges our understanding of AI’s role in social practices and its integration into the human experience. Central to this discourse is the concept of the ‘cybork’ (a portmanteau of ‘cyborg’ and ‘work’), which symbolizes not just a physical entity but a dynamic system of actions and (...) interactions within a socio-technical landscape: work accomplished with machines. In this framework, intelligence in AI lies not in any function of isolated systems, but rather in the situated context of their use within collective and meaningful practices that give technology its sense and direction. Conversely, technology both enables and shapes these practices to the extent that distinguishing between the two can seem unnecessary, or even detrimental, to the optimal design of and for work practices. The cybork embodies this integration and entanglement, transcending the traditional boundaries between individuals and collectives, entities and actions. It reveals the inseparability and co-dependence of humans and technology, where technological artifacts become extensions of human capabilities, embody collective human history and development, and serve as both products and participants in societal practices, fundamentally shaping our interaction with the world. (shrink)

Many scholars make a very clear distinction between intelligence and consciousness. Let’s take one of the most famous today, Israeli history Professor, Yuval Noah Harari, the author of Sapiens and Homo Deus. In his 2018 book, 21 lessons for the twenty-first century, he writes that, “intelligence and consciousness are very different things. Intelligence is the ability to solve problems. Consciousness is the ability to feel things such as pain, joy, love, and anger.”.

The future rests under the sign of technology. Given the prevalence of technological neutrality and inevitabilism, most conceptualizations of the future tend to ignore moral problems. In this paper we argue that every choice about future technologies is a moral choice and even the most technology-dominated scenarios of the future are, in fact, moral provocations we have to imagine solutions to. We begin by explaining the intricate connection between morality and the future. After a short excursion into the history (...) of Artificial Intelligence, we analyse two possible scenarios, which show that building the future with technology is, first and foremost, a moral endeavor. (shrink)

Applications of artificial intelligence/machine learning in health care are dynamic and rapidly growing. One strategy for anticipating and addressing ethical challenges related to AI/ml for health care is patient and public involvement in the design of those technologies – often referred to as ‘co-design’. Co-design has a diverse intellectual and practical history, however, and has been conceptualized in many different ways. Moreover, AI/ml introduces challenges to co-design that are often underappreciated. Informed by perspectives from critical data studies (...) and critical digital health studies, we review the research literature on involvement in health care, and involvement in design, and examine the extent to which co-design as commonly conceptualized is capable of addressing the range of normative issues raised by AI/ml for health care. We suggest that AI/ml technologies have amplified and modified existing challenges related to patient and public involvement, and created entirely new challenges. We outline three pitfalls associated with co-design for ethical AI/ml for health care and conclude with suggestions for addressing these practical and conceptual challenges. (shrink)

AI-powered technology can both promote accuracy and hide the standards of measurement and circulation of information. It can also produce models that are opaque and hard to access. As such, the new paradigm of AI asks to pounder about societal values and sets of priorities we want to promote, especially as these technologies are further deployed in times of warfare. The systemic tracking of people’s life and the opaqueness of the models designate a new paradigm in the formation of truth, (...) as censorship is enabled on a new scale. (shrink)

This paper considers recent experiments in art and artificial intelligence that crystallize around training algorithms to generate artworks based on datasets derived from the Western art historical canon. Over the last decade, a shift towards the rejection of canonicity has begun to take shape in art historical discourse. At the same time, algorithmically enabled practices in the US and Europe have emerged that entrench the Western canon as a locus and guarantor of aesthetic value. Operating within the epistemic (...) framework of a “view from nowhere,” this tendency in generative art inherits the coloniality of both art history and artificial intelligence. Producing “art histories from nowhere,” this tendency conflates the conceptual category of visual art with the histories of Western cultural production. It reproduces a set of aesthetic values that entrench the mythology of the artist-genius and his imputed whiteness and masculinity; the extolment of innovation and novelty as self-evident virtues; disembodied Cartesian models of knowing and sensing; and the erasure of contributions that have been occluded from canonical visibility. As we encounter systems trained on particular visions of art history and of the artist, how might we remain attentive to the specific lens through which they are taught to see? This essay addresses that question by bringing the coloniality of recent experiments into view, bridging data feminisms and decolonial studies to formulate alternative visions of encounters between art and AI. (shrink)

The inquiry into the moral status of artificial intelligence (AI) is leading to prolific theoretical discussions. A new entity that does not share the material substrate of human beings begins to show signs of a number of properties that are nuclear to the understanding of moral agency. It makes us wonder whether the properties we associate with moral status need to be revised or whether the new artificial entities deserve to enter within the circle of moral consideration. (...) This raises the foreboding that we are at the gates of an anthropological crisis: the properties bound to moral agency have been exclusively possessed in the past by human beings and have shaped the very definition of being human. In this article, I will argue that AI does not lead us to an anthropological crisis and that, if we adhere to the history and philosophy of technology, we will notice that the debate on the moral status of AI uncritically starts from an anthropology of properties and loses sight of the relational dimension of technology. First, I will articulate three criteria for analyzing different anthropological views in philosophy of technology. Second, I will propose six anthropological models: traditional, industrial, phenomenological, postphenomenological, symmetrical, and cyborg. Third, I will show how the emergence of AI breaks with the dynamics of increased relationality in the history and philosophy of technology. I will argue that this aspect is central to debates about the moral status of AI, since it sheds light on an aspect of moral consideration that has been obscured. Finally, I will reject entirely relational approaches to moral status and propose two hybrid possibilities for rethinking it. (shrink)

Artificial intelligence (AI) technologies are increasingly creeping into the work sphere, thereby gradually questioning and/or disturbing the long-established moral concepts and norms communities have been using to define what makes work good. Each community, and Muslims make no exception in this regard, has to revisit their moral world to provide well-thought frameworks that can engage with the challenging ethical questions raised by the new phenomenon of AI-mediated work. For a systematic analysis of the broad topic of AI-mediated work (...) ethics from an Islamic perspective, this article focuses on presenting an accessible overview of the “moral world” of work in the Islamic tradition. Three main components of this moral world were selected due to their relevance to the AI context, namely (1) Work is inherently good for humans, (2) Practising a religiously permitted profession and (c) Maintaining good relations with involved stakeholders. Each of these three components is addressed in a distinct section, followed by a sub-section highlighting the relevance of the respective component to the particular context of AI-mediated work. The article argues that there are no unsurmountable barriers in the Islamic tradition against the adoption of AI technologies in work sphere. However, important precautions should be considered to ensure that embracing AI will not be at the cost of work-related moral values. The article also highlights how important lessons can be learnt from the positive historical experience of automata that thrived in the Islamic civilization. (shrink)

The field of artificial intelligence (AI) can be characterized as the investigation of computational systems that exhibit intelligent behavior (including algorithms and models used in these systems). The emphasis is not so much on understanding (human) cognitive processes as on producing models, algorithms, and systems that are capable of apparently intelligent behavior by whatever means available. The idea of AI has had a long history that can be traced all the way back to, for example, Leibniz. The (...) idea was furthered through the development, early in this century, of mathematical logic, cybernetics, and information theory, all of which contributed to AI theorizing. Alan Turing's bold claim that machines can think, advanced in his famous 1950 paper, and the “Turing test” he proposed therein as a means to test the intelligence of machines predated and prompted the formation of AI. Six years later, the Dartmouth conference in 1956, the participants of which included Allen Newell, Herbert Simon, Marvin Minsky, and John McCarthy, inaugurated AI as an academic discipline. This contemporary version of AI was facilitated by the invention and rapidly widening use of digital computers. AI embodies an extremely diverse set of ideas that are often mutually conflicting (as in the case of symbolism versus connectionism), and its relationship with other fields studying cognition (such as psychology and linguistics) has been a close but uneasy one. (shrink)

The papers in the following volume are the outcome of a three-year long interdisciplinary research project. The project began with an in-person meeting hosted and funded by the Daimler und Benz Stiftung in Germany in March 2020 (the world was shutting down one nation at a time as we met). During the pandemic we continued to meet monthly online with support from Memorial University of Newfoundland. From the beginning it was the goal of the Working Group on Intelligence (WGI), (...) as we called ourselves, to broaden and deepen the AI debate with a more nuanced understanding of intelligence than is common in cognitive and computer science discussions of AI. We wished to draw on the history of philosophy, ecology, and the philosophy of mind to establish that intelligence is meant in many senses, to use an Aristotelian expression. The clarification of these various meanings is essential to the discussion around the ethics of AI, especially the question concerning the possibility of strong AI or Artificial General Intelligence. (shrink)

Heuristic programming was the first area in which AI methods were tested. The favourite case-studies were fairly simple toy- problems, such as cryptarithmetic, games, such as checker or chess, and formal problems, such as logic or geometry theorem-proving. These problems are well-defined, roughly speaking, at least in comparison to real-life problems, and as such have played the role of Drosophila in early AI. In this chapter I will investigate the origins of heuristic programming and the shift to more knowledge-based and (...) real-life problem solving. (shrink)

With the emergence of Artificial Intelligence (AI) in the Anthropocene, we are faced with “humanizing AI before it dehumanizes us.” Before the advent of the “posthuman,” will our technologies help develop a better world, or enable us to more efficiently destroy it? This essay is an appeal to Black philosophers to contribute to the critique and value theory of AI. OpenAI’s GPT-4 has opened new ethical questions. This examination of AI’s history, and the possibility of “thinking machines,” (...) concludes that emerging technologies have disproportionately adverse effects on Black and brown people. To counter this, as a sentient tool, AI ought not be an instrument enabling excess capital accumulation, increased cognitive class division, surveillance for the authoritarian state, and pernicious anti-Black racism. Because of this, a new value theory for this technology should be based on participatory socialist principles of access to resources, environmentalism, and redistribution of the global commons. Informed by broader perspectives, as a more useful tool in bridging power differentials, AI should be the people’s tool. (shrink)

This article introduces seven ethical issues raised by the introduction of artificial intelligence (AI) at work. Each ethical issue is presented in connection to broader and older philosophical topics as well as topics in the more specialised literature on applied ethics of technology. The seven issues are: (1) How to govern the impact of AI on job losses and other social issues raised by the reshaping of the job market? (2) AI may contribute to create new forms of (...) oppression and violation of rights of the workforce; (3) AI may negatively affect workers’ (moral) agency, autonomy or responsibility; (4) AI may create hidden labour, that is, economically valuable tasks are performed by human agents without their work being sufficiently recognised, rewarded or protected, with (technological) companies acquiring an unfair gain and an increasing socio-economic power over people; (5) To what extent can AI affect the opportunity for people to perform good or meaningful work, and how should meaningful work be defined in a pluralistic society? (6) The introduction of AI at work may have a broader impact on social values and norms; (7) Who is responsible for making AI have a positive rather than a negative impact on ethical and societal values? In addition to providing a critical introduction to the ethical debate on AI and the future of work, the article also positions on this broader ethical and philosophical map the five articles of The Journal of Ethics special issue ‘Artificial Intelligence and the Future of Work’. (shrink)

The tendency to idealise artificial intelligence as independent from human manipulators, combined with the growing ontological entanglement of humans and digital machines, has created an “anthrobotic” horizon, in which data analytics, statistics and probabilities throw our agential power into question. How can we avoid the consequences of a reified definition of intelligence as universal operation becoming imposed upon our destinies? It is here argued that the fantasised autonomy of automated intelligence presents a contradistinctive opportunity for philosophical (...) consciousness to understand itself anew as holistic and co-creative, beyond the recent “analytic” moment of the history of philosophy. Here we introduce the concept of “crealectic intelligence”, a meta-analytic and meta-dialectic aspect of consciousness. Intelligent behaviour may consist in distinguishing discrete familiar parts or reproducible functions in the midst of noise via an analytic process of segmentation; intelligence may also manifest itself in the constitution of larger wholes and dynamic unities through a dialectic process of association or assemblage. But, by contrast, crealectic intelligence co-creates realities in the image of an ideal or truth, taking into account the desiring agent imbued with a sense of possibility, in a relationship not only with the Real but also with the creative sublime or “Creal”. (shrink)

Music and affects share a long history. In recent times, 4E cognitive sciences (embodied, embedded, enacted, and extended), situated affectivity, and related ecological theoretical frameworks have been conceptualizing music as a case of a tool for feeling. Drawing on this debate, I propose to further theorize the role of music in situating our affectivity by analyzing how the very affective affordances of music are technologically situated. In other words, I propose to shift the attention from music as a tool (...) for feeling to the tools for feeling music. I argue that the experience of music as a tool for feeling may be altered, enhanced, or lessened depending on the tools for feeling music. I investigate the extent to which AI might be a case of a tool for feeling music and examine the influence it could exert over musical affectivity. I conclude that AI can be considered a tool for feeling music of curatorial type and that the limitations and/or biases of AI as a method risk lessening the power of musical affective affordances. (shrink)

The moral enhancement of human beings is a constant theme in the history of humanity. Today, faced with the threats of a new, globalised world, concern over this matter is more pressing. For this reason, the use of biotechnology to make human beings more moral has been considered. However, this approach is dangerous and very controversial. The purpose of this article is to argue that the use of another new technology, AI, would be preferable to achieve this goal. Whilst (...) several proposals have been made on how to use AI for moral enhancement, we present an alternative that we argue to be superior to other proposals that have been developed. (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)

The central thesis of this book is that the argument that probability is insufficient to handle uncertainty in artificial intelligence (AI) is metaphysical in nature. Piscopo calls this argument against probability the non-adequacy claim and provides this summary of it [which first appeared in (Piscopo and Birattari 2008)]:Probability theory is not suitable to handle uncertainty in AI because it has been developed to deal with intrinsically stochastic phenomena, while in AI, uncertainty has an epistemic nature. (Piscopo (3))Piscopo uses (...) the term “metaphysical” in the Popperian sense: the non-adequacy claim is metaphysical (rather than scientific) since it cannot be disproved (much less established) by observation or experiment.In Chapter 2, Piscopo recounts some of the relevant history and issues in philosophy of science. There is little that is controversial here. One problem is that when addressing the question of how a particular probabilistic model is tested, Piscopo limits herself .. (shrink)

We discuss, first, TUring's role in the development of the computer; second, the early history of Artificial Intelligence (to 1956); and third, TUring's fa- mous imitation game, now universally known as the TUring test, which he proposed in cameo form in 1948 and then more fully in 1950 and 1952. Various objections have been raised to Turing's test: we describe some of the most prominent and explain why, in our view, they fail.

In this article, I establish a theory of knowledge approach for evaluating the use of computers for educational purposes at the university. In so doing, I trace part of the history of the “enabling factor” of Artificial Intelligence in this sector, an important element that has been integrated into everyday learning environments. The result of my reflection is a dialogical structure, directly inspired by past technology assessment research, which illustrates the conceptual advancement of researchers in the field (...) of learning technologies. The notions covered have implications in future policy-related discourse with regards to education. (shrink)

I develop a multilevel, holistic view of persons, emphasizing embodiment, emotions, consciousness, and the social self. In successive sections I draw from six sources: 1. Theology. The biblical understanding of the unitary, embodied, social self gave way in classical Christianity to a body‐soul dualism, but it has been recovered by many recent theologians. 2. Neuroscience. Research has shown the localization of mental functions in regions of the brain, the interaction of cognition and emotion, and the importance of social interaction in (...) evolutionary history and child development. 3. Artificial intelligence. Some forms of robotics use embodied systems that learn by interacting with their environment, but the possibilities for emotion, socialization, and consciousness in robots remain problematic. 4. Relations between levels. Concepts that can help us relate studies of neurons and persons include the hierarchy of levels, the communication of information, thebehavior of dynamic systems, and epistemological and ontological emergence. 5. Philosophy of mind. Two‐aspect theories of the mind‐brain relation offer an alternative between the extremes of eliminative materialism and the thesis that consciousness is irreducible. 6. Process philosophy. I suggest that process thought provides a coherent philosophical framework in which these themes can be brought together. It combines dipolar monism with organizational pluralism, and it emphasizes embodiment, emotions, a hierarchy oflevels, and the social character of selfhood. (shrink)

For all of recorded history prior to the second half of the twentieth century, there has been but one realm in which the cognitive processes of reasoning and problem solving, learning and discovery, language and mathematics took place. The realm of human intellect no longer has an exclusive claim on these cognitive processes--artificial intelligence represents a parallel claim. Wagman compares the two realms, focusing on each of the major components of cognition: logic, reasoning, problem-solving, language, memory, learning, (...) and discovery. He identifies consonant and disparate modes of cognition, and develops a general theory of human and artificial intelligence. (shrink)

There have been few attempts, so far, to document the history of artificial intelligence. It is argued that the “historical sociology of scientific knowledge” can provide a broad historiographical approach for the history of AI, particularly as it has proved fruitful within the history of science in recent years. The article shows how the sociology of knowledge can inform and enrich four types of project within the history of AI; organizational history; AI viewed (...) as technology; AI viewed as cognitive science and historical biography. In the latter area the historical treatments of Darwin and Turing are compared to warn against the pitfalls of “rational reconstructions” of the past. (shrink)

We are not today close to producing a computer that could convince us that it is intelligent. Some philosophers have argued that we are not even appreciably closer to this goal than we were ten years ago. But why should artificial intelligence even be considered possible? In this paper I shall argue that the temptation to believe in the possibility of AI stems from a misunderstanding about the nature of ideas; further, this misunderstanding can be traced back at (...) least to Plato’s presentation of the metaphor of the cave. A phenomenological view of the nature of ideas removes the temptation to believe in the possibility of AI as presently considered. (shrink)

Artificial Intelligence (AI) is a high-profile subject these days. In its brief history it has undergone several highs and lows and suffered from significant degrees of hype as well as antagonism and fear. One thing is clear: we are no closer to the goal of producing a truly sentient being than when it started. Nonetheless, the tools developed by AI researchers are here to stay and as with all technological advances it has its good and bad aspects. (...) In this article I will present a brief overview of the field of AI looking at what it is, how it developed, what are its specialism as well as some of its well-publicised successes, and failures, as well as pointing out some key Christian participants in the story. (shrink)

Artificial intelligence is not and has never been a technology. It began with Turing's famous "can machine think?", a philosophical question that too many were quick to transform into a more prosaic "can Thought be mechanized?" Only in this perspective can the history and the technological success of AI be duly explained and understood, one of the tasks this book engages in. -/- It is important for philosophers to take AI seriously, and for AI researchers to see (...) their discipline through the lenses of the adventure of the Spirit of man. The conclusion is that - paraphrasing Von Clausewitz's declaration about politics - "AI is a continuation of Philosophy by other means". Only after a proper meditaion and understanding of this fact can all the ethical, social and economical debates surrounding Artificial Intelligence begin to be discussed. (shrink)

This is the lightly revised text of my commentary/response to David Carr’s keynote address, “Phenomenology of Crisis,” at the 2024 meeting of the Husserl Circle.

The use of artificial intelligence as an instrument to assist judges in determining sentences in criminal cases is an issue that gives rise to many theoretical challenges. The purpose of this article is to examine one of these challenges known as the “input problem.” This problem arises supposedly due to two reasons: that in order for an algorithm to be able to provide a sentence recommendation, it needs to be inputted with case specific information; and that the task (...) of presenting an adequate picture of a crime often turns out to be highly complex. Even though this problem has been noted since the earliest attempts at developing sentencing support systems, almost no one has considered the ethical nature of this challenge. The aim of this article is to fill that void. First, it is shown that the input problem has been subject to somewhat different interpretations. Second, several possible answers as to when and why the problem constitutes an ethical challenge are considered. Third, a few suggestions are presented as to how undesirable implications of complexity at the input stage might be ameliorated by tailoring the way sentencing algorithms are developed and used in the work of criminal courts. (shrink)

The association of Wittgenstein’s name with the notion of artificial intelligence is bound to cause some surprise both to Wittgensteinians and to people interested in artificial intelligence. After all, Wittgenstein died in 1951 and the term artificial intelligence didn’t come into use until 1956 so that it seems unlikely that one could have anything to do with the other. However, establishing a connection between Wittgenstein and artificial intelligence is not as insuperable a (...) problem as it might appear at first glance. While it is true that artificial intelligence as a quasi-distinct discipline is of recent vintage, some of its concerns, especially those of a philosophical nature, have been around for quite some time. At the birth of modern philosophy we find Descartes wondering whether it would be possible to create a machine that would be phenomenologically indistinguishable from.. (shrink)

Hubert and Stuart Dreyfus have tried to place connectionism and artificial intelligence in a broader historical and intellectual context. This history associates connectionism with neuroscience, conceptual holism, and nonrationalism, and artificial intelligence with conceptual atomism, rationalism, and formal logic. The present paper argues that the Dreyfus account of connectionism and artificial intelligence is both historically and philosophically misleading.

The paper focuses on the questions of whether, to what extent, and in what ways the implications of the rapid development of artificial intelligence are changing the nature of one of the fundamental philosophical questions, “What does it (even) mean to understand?” It draws on two sources in particular: Hinton’s explanation of the technological development and functioning of deep neural networks and Nietzsche’s deconstruction of human understanding based on his key concept of “embodied errors.” In doing so, it (...) reveals a series of unexpected parallels, relating in particular to the notion of micro- evolution and the function of error in the processes underlying “thinking” and “intelligence.” The paper therefore draws certain parallels and demarcation lines between human understanding and the “learning” procedures of digital neural networks. At the same time, it addresses the question of what it means for the interpretation of human understanding that, for the first time in history, understanding is faced with a real, existing antithesis, represented by intelligent systems which, although they do not understand, are capable of performing the tasks of understanding, and capable of replacing understanding. (shrink)

Since antiquity, philosophers and engineers have tried to take life’s measure by reproducing it. Aiming to reenact Creation, at least in part, these experimenters have hoped to understand the links between body and spirit, matter and mind, mechanism and consciousness. Genesis Redux examines moments from this centuries-long experimental tradition: efforts to simulate life in machinery, to synthesize life out of material parts, and to understand living beings by comparison with inanimate mechanisms. Jessica Riskin collects seventeen essays from distinguished scholars in (...) several fields. These studies offer an unexpected and far-reaching result: attempts to create artificial life have rarely been driven by an impulse to reduce life and mind to machinery. On the contrary, designers of synthetic creatures have generally assumed a role for something nonmechanical. The history of artificial life is thus also a history of theories of soul and intellect. Taking a historical approach to a modern quandary, Genesis Redux is essential reading for historians and philosophers of science and technology, scientists and engineers working in artificial life and intelligence, and anyone engaged in evaluating these world-changing projects. (shrink)

cians concerned with using logical tools in philosophy have been keenly aware of the limitations that arise from the original con centration of symbolic logic on the idiom of mathematics, and many of them have worked to create extensions of the received logical theories that would make them more generally applicable in philosophy. Carnap's Testability and Meaning, published in 1936 and 1937, was a good early example of this sort of research, motivated by the inadequacy of first-order formalizations of dis (...) 'This sugar cube is soluble in water'. positional sentences like And in fact there is a continuous history of work on this topic, extending from Carnap's paper to Shoham's contribution to the present volume.. Much of the work in philosophical logic, and much of what has appeared in The Journal of Philosophical Logic, was mo tivated by similar considerations: work in modal logic, intensional logics, non declaratives, presuppositions, and many other topics. In this sort of research, sin.ce the main point is to devise new formalisms, the technical development tends to be rather shallow in comparison with mathematical logic, though it is sel dom absent: theorems need to be proved in order to justify the formalisms, and sometimes these are nontrivial. On the other hand, much effort has to go into motivating a logical innovation. (shrink)

This article analyses the limits of legal norms and institutions in holding to account the emerging power of Artificial Intelligence (AI) and Machine Learning. It demonstrates how a symbiosis of capitalism and new forms of digital power is mutating to produce novel and dangerous styles of organised irresponsibility that go beyond the reach of conventional legal mechanisms. It draws on the work of Pashukanis, Baudrillard, and Alain Supiot to show how this transformation is taking place. Referring to the (...) role of AI in the spread of Financial Technologies, it introduces a new term – ‘venture legalism’ – to describe how unprecedented risks are currently being created. It concludes by observing how ethical and democratic registers are equally implausible modes of accountability. (shrink)