In ‘Computing Machinery and Intelligence’, Turing, sceptical of the question ‘Can machines think?’, quickly replaces it with an experimentally verifiable test: the imitation game. I suggest that for such a move to be successful the test needs to be relevant, expansive, solvable by exemplars, unpredictable, and lead to actionable research. The Imitation Game is only partially successful in this regard and its reliance on language, whilst insightful for partially solving the problem, has put AI progress on the wrong foot, prescribing (...) a top-down approach for building thinking machines. I argue that to fix shortcomings with modern AI systems a nonverbal operationalisation is required. This is provided by the recent Animal-AI Testbed, which translates animal cognition tests for AI and provides a bottom-up research pathway for building thinking machines that create predictive models of their environment from sensory input. (shrink)

This chapter discusses the emerging field of data ethics and ethics of AI. It starts with the notion of Big Data and the non-neutrality of data practices. It then turns to artificial intelligence, discussing its history and functioning and questions of agency and responsibility. Following this, the chapter delves into three core principles in AI and data ethics: privacy, fairness, and accountability. It concludes with discussing some important standards and regulations for AI and data ethics, like the GDPR.

Leibniz dit souvent que toutes les substances individuelles et seulement les substances individuelles peuvent être agents moraux authentiques. Mais, dans un passage fascinant des "Nouveaux essais", Leibniz semble concéder à John Locke que si les machines pensantes existaient, elles pourraient être des agents moraux authentiques. Ce serait une concession très significative considérant le fait que pour Leibniz les machines ne sont pas du tout des substances authentiques, mais de simple agrégats de matière. En général, les érudits ont interprété ce passage (...) comme un moyen pour Leibniz d'affirmer que l'identité métaphysique à long terme n'est pas une condition nécessaire pour l'identité morale à long terme. Mais, dans cette étude, je vais soutenir que Leibniz ne concède réellement pas à Locke que les machines pensantes pourraient être des agents moraux. (shrink)

This paper explores Church's Thesis and related claims madeby Turing. Church's Thesis concerns computable numerical functions, whileTuring's claims concern both procedures for manipulating uninterpreted marksand machines that generate the results that these procedures would yield. Itis argued that Turing's claims are true, and that they support (the truth of)Church's Thesis. It is further argued that the truth of Turing's and Church'sTheses has no interesting consequences for human cognition or cognitiveabilities. The Theses don't even mean that computers can do as much (...) as peoplecan when it comes to carrying out effective procedures. For carrying out aprocedure is a purposive, intentional activity. No actual machine does, orcan do, as much. (shrink)

In Malicious Deceivers, Ioana B. Jucan traces a genealogy of post-truth intimately tied to globalizing modernity and connects the production of repeatable fakeness with capitalism and Cartesian metaphysics. Through case studies that cross times and geographies, the book unpacks the notion of fakeness through the related logics of dissimulation (deception) and simulation (performativity) as seen with software/AI, television, plastics, and the internet. Specifically, Jucan shows how these (dis)simulation machines and performative objects construct impoverished pictures of the world, ensuring a repeatable (...) sameness through processes of hollowing out embodied histories and lived experience. Through both its methodology and its subjects-objects of study, the book further seeks ways to counter the abstracting mode of thinking and the processes of voiding performed by the twinning of Cartesian metaphysics and global capitalism. Enacting a model of creative scholarship rooted in the tradition of writing as performance, Jucan, a multimedia performance-maker and theatre director, uses the embodied "I" as a framing and situating device for the book and its sites of investigation. In this way, she aims to counter the Cartesian voiding of the thinking "I" and to enact a different kind of relationship between self and world from the one posited by Descartes and replayed in much Western philosophical and - more broadly - academic writing: a relationship of separation that situates the "I" on a pedestal of abstraction that voids it of its embodied histories and fails to account for its positionality within a socio-historical context and the operations of power that define it. (shrink)

This chapter contains sections titled: The Philosophical Tale.

Radical democratic thinking is becoming intrigued by the material situatedness of its political agents and by the role of nonhuman participants in political interaction. At stake here is the displacement of narrow anthropocentrism that currently guides democratic theory and practice, and its repositioning into what we call ‘the nonhuman condition’. This Critical Exchange explores the nonhuman condition. It asks: What are the implications of decentering the human subject via a new materialist reading of radical democracy? Does this reading dilute (...) political agency? Or should this be seen, on the contrary, as an invitation for new voices and demands to enter into democratic assemblages? How might engagement with the more-than-human disrupt or extend theories of radical democracy? Hans Asenbaum and Amanda Machin discuss the human democratic subject both through radical democratic and new materialist lenses. They suggest that a new materialist decentred subject does not lose agency but further gains political responsibility in radical democracy. Jean-Paul Gagnon highlights the possibility of becoming through loss. In losing our anthropocentric arrogance—our understanding of being other and better than animal—we become more connected and discover our place in human-nonhuman assemblages. Melissa Orlie agrees that something can be gained through renouncing dominant human fantasies and presents a ‘radical democratic naturalism’. By renouncing land violence and acknowledging nature’s subjectivity, we can further nonexploitative radical democratic politics. This is where the notion of ‘tidalectic’ processes introduced by James L. Smith is helpful. Focusing on water and the Indigenous knowledges around rivers, he considers how democracy and community can be reimagined as plural, cyclical and attentive to the nonhuman with which the human is inevitably entangled. Diana Leong offers a different approach. Considering the nonhuman from the perspective of Black Studies demands an awareness to how blackness has long been constituted as non- or partially human. (shrink)

While the psychiatric perspective on pathologising vital cycles and processes, sexual diversity, and the stages of childhood life receives more and more rejection of their positions, the trend toward depathologisation as drifts in social movements and sociological, psychological, anthropological, and philosophical perspectives still does not offer practical solutions to mental illness and psychological suffering. The depathologising gaze, promoted not only by social movements or emerging disciplines—such as Mad Studies and child-centered philosophy—but also recently by traditional disciplines, has the harmful effect (...) of abandoning many suffering people, whose expectations in “Psy” professionals are vital to solving your real problems.How can one find a middle ground between these two tendencies?There’s not a simple answer to that problem. So, authors in this chapter propose a revision of the term pathos as a cultural object and its human implication. The question is linked with some of the foundational conceptions about the human being (Vygotski, Pensamiento y lenguaje. Editora Revolucionaria, 1926; Foucault, Naissance de la Clinique. Presses Universitaires de France, 1963; Canguilhem, Le normal et le pathologique. PUF, 1966) and its expressions (Deleuze, Las cartas del mal (13/1/1981) en Gilles Deleuze: En medio de Spinoza. Cactus, 1981).Culture, time, aesthetics, consciousness; continuity body-mind; instinct-pulsion, virtualisation, networks, and so on are some of the concepts revisited in this chapter to reframe the de question.Pathos, psychopathology, pathologisation, depathologisation, and mental health and illness are presented in this chapter as differentiated concepts with particular effects in each cultural context and referential frame, but particularly in each singular case (Forrester, Thinking in cases. Polity, 2017) as an empirical level for analysing the human nature (Foucault, Naissance de la Clinique. Presses Universitaires de France, 1963).Thus, a reframe of pathology and mental health is proposed, as a result of a new set of particular relationships, according to the formula opportunely analysed on Spinoza by Vygotski (Pensamiento y lenguaje. Editora Revolucionaria, 1926) and Deleuze (Las cartas del mal (13/1/1981) en Gilles Deleuze: En medio de Spinoza. Cactus, 1981), respectively. (shrink)

The location of the living human being in the animal world is a long-standing discussion, with recurrences from time to time. Perhaps one of the most significant for contemporary Western thought was the course that Kojeve gave between 1935 and 1939 on the phenomenology of Hegel’s spirit, not so much not only because of the teaching itself but because of the resonances on the rest of French thought and in a certain sense European in general. Bataille, Lacan, Levy-Srauss, Foucault, and (...) Agamben, among others, refer to the turn this course represented for human interpretation.Based on this interpretation, several unavoidable concepts can be identified, without which this discussion would be meaningless: the concept of homo has been indistinctly associated with sapiens, faber, zoon politikón, ludens, conscious, or drive. The first has had a clear expression in the anthropological tradition or non-pragmatic sociology, leaving the last two reserved for psychology and psychoanalysis.In an approximation to the Freudian text of 1915 Drive and destinations of drive, which J. Lacan made in his Seminar 11, “The Four Fundamental Concepts of Psychoanalysis”; specifically, in the class of May 6, 1964 “Disassembly of the Drive,” he reminds us how essential one of the concepts of psychoanalysis is for the analytic experience: the drive (Trieb). This term, with a long history of clarifications and ambiguities in Freud’s work, is found throughout the entire corpus of his metapsychology, basting together the rest of the concepts and giving the body to a theory of the human psyche. Thus, the drive, rooted in psychoanalytic interpretations, which “every analyst (is) knows by existence” (Lacan, Les quatre concepts fondamentaux de la psychanalyse. Le séminaire, livre XI. Éditions du Seuil, 1964, p. 60); however, it has been “used” at will, according to what each theoretician needed for what he had to address.At the very core of this discussion is the relationship with Pathos. The recognition or not of the living human and its type variants, pathology as a result of the non-pathological or pathos as indissoluble from the cultural essence have been some of the central questions. However, autism has appeared as an uncomfortable stone, whether one enters via “normality” toward the “pathological” or vice versa. It has even had a problematic history in the psychoanalytic tradition as well.In this way, since the notion of autism began to be legitimised in the psychoanalytic tradition to name certain subjects—particularly infants—a diverse and challenging use was made of the Freudian notion of drive in its interpretation.Then, to ask: how could “drive theory” explain what psychoanalysis considers “autism”? What are the difficulties in the dialogue between these two signifiers? Are these difficulties due to the misunderstanding of the word autism, as some hypothesise? Or to the different meanings of the drive in Freud, as others think? Or perhaps, are there other epistemic reasons that block these two concepts in the psychoanalytic theoretical gear?We hypothesise that the appearance of autism came to shake up all this tradition for which the human subject was a fracture in the animal evolutionary continuity, both that of consciousness/unconscious—which exceeds the possibility of discussion in this space—and the “drive thesis,” which is the one that concerns us. In this sense, the opposition continuism-discontinuism would now be, for the phylogenetic, put into question, to be eventually replaced by an asymptotic continuism, more assimilable to the Spinozian bet.This chapter explores the references to Sigmund Freud’s theory of drives in the interpretative approaches to child autism. Notably, it analyses the psychoanalytic thesis that proposes a constitutive failure in primordial times to understand the genesis of autism. The work explicitly presents a revelation of drive theory’s importance for the approach to autism. It also drives the exploration of the modes of appropriation and the use of said theorisation to explain the autistic phenomenon. Finally, the chapter discusses the analysis of the difficulties presented to the psychoanalytic authors when trying to accept autistic functioning and their theoretical choices to interpret it according to drive’s theory. (shrink)

A book Review of Artificial Knowing Gender and the Thinking Machine, by Alison Adam, Routledge: Taylor and Francis, 1998.

When Turing considered the question, “Can machines think?” he anticipated many difficulties this claim would have to overcome before being considered seriously, much less accepted. The most basic difficulty was bias against the idea embedded in the English words machines and think. When considering this and other difficulties for his claim, Turing (1947/2004) urged that “… fair play must be given to the machine.” As Magnani (2022) points out, Turing was working at a time when the concept of computing (...) was changing fundamentally due to the development of digital computers, in which Turing played a significant role. Turing’s ideas about thinking machines were part of his response to this profound revision in history, which both motivated and grounded his call for fair play. The aim of this article to discuss and develop Turing’s idea of fair play as a reconsideration of the trade-off between skeptical and charitable strategies for the assessment of hypotheses like machines can think. Specifically, Turing’s call amounts to the view that critics of the hypothesis are overly skeptical due to historical bias and partiality. His call for fair play is a call for a more charitable assessment of the hypothesis, one that neutralizes the prejudices embedded in his contemporary context. (shrink)

Recent progress in artificial intelligence has renewed interest in building systems that learn and think like people. Many advances have come from using deep neural networks trained end-to-end in tasks such as object recognition, video games, and board games, achieving performance that equals or even beats that of humans in some respects. Despite their biological inspiration and performance achievements, these systems differ from human intelligence in crucial ways. We review progress in cognitive science suggesting that truly human-like learning and (...) class='Hi'>thinking machines will have to reach beyond current engineering trends in both what they learn and how they learn it. Specifically, we argue that these machines should build causal models of the world that support explanation and understanding, rather than merely solving pattern recognition problems; ground learning in intuitive theories of physics and psychology to support and enrich the knowledge that is learned; and harness compositionality and learning-to-learn to rapidly acquire and generalize knowledge to new tasks and situations. We suggest concrete challenges and promising routes toward these goals that can combine the strengths of recent neural network advances with more structured cognitive models. (shrink)

In the opening paragraph of “Computing Machinery and Intelligence” Alan Turing famously notes that “if the meaning of the words ‘machine’ and ‘think’ are to be found by examining how they are commonly used it is difficult to escape the conclusion that the meaning and the answer to the question, ‘Can machines think?’ is to be sought in a statistical survey such as a Gallup poll.” He then immediately responds, “But this is absurd.” But why is this absurd, if (...) indeed it is? We think that the suggested method is absurd because the answer to the question might not follow from the meaning of the words alone—it might critically depend on what machines can be built to do. Further, the ordinary use of the terms might display shallow biases or superstitions that we want to set aside, or overcome, in pursuing a science or philosophy of mind. However, we do not think that the method is absurd insofar as we are interested in getting clear on “the normal use of the words,” as Turing puts it. And we believe that getting clear on the normal use of words like “machine” and “think” is relevant even if we then want to move beyond the ordinary usage in our theorizing. But the best way to figure out how ordinary people use language is via empirical investigation. (shrink)

Machine and Sovereignty offers a future-oriented mode of political thought that encompasses the unprecedented global challenges we are confronting: the rise of artificial intelligence, the ecological crisis, and intensifying geopolitical conflicts. Arguing that a new approach to planetary thinking is urgently needed, Yuk Hui presents new epistemological and technological frameworks for understanding and rising to the crises of our present and our future.

From his preliminary analysis in 1965, Hubert Dreyfus projected a future much different than those with which his contemporaries were practically concerned, tempering their optimism in realizing something like human intelligence through conventional methods. At that time, he advised that there was nothing “directly” to be done toward machines with human-like intelligence, and that practical research should aim at a symbiosis between human beings and computers with computers doing what they do best, processing discrete symbols in formally structured problem domains. (...) Fast-forward five decades, and his emphasis on the difference between two essential modes of processing, the unconscious yet purposeful mode fundamental to situated human cognition, and the “minded” sense of conscious processing characterizing symbolic reasoning that seems to lend itself to explicit programming, continues into the famous Dreyfus–McDowell debate. The present memorial reviews Dreyfus’ early projections, asking if the fears that punctuate current popular commentary on AI are warranted, and in light of these if he would deliver similar practical advice to researchers today. (shrink)

_Artificial Knowing_ challenges the masculine slant in the Artificial Intelligence (AI) view of the world. Alison Adam admirably fills the large gap in science and technology studies by showing us that gender bias is inscribed in AI-based computer systems. Her treatment of feminist epistemology, focusing on the ideas of the knowing subject, the nature of knowledge, rationality and language, are bound to make a significant and powerful contribution to AI studies. Drawing from theories by Donna Haraway and Sherry Turkle, and (...) using tools of feminist epistemology, Adam provides a sustained critique of AI which interestingly re-enforces many of the traditional criticisms of the AI project. _Artificial Knowing_ is an esential read for those interested in gender studies, science and technology studies, and philosophical debates in AI. (shrink)

Bu makale, “Makineler düşünebilir mi?” sorusunu yalnızca teknik bir yeterlilik meselesi olarak değil, düşüncenin mahiyetine, zihnin yapısına ve bilincin imkânına dair temel bir felsefi soruşturma olarak ele alır. Yapay zekâ, insan benzeri düşünme ve davranma kalıplarıyla ilişkilendirilerek dört temel paradigma çerçevesinde - insan gibi düşünen, insan gibi davranan, rasyonel düşünen ve rasyonel davranan sistemler - incelenir. Bu çerçeve, zihinsel etkinliğin salt hesaplamalı süreçler ve dışsal işlevlerle açıklanıp açıklanamayacağı ya da anlam, niyet ve bilinç gibi içkin fenomenleri zorunlu olarak içerip içermediği (...) sorusunu gündeme taşır. Turing’in taklit oyunu ve Searle’ün Çin Odası düşünce deneyi, sentaktik işlem ile semantik kavrayış arasındaki farkı görünür kılarak, yapay sistemlerin gerçekten “anlayıp anlamadığı”na dair felsefi ayrımı temellendirir. Günümüzde doğal dil işleme, makine öğrenimi ve görsel algı gibi alanlarda kaydedilen ilerlemeler, yapay zekânın işlevsel gücünü önemli ölçüde artırmıştır. Ancak bu gelişmelerin, bilinçli deneyim, özne oluş ve anlam üretme yetisiyle örtüşüp örtüşmediği hâlâ açık bir sorudur. Güçlü yapay zekâ savunuları, zihinsel süreçlerin algoritmik olarak yeniden üretilebileceğini kabul eder. Buna karşılık eleştirel yaklaşımlar, zihni yalnızca işleyen bir mekanizma olarak değil, bedensel, ilişkisel ve fenomenolojik bir bütünlük içinde değerlendirir. Bu çalışma, yapay zekâyı teknik bir araç olarak değil, düşünceyi, anlamı ve bilinci yeniden düşünmeye çağıran felsefi bir meydan okuma olarak görmektedir. Düşünce, hesaplamaya indirgenemeyen, varoluşsal derinliği olan bir fenomendir. Bu bağlamda yapay zekâ sorusu, özünde insanın ne olduğu sorusuna yönelmiş çağdaş bir felsefi ifadedir. (shrink)

Mr. A. M. Turing was quoted in The Times about a year ago as saying it would be interesting to discover the degree of intellectual activity of which a machine was capable and to what extent it could think for itself. He has now pressed this suggestion further and given the results of his researches in an article called “Computing Machines and Intelligence,” together with a brief account of a “child-machine” which he has attempted to educate . I (...) intend to discuss this article in some detail and examine his claim that “machines can think.”. (shrink)

Turing’s much debated test has turned 70 and is still fairly controversial. His 1950 paper is seen as a complex and multilayered text, and key questions about it remain largely unanswered. Why did Turing select learning from experience as the best approach to achieve machine intelligence? Why did he spend several years working with chess playing as a task to illustrate and test for machine intelligence only to trade it out for conversational question-answering in 1950? Why did Turing (...) refer to gender imitation in a test for machine intelligence? In this article, I shall address these questions by unveiling social, historical and epistemological roots of the so-called Turing test. I will draw attention to a historical fact that has been only scarcely observed in the secondary literature thus far, namely that Turing’s 1950 test emerged out of a controversy over the cognitive capabilities of digital computers, most notably out of debates with physicist and computer pioneer Douglas Hartree, chemist and philosopher Michael Polanyi, and neurosurgeon Geoffrey Jefferson. Seen in its historical context, Turing’s 1950 paper can be understood as essentially a reply to a series of challenges posed to him by these thinkers arguing against his view that machines can think. Turing did propose gender learning and imitation as one of his various imitation tests for machine intelligence, and I argue here that this was done in response to Jefferson's suggestion that gendered behavior is causally related to the physiology of sex hormones. (shrink)

The fact that we were used to thinking non-thinking machines, the ones supplementing human physical labor, and that we are only now encountering machines that supposedly supplement human thinking, does not mean that this is either the direction in the evolution of the machine or the genealogy of ideas about the machine. Psychoanalysis tempts us to say that the history of the machine could only be written together with the history of the unconscious, while (...) studies of ancient orality reveal to us the intricacy of the oral technicity predating the technology of the written word. This means that the machine predates a simple tool, and highlights the possibility of thinking a genealogy of the machine, which must necessarily entangle with the genealogy of thought and memory. Following this line of thought, we should correct ourselves by saying that the idea of a machine that thinks is not a contemporary occurrence after all. (shrink)

Over three decades ago, in a brief but provocative essay, Paul Ziff argued for the thesis that robots cannot have feelings because they are "mechanisms, not organisms, not living creatures. There could be a broken-down robot but not a dead one. Only living creatures can literally have feelings."[i] Since machines are not living things they cannot have feelings. In the first half of my paper I review Ziff's arguments against the idea that robots could be conscious, especially his appeal to (...) our linguistic usage. In the second half of the essay I try to provide a deeper ontological understanding of why we ought not attribute minds to nonliving artifacts. I argue that inanimate mechanisms are incapable of genuinely active and purposive behavior. They are importantly different in kind from living human beings and animals. (shrink)

Can computers think? This book is intended to demonstrate that thinking, understanding, and intelligence are more than simply the execution of algorithms--that is, that machines cannot think. Written and edited by leaders in the fields of artificial intelligence and the philosophy of computing.

The dynamic development of technology, as well as of AI’s, raises the fundamental question: can machines think? At the beginning of the 20th Century the Austrian philosopher wonders about this problem and analyses it from a logical-philosophical conception which conveys the need to recognize all the elements comprised in the thought-language relationship. An ethical-religious dimension is revealed in certain uses of language. This dimension, which shows the human’s attitude to the world, stems from the human tendency to search for explanations. (...) This attitude does not extend to machines. (shrink)

Lake et al. propose three criteria which, they argue, will bring artificial intelligence (AI) systems closer to human cognitive abilities. In this paper, we explore the application of these criteria to a particular domain of human cognition: our capacity for moral reasoning. In doing so, we explore a set of considerations relevant to the development of AI moral decision-making. Our main focus is on the relation between dual-process accounts of moral reasoning and model-free/model-based forms of machine learning. We also (...) discuss how work in embodied and situated cognition could provide a valu- able perspective on future research. (shrink)

Heidegger's treatment of 'machination' in the Beiträge zur Philosophie begins the critique of technological thinking that would centrally characterize his later work. Unlike later discussions of technology, the critique of machination in Beiträge connects its arising to the predominance of 'lived-experience' ( Erlebnis ) as the concealed basis for the possibility of a pre-delineated, rule-based metaphysical understanding of the world. In this essay I explore this connection. The unity of machination and lived-experience becomes intelligible when both are traced to (...) their common root in the primordial Greek attitude of techne , originally a basic attitude of wondering knowledge of nature. But with this common root revealed, the basic connection between machination and lived-experience also emerges as an important development of one of the deepest guiding thoughts of the Western philosophical tradition: the Parmenidean assertion of the sameness of being and thinking. In the Beiträge 's analysis of machination and lived-experience, Heidegger hopes to discover a way of thinking that avoids the Western tradition's constant basic assumption of self-identity, an assumption which culminates in the modern picture of the autonomous, self-identical subject aggressively set over against a pre-delineated world of objects in a relationship of mutual confrontation. In the final section, I investigate an important and illuminating parallel to Heidegger's result: the consideration of the relationship between experience and technological ways of thinking that forms the basis of the late Wittgenstein's famous rule-following considerations. (shrink)

The focus of this article is the psychological allure of automation, as well as the anticipated cognitive and social consequences of heavily mediated and automated societies. The article approaches these themes through an in-depth analysis of E. M. Forster’s rather dystopian vision of a fully automated society in his 1909 story “The Machine Stops.” The analysis puts Forster’s vision in conversation with contemporary automation trends, for example, addictive designs and data-driven personalization. A series of potential cognitive and social harms (...) are treated as stemming not from automation or mediation in itself but from, e.g., a loss of temporal, navigational, and social conditions for integrating our mediated experiences in a way that supports our epistemic world orientation. Thus, while our current automation trends differ from Forster’s 1909 vision, they might pose systematic and somewhat predictable threats to our cognitive, social, and political ecologies. (shrink)

This paper revisits the often debated question Can machines think? It is argued that the usual identification of machines with the notion of algorithm has been both counter-intuitive and counter-productive. This is based on the fact that the notion of algorithm just requires an algorithm to contain a finite but arbitrary number of rules. It is argued that intuitively people tend to think of an algorithm to have a rather limited number of rules. The paper will further propose a modification (...) of the above mentioned explication of the notion of machines by quantifying the length of an algorithm. Based on that it appears possible to reconcile the opposing views on the topic, which people have been arguing about for more than half a century. (shrink)

This question as to whether machines can, or could, be made to think, has become familiar in recent years since the renewed outburst of interest that has taken place in the development of Cybernetics. The notion of servo–mechanisms and the like has a history in remote antiquity but the form of its fundamental question has recently taken on a new and especially acute significance.

Professors A. D. Ritchie and F. H. George both miss the question: What is the use of saying that machines think? Does the extension in the use of the word “think” to cover the complicated activity of modern machines enable us to explain better the nature of such activity? Extensions in usage are common and necessary in science.

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)