Clark Glymour, Richard Scheines, Peter Spirtes and Kevin Kelly. Discovering Causal Structure: Artifical Intelligence, Philosophy of Science and Statistical Modeling.

In this paper, I provide an overview of today’s philosophical approaches to the problem of “intelligence” in the field of artificial intelligence by examining several important papers on phenomenology and the philosophy of biology such as those on Heideggerian AI, Jonas's metabolism model, and slime mold type intelligence.

Artificial Intelligence and Music Ecosystem highlights the opportunities and rewards associated with the application of AI in the creative arts. Featuring an array of voices, including interviews with Jacques Attali, Holly Herndon and Scott Cohen, this book offers interdisciplinary approaches to pressing ethical and technical questions associated with AI. Considering the perspectives of developers, students and artists, as well as the wider themes of law, ethics and philosophy, Artificial Intelligence and Music Ecosystem is an essential (...) introduction for anyone interested in the impact of AI on music, including those studying and working in the creative arts. (shrink)

This interdisciplinary collection of classical and contemporary readings provides a clear and comprehensive guide to the many hotly-debated philosophical issues at the heart of artificial intelligence.

As China and the United States strive to be the primary global leader in AI, their visions are coming into conflict. This is frequently painted as a fundamental clash of civilisations, with evidence based primarily around each country’s current political system and present geopolitical tensions. However, such a narrow view claims to extrapolate into the future from an analysis of a momentary situation, ignoring a wealth of historical factors that influence each country’s prevailing philosophy of technology and thus their (...) overarching AI strategies. In this article, we build a philosophy-of-technology-grounded framework to analyse what differences in Chinese and American AI policies exist and, on a fundamental level, why they exist. We support this with Natural Language Processing methods to provide an evidentiary basis for our analysis of policy differences. By looking at documents from three different American presidential administrations––Barack Obama, Donald Trump, and Joe Biden––as well as both national and local policy documents (many available only in Chinese) from China, we provide a thorough comparative analysis of policy differences. This article fills a gap in US–China AI policy comparison and constructs a framework for understanding the origin and trajectory of policy differences. By investigating what factors are informing each country’s philosophy of technology and thus their overall approach to AI policy, we argue that while significant obstacles to cooperation remain, there is room for dialogue and mutual growth. (shrink)

Organizations such as the EU High-Level Expert Group on AI and the IEEE have recently formulated ethical principles and (moral) values that should be adhered to in the design and deployment of artificial intelligence (AI). These include respect for autonomy, non-maleficence, fairness, transparency, explainability, and accountability. But how can we ensure and verify that an AI system actually respects these values? To help answer this question, I propose an account for determining when an AI system can be said (...) to embody certain values. This account understands embodied values as the result of design activities intended to embed those values in such systems. AI systems are here understood as a special kind of sociotechnical system that, like traditional sociotechnical systems, are composed of technical artifacts, human agents, and institutions but—in addition—contain artificial agents and certain technical norms that regulate interactions between artificial agents and other elements of the system. The specific challenges and opportunities of embedding values in AI systems are discussed, and some lessons for better embedding values in AI systems are drawn. (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)

What does it mean to consider the world of AI through a Christian lens? Rapid developments in AI continue to reshape society, raising new ethical questions and challenging our understanding of the human person. Encountering Artificial Intelligence draws on Pope Francis’ discussion of a culture of encounter and broader themes in Catholic social thought in order to examine how current AI applications affect human relationships in various social spheres and offers concrete recommendations for better implementation. The document also (...) explores questions regarding personhood, consciousness, and the kinds of relationships humans might have with even the most advanced AI. Through these discussions, this book investigates the theoretical and practical challenges to interpersonal encounter raised by the age of AI. (AI Research Group for the Centre for Digital Culture of the Dicastery of Culture and Education of the Holy See). (shrink)

Deep learning (DL) has become increasingly central to science, primarily due to its capacity to quickly, efficiently, and accurately predict and classify phenomena of scientific interest. This paper seeks to understand the principles that underwrite scientists’ epistemic entitlement to rely on DL in the first place and argues that these principles are philosophically novel. The question of this paper is not whether scientists can be justified in trusting in the reliability of DL. While today’s artificial intelligence exhibits characteristics (...) common to both scientific instruments and scientific experts, this paper argues that the familiar epistemic categories that justify belief in the reliability of instruments and experts are distinct, and that belief in the reliability of DL cannot be reduced to either. Understanding what can justify belief in AI reliability represents an occasion and opportunity for exciting, new philosophy of science. (shrink)

AI needs many ideas that have hitherto been studied only by philosophers. This is because a robot, if it is to have human level intelligence and ability to learn from its experience, needs a general world view in which to organize facts. It turns out that many philosophical problems take new forms when thought about in terms of how to design a robot. Some approaches to philosophy are helpful and others are not.

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

Artificial intelligence is increasingly permeating many types of high-stake societal decision-making such as the work at the criminal courts. Various types of algorithmic tools have already been introduced into sentencing. This article concerns the use of algorithms designed to deliver sentence recommendations. More precisely, it is considered how one should determine whether one type of sentencing algorithm (e.g., a model based on machine learning) would be ethically preferable to another type of sentencing algorithm (e.g., a model based on (...) old-fashioned programming). Whether the implementation of sentencing algorithms is ethically desirable obviously depends upon various questions. For instance, some of the traditional issues that have received considerable attention are algorithmic biases and lack of transparency. However, the purpose of this article is to direct attention to a further challenge that has not yet been considered in the discussion of sentencing algorithms. That is, even if is assumed that the traditional challenges concerning biases, transparency, and cost-efficiency have all been solved or proven insubstantial, there will be a further serious challenge associated with the comparison of sentencing algorithms; namely, that we do not yet possess an ethically plausible and applicable criterion for assessing how well sentencing algorithms are performing. (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)

This book deals with the major philosophical issues in the theoretical framework of Artificial Intelligence (AI) in particular and cognitive science in general.

The paper explores integrating AI into scholarly communication for enhanced human cognitive abilities. The conception of human-machine communication (HMC) approach that regards AI-based technologies not as interactive objects, but communicative subjects, throws issues that are more philosophical in scholarly communication. It is a known fact that, there is increased interaction between humans and machines especially consolidated by COVID-19 pandemic, which heightened the development of Individual Adaptive Learning System thereby necessarily requiring inputs from NI to strengthen AI. This positioned university at (...) the juxtaposition for ensuring the production of highly talented individuals who can continue to think beyond the thinkable intelligently and enabling AI experts to carry on building algorithms that can further the development of technology to the next level. To perform such a task, research output is paramount in connecting university and publishing industry. The paper critically examines important components and tries to do justice for emanating of critical questions from researchers (NI) thus feeding the development of technology (AI). (shrink)

This book is a collection of all the papers published in the special issue “Artificial Intelligence, Robots, and Philosophy,” Journal of Philosophy of Life, Vol.13, No.1, 2023, pp.1-146. The authors discuss a variety of topics such as science fiction and space ethics, the philosophy of artificial intelligence, the ethics of autonomous agents, and virtuous robots. Through their discussions, readers are able to think deeply about the essence of modern technology and the future of (...) humanity. All papers were invited and completed in spring 2020, though because of the Covid-19 pandemic and other problems, the publication was delayed until this year. I apologize to the authors and potential readers for the delay. I hope that readers will enjoy these arguments on digital technology and its relationship with philosophy. *** -/- Contents*** -/- Introduction : Descartes and Artificial Intelligence; Masahiro Morioka*** -/- Isaac Asimov and the Current State of Space Science Fiction : In the Light of Space Ethics; Shin-ichiro Inaba*** -/- Artificial Intelligence and Contemporary Philosophy : Heidegger, Jonas, and Slime Mold; Masahiro Morioka*** -/- Implications of Automating Science : The Possibility of Artificial Creativity and the Future of Science; Makoto Kureha*** -/- Why Autonomous Agents Should Not Be Built for War; István Zoltán Zárdai*** -/- Wheat and Pepper : Interactions Between Technology and Humans; Minao Kukita*** -/- Clockwork Courage : A Defense of Virtuous Robots; Shimpei Okamoto*** -/- Reconstructing Agency from Choice; Yuko Murakami*** -/- Gushing Prose : Will Machines Ever be Able to Translate as Badly as Humans?; Rossa Ó Muireartaigh***. (shrink)

This paper examines the hypothesis that analogies may play a role in the generation of new ideas that are built into new explanatory theories. Methods of theory construction by analogy, by failed analogy, and by modular components from several analogies are discussed. Two different analyses of analogy are contrasted: direct mapping (Mary Hesse) and shared abstraction (Michael Genesereth). The structure of Charles Darwin's theory of natural selection shows various analogical relations. Finally, an "abstraction for selection theories" is shown to be (...) the structure of a number of theories. (shrink)

This book develops an original theoretical framework for understanding human-technology relations. The author's approach, which he calls technoanalysis, analyzes artificial intelligence based on Freudian psychoanalysis, biosemiotics, and Latour's actor-network theory. How can we communicate with AI to determine shared values and objectives? And what, ultimately, do we want from machines? These are crucial questions in our world, where the influence of AI-based technologies is rapidly growing. Unconscious dynamics influence AI and digital technology and understanding them is essential to (...) better controlling AI systems. This book's unique methodology- which combines psychoanalysis, biosemiotics, and actor-network theory-reveals a radical reformulation of the problem of the human mind. Technoanalysis views the mind as a hybrid network of humans and nonhuman actants in constant interaction with one another. The author argues that human unconscious dynamics influence and shape technology, just as technology influences and shapes human unconscious dynamics. He proceeds to show how this conception of the relationship between the unconscious and technology can be applied to social robotics and AI. Unconscious Networks will appeal to scholars and advanced students interested in philosophy of technology, philosophy of artificial intelligence, psychoanalysis, and science and technology studies. (shrink)

The exploration of metaphysical arguments in the symbolic AI environment provides clarification and raises unexpected questions about notions in philosophy of religion and theology. Recent attempts to apply automatic theorem prover technology to Anselm's ontological argument have led to a simplification of the argument. This computationally discovered simplification has given rise to logical observations. The article assesses one of these observations: the application of the diagonal method (in Cantor's version) to Anselm's argument. The evaluation of the applications of theorem (...) provers to metaphysical and theological arguments contributes to the following topics in philosophy of religion: the limits of natural theology, the relationship between religion and STEM, and theology's scientificity. (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)

Moving from a behavioral definition of intelligence, which describes it as the ability to adapt to the surrounding environment and deal effectively with new situations (Anastasi, 1986), this paper explains to what extent the performance obtained by ChatGPT in the linguistic domain can be considered as intelligent behavior and to what extent they cannot. It also explains in what sense the hypothesis of decoupling between cognitive and problem-solving abilities, proposed by Floridi (2017) and Floridi and Chiriatti (2020) should be (...) interpreted. The problem of symbolic grounding (Harnad, 1990) is then addressed to show the problematic relationship between ChatGPT and the natural environment, and thus the impossibility for it to understand the symbols it manipulates. To explain the reasons why ChatGPT does not succeed in this task, an investigation is carried out and a possible solution to the problem in the artificial domain is proposed by making a comparison with the natural ability of living beings to ground their own meanings from some basic cognitive-sensory aspects, which, it is explained, are directly related to the emergence of self-awareness in humans. Thus, the question is raised whether a possible and concrete solution to the Symbol Grounding Problem would involve in the artificial domain the development of cognitive abilities fully comparable to those of humans. Finally, I explain the difficulties that would have to be overcome before such a level could be reached, since human cognitive capacities are intimately linked to intersubjectivity and intercorporeality. (shrink)

Some recent uses of artificial intelligence for facial recognition, evaluating resumes, and sorting photographs by subject matter have revealed troubling disparities in performance or impact based on the demographic traits of subject populations. These disparities raise pressing questions about how using artificial intelligence can work to promote justice or entrench injustice. Political theorists and philosophers have developed nuanced vocabularies and theoretical frameworks for understanding and adjudicating disputes about what justice requires and what constitutes injustice. The interdisciplinary (...) community committed to understanding and conscientiously using big data could benefit from this work. Thus, in the spirit of encouraging cross-disciplinary dialogue and collaboration, this piece examines contemporary scholarship in political theory and philosophy to illustrate some of the vocabularies and frameworks political theorists and philosophers have developed for thinking about justice and injustice. It then draws on these frameworks to illuminate how the use of artificial intelligence can implicate questions of justice, with a focus on institutional discrimination, structural injustice, and epistemic injustice. Ultimately, the piece argues that the use of artificial intelligence—far from representing a decision to take power out of human hands—represents a novel way of harnessing human power, making questions of justice central to its conscientious undertaking. (shrink)

Buchanan and Darden have provided compelling reasons why philosophers of science concerned with the nature of scientific discovery should be aware of current work in artificial intelligence. This paper contends that artificial intelligence is even more than a source of useful analogies for the philosophy of discovery: the two fields are linked by interfield connections between philosophy of science and cognitive psychology and between cognitive psychology and artificial intelligence. Because the philosophy (...) of discovery must pay attention to the psychology of practicing scientists, and because current cognitive psychology adopts a computational view of mind with AI providing the richest models of how the mind works, the philosophy of discovery must also concern itself with AI models of mental operations. The relevance of the artificial intelligence notion of a frame to the philosophy of discovery is briefly discussed. (shrink)

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

This paper looks at philosophical questions that arise in the context of AI alignment. It defends three propositions. First, normative and technical aspects of the AI alignment problem are interrelated, creating space for productive engagement between people working in both domains. Second, it is important to be clear about the goal of alignment. There are significant differences between AI that aligns with instructions, intentions, revealed preferences, ideal preferences, interests and values. A principle-based approach to AI alignment, which combines these elements (...) in a systematic way, has considerable advantages in this context. Third, the central challenge for theorists is not to identify ‘true’ moral principles for AI; rather, it is to identify fair principles for alignment that receive reflective endorsement despite widespread variation in people’s moral beliefs. The final part of the paper explores three ways in which fair principles for AI alignment could potentially be identified. (shrink)

An exploration of the important philosophical issues and concerns related to artificial intelligence. The book focuses on the philosphical, rather than the technical or technological aspects of artificial intelligence.

Presupposing no familiarity with the technical concepts of either philosophy or computing, this clear introduction reviews the progress made in AI since the inception of the field in 1956. Copeland goes on to analyze what those working in AI must achieve before they can claim to have built a thinking machine and appraises their prospects of succeeding. There are clear introductions to connectionism and to the language of thought hypothesis which weave together material from philosophy, artificial (...) class='Hi'>intelligence and neuroscience. John Searle's attacks on AI and cognitive science are countered and close attention is given to foundational issues, including the nature of computation, Turing Machines, the Church-Turing Thesis and the difference between classical symbol processing and parallel distributed processing. The book also explores the possibility of machines having free will and consciousness and concludes with a discussion of in what sense the human brain may be a computer. (shrink)

인공지능에 인격의 지위를 부여할 수 있는지에 대한 찬반 논쟁에서, 인격에 대한 칸트의 관점이 종종 인용된다. 인공지능에 인격을 부여할 수 있는지에 대한 찬성 입장과 반대 입장 사이에 여러 상이한 주장들이 발견되는 한편, 양측은 종종 인격에 대한 칸트의 관점에 따르면 인공지능에는 인격이 부여될 수 없다는 해석을 공통적으로 받아들인다. 인공지능에 인격의 지위를 부여하는 것에 반대하는 입장에서는 칸트 철학에 대한 그러한 해석을 인공지능 일반에 인격의 지위를 부여해서는 안 된다는 주장을 뒷받침하는 철학적 논거 중 하나로 활용하는 반면, 인공지능에 인격의 지위를 부여하는 것에 찬성하는 입장에서는 칸트 (...) 철학에 대한 그러한 해석을 극복해야 할 인간 중심주의적 편견을 보여주는 한 사례로 활용한다. 본 논문은 찬반 양측이 종종 공유하는 해당 해석의 한계를 지적하고, 인격에 대한 칸트의 관점이 인공지능에 인격을 부여할 수 있는지의 문제에 어떠한 시사점을 줄 수 있는지에 대해 논의한다. 해당 해석은 특정 분야의 문제 해결을 위해서만 활용될 수 있는 약 인공지능에 적용되는 경우 어느 정도 설득력이 있으나, 이성적 사유와 도덕적 행위를 수행할 수 있을 것으로 상상되는 강 인공지능까지 논의의 범위에 포함되는 경우 문제적이다. 해당 해석은 칸트가 인격을 이성적 사유와 도덕적 행위의 가능성을 뒷받침하는 표상으로 제시할 뿐, 인격의 표상이 적용될 수 있는 실제 존재자의 범위에 대한 객관적 지식을 주장하지 않는다는 점을 종종 간과한다. 칸트는 인격에 대한 객관적 지식이 성립될 수 없다고 주장하므로, 인격에 대한 칸트의 관점은 인격적 존재자를 인간종의 범위 안으로 국한시키는 인간 중심주의와는 거리가 멀며, 이성적 사유와 도덕적 행위를 수행할 수 있을 것으로 상상되는 강인공지능의 출현 가능성을 부정할 논거로 활용되기 어렵다. (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)

인공 감정에 관한 철학적 탐구가 필요한 시점이다. 인간의 고유한 영역으로 간주되던 인지적 과제에서 기계의 추월을 염려하는 처지가 되자, 사람들은 이제 이성이 아니라 감정에서 인간의 고유성을 찾으려한다. 하지만 최근 인공지능 로봇에 감성을 불어넣는 작업이 새로운 화두로 떠오르고 있다. 이 글은 인공 감정의 실현가능성과 잠재적인 위험을 논의한다. 먼저, 감성 로봇의 개발 현황과 주요한 동기들을 개괄하고, 왜 로봇의 감정이 문제가 되는지 살펴본다. 진정한 감정-소유 로봇이 가능한지 검토하기 위해 감정을 선험적으로 정의하기보다는 감정이 수행하는 몇 가지 핵심 역할을 소개하고 이로부터 어떤 대상에 감정을 부여할 수 (...) 있는 기준들을 제안한다. 나는 이런 기준에 비추어 진정한 감정 로봇이 근미래에 실현될 가능성이 낮다고 주장한다. 그러나 감정-소유 로봇이 등장하기 이전이라도, 어느 정도의 자율성을 가진 로봇과 맺는 일방적 감정 소통은 잠재적으로 위험할 수 있으며, 이에 대비하는 것이 시급하다고 주장한다. (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 essay presents an analysis of different processes of machine learning: supervised, unsupervised, and semisupervised, through the prism of the epistemologies of several prominent Islamic philosophical schools. I discuss the way each school conceptualizes the ontological absolute (immortality, death, afterlife) and the way this shapes their respective epistemologies. I present an analysis of the different machine learning processes through the prism of the epistemological constructs of each of these philosophic traditions. I conclude with the argument that more scholars from the (...) Islamic philosophical tradition should engage in the debates about the development of artificial intelligence and its implications, given that many Muslim countries are among the leaders in this development and its application in everyday life. (shrink)

Determining the agency-status of machines and AI has never been more pressing. As we progress into a future where humans and machines more closely co-exist, understanding hallmark features of agency affords us the ability to develop policy and narratives which cater to both humans and machines. This paper maintains that decision-making processes largely underpin agential action, and that in most instances, these processes yield good results in terms of making good choices. However, in some instances, when faced with two (or (...) more) choices, an agent may find themselves with equal reasons to choose either - thus being presented with a tie. This paper argues that in the event of a tie, the ability to create a voluntarist reason is a hallmark feature of agency, and second, that AI, through current tie-breaking mechanisms does not have this ability, and thus fails at this particular feature of agency. (shrink)

‘도덕 행위자(moral agent)’의 개념은 전통적으로 자신의 행동에 대해 책임을 질 수 있는 자유의지를 가진 인격적 존재에 한정되어 적용되었다. 그런데 도덕적 함축을 갖는 다양한 행동을 수행할 수 있는 자율적 AI의 등장은 이러한 행위자 개념의 수정을 요구하는 것처럼 보인다. 필자는 이 논문에서 일정한 요건을 만족시키는 AI에 대해서 인격성을 전제하지 않는 기능적인 의미의 도덕 행위자 자격이 부여될 수 있다고 주장한다. 그리고 그런 한에 있어서, AI에게도 그 행위자성에 걸맞은 책임 혹은 책무성의 귀속이 가능해진다. 이러한 주장을 뒷받침하기 위하여, 본 논문은 예상되는 여러 가능한 반론들을 살펴보고 (...) 거기에 응답함으로써, AI를 자율적 행위자로 여길 수 있는 여러 근거들을 제시하는 동시에, AI에게 귀속 가능한 책임 혹은 책무성의 개념을 발전시키고자 시도한다. (shrink)

인공지능이 자율성을 가진 존재일 수 있는가? 자율성은 책임과 권리같은 관념의 선결 조건으로 오늘의 사회에서 ‘인공지능이 해내는 일’에 연관된 책임과 공헌을 배분하는 데 적용할 규범의 이론적 기반이 된다는 점에서 이 물음은 현실적으로 중요하다. 공학의 ‘자율적 에이전트’ 개념은 현행의 철학적 논의에도 영향을 미치며, 공학과 철학의 자율성 개념 간의 관계가 명료하게 인식되지 못한 까닭에 야기될 혼란의 개연성이 실재한다. 이런 현실의 문제 상황을 의식하면서, 이 논문은 앞의 물음을 가능성에 관한 물음과 정당성에 관한 물음으로 분석하고, 인공지능의 자율성에 관한 전망을 검토한다. 논의의 과정에서 ‘X가 자율성을 가진다’는 (...) 의미를 규명해야 할 필요가 확인되고, 논문은 루소와 칸트와 크리스만의 논의를 활용하여 자율성의 개념을 고찰한다. 그렇게 분석한 자율성의 개념을 인공지능의 속성에 적용해 볼 때, 칸트가 정립한 자율성 개념에 비추어 인공지능은 자율적 존재일 수 없으며, 크리스만의 서술에서 부각된 자율적 존재의 핵심 속성을 고려할 때 인공지능이나 그것으로 작동하는 로보틱 시스템이 자율성을 지니도록 하는 것은 부적절한 위험을 허용한다는 점에서 옳지 않음이 드러난다. (shrink)

Departing from popular imaginations around artificial intelligence (AI), this article engages in the I in the AI acronym but from perspectives outside of mathematics, computer science and machine learning. When intelligence is attended to here, it most often refers to narrow calculating tasks. This connotation to calculation provides AI an image of scientificity and objectivity, particularly attractive in societies with a pervasive desire for numbers. However, as is increasingly apparent today, when employed in more general areas of (...) our messy socio-cultural realities, AI- powered automated systems often fail or have unintended consequences. This article will contribute to this critique of AI by attending to Nicholas of Cusa and his treatment of intelligence. According to him, intelligence is equally dependent on an ability to handle the unknown as it unfolds in the present moment. This suggests that intelligence is organic which ties Cusa to more contemporary discussions in tech philosophy, neurology, evolutionary biology, and cognitive sciences in which it is argued that intelligence is dependent on having—and acting through—an organic body. Understanding intelligence as organic thus suggests an oxymoronic relationship to artificial. (shrink)

Report for "The Reasoner" on the conference "Philosophy and Theory of Artificial Intelligence", 3 & 4 October 2011, Thessaloniki, Anatolia College/ACT, http://www.pt-ai.org. --- Organization: Vincent C. Müller, Professor of Philosophy at ACT & James Martin Fellow, Oxford http://www.sophia.de --- Sponsors: EUCogII, Oxford-FutureTech, AAAI, ACM-SIGART, IACAP, ECCAI.

This paper discusses the problem of responsibility attribution raised by the use of artificial intelligence technologies. It is assumed that only humans can be responsible agents; yet this alone already raises many issues, which are discussed starting from two Aristotelian conditions for responsibility. Next to the well-known problem of many hands, the issue of “many things” is identified and the temporal dimension is emphasized when it comes to the control condition. Special attention is given to the epistemic condition, (...) which draws attention to the issues of transparency and explainability. In contrast to standard discussions, however, it is then argued that this knowledge problem regarding agents of responsibility is linked to the other side of the responsibility relation: the addressees or “patients” of responsibility, who may demand reasons for actions and decisions made by using AI. Inspired by a relational approach, responsibility as answerability thus offers an important additional, if not primary, justification for explainability based, not on agency, but on patiency. (shrink)

Presupposing no familiarity with the technical concepts of either philosophy or computing, this clear introduction reviews the progress made in AI since the inception of the field in 1956. Copeland goes on to analyze what those working in AI must achieve before they can claim to have built a thinking machine and appraises their prospects of succeeding.There are clear introductions to connectionism and to the language of thought hypothesis which weave together material from philosophy, artificial intelligence (...) and neuroscience. John Searle's attacks on AI and cognitive science are countered and close attention is given to foundational issues, including the nature of computation, Turing Machines, the Church-Turing Thesis and the difference between classical symbol processing and parallel distributed processing. The book also explores the possibility of machines having free will and consciousness and concludes with a discussion of in what sense the human brain may be a computer. (shrink)

Advanced AI systems are rapidly making their way into medical research and practice, and, arguably, it is only a matter of time before they will surpass human practitioners in terms of accuracy, reliability, and knowledge. If this is true, practitioners will have a prima facie epistemic and professional obligation to align their medical verdicts with those of advanced AI systems. However, in light of their complexity, these AI systems will often function as black boxes: the details of their contents, calculations, (...) and procedures cannot be meaningfully understood by human practitioners. When AI systems reach this level of complexity, we can also speak of black-box medicine. In this paper, we want to argue that black-box medicine conflicts with core ideals of patient-centered medicine. In particular, we claim, black-box medicine is not conducive for supporting informed decision-making based on shared information, shared deliberation, and shared mind between practitioner and patient. (shrink)

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

Historically, the dispute between empiricists and nativists in philosophy and cognitive science has concerned human and animal minds (Margolis and Laurence in Philos Stud: An Int J Philos Anal Tradit 165(2): 693-718, 2013, Ritchie in Synthese 199(Suppl 1): 159–176, 2021, Colombo in Synthese 195: 4817–4838, 2018). But recent progress has highlighted how empiricist and nativist concerns arise in the construction of artificial systems (Buckner in From deep learning to rational machines: What the history of philosophy can teach (...) us about the future of artificial intelligence. Oxford University Press.). This paper uses nativism and empiricism to address questions about the nature of artificial intelligence and its trajectory. It begins by defining the nativism/empiricism debate in terms of the generality of a system. Nativist systems have initial states with domain-specific features; empiricist systems have initial states with only domain-general features. With the debate framed in this way, it then explores a variety of arguments for nativism and empiricism in AI. These arguments revolve around two different questions which must be distinguished: whether nativism the only possible approach to developing human-level AI (HLAI); and whether nativism is the most practical approach to developing HLAI. On the first question, it argues that nativism is quite clearly not the only possible approach to developing HLAI, as is sometimes suggested. It argues that existing arguments for the necessity of nativism are unconvincing, because they analogize from poverty of the stimulus arguments about humans, while AIs often have access to much more data than humans. Then it argues that the case of evolution gives us a compelling argument against nativism. On the second, practical question, the paper argues that there is a tradeoff between the advantages of encoding innate machinery directly, and the advantages of evolving or learning it. However, as the past decade has shown, empiricism is a much more viable path to greater capability levels, given the ‘bitter lesson’ (Sutton in _Reinforcement Learning: An Introduction_. MIT press.) that encoding the ‘correct’ knowledge in AI systems is perennially outperformed by more empiricist methods that leverage large-scale data and computation. (shrink)

This paper argues that to negate the ontological difference between the natural and the artificial, is not plausible; nor is the reduction of the natural to the artificial or vice versa possible. Except if one intends to empty the semantic content of the terms and notions: “natural” and “artificial.” Most philosophical discussions on Artificial Intelligence (AI) have always been in relation to the human person, especially as it relates to human intelligence, consciousness and/or mind (...) in general. This paper, intends to broaden the conversation, by discussing AI in relation to the notions of “nature” and the “artificial.” This intention is to more critically understand the artificiality in and of artificial intelligence. To achieve this, the notion of “nature” in Aristotle’s Philosophy of Nature, has been employed as an epistemological tool in interrogating the notion of the artificial and the objectives of the science and technology of 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)

An argument with roots in ancient Greek philosophy claims that only humans are capable of a certain class of thought termed conceptual, as opposed to perceptual thought, which is common to humans, the higher animals, and some machines. We outline the most detailed modern version of this argument due to Mortimer Adler, who in the 1960s argued for the uniqueness of the human power of conceptual thought. He also admitted that if conceptual thought were ever manifested by machines, such (...) an achievement would contradict his conclusion. We revisit Adler’s criterion in the light of the past five decades of artificial-intelligence research, and refine it in view of the classical definitions of perceptual and conceptual thought. We then examine two well-publicized examples of creative works produced by AI systems and show that evidence for conceptual thought appears to be lacking in them. Although clearer evidence for conceptual thought on the part of AI systems may arise in the near future, especially if the global neuronal workspace theory of consciousness prevails over its rival, integrated information theory, the question of whether AI systems can engage in conceptual thought appears to be still open. (shrink)