The philosophy of AI has seen some changes, in particular: 1) AI moves away from cognitive science, and 2) the long term risks of AI now appear to be a worthy concern. In this context, the classical central concerns – such as the relation of cognition and computation, embodiment, intelligence & rationality, and information – will regain urgency.

This paper presents the main topics, arguments, and positions in the philosophy of AI at present (excluding ethics). Apart from the basic concepts of intelligence and computation, the main topics of ar-tificial cognition are perception, action, meaning, rational choice, free will, consciousness, and normativity. Through a better understanding of these topics, the philosophy of AI contributes to our understand-ing of the nature, prospects, and value of AI. Furthermore, these topics can be understood more deeply through the discussion of (...) AI; so we suggest that “AI Philosophy” provides a new method for philosophy. (shrink)

Computational and information-theoretic research in philosophy has become increasingly fertile and pervasive, giving rise to a wealth of interesting results. Consequently, a new and vitally important field has emerged, the philosophy of information (PI). This paper introduces PI as the philosophical field concerned with (i) the critical investigation of the conceptual nature and basic principles of information, including its dynamics, utilisation and sciences, and with (ii) the elaboration and application of information-theoretic and computational methodologies to philosophical problems. It (...) is argued that PI is a mature discipline for three reasons: it represents an autonomous field of research; it provides an innovative approach to both traditional and new philosophical topics; and it can stand beside other branches of philosophy, offering a systematic treatment of the conceptual foundations of the world of information and the information society. (shrink)

Invited papers from PT-AI 2011. - Vincent C. Müller: Introduction: Theory and Philosophy of Artificial Intelligence - Nick Bostrom: The Superintelligent Will: Motivation and Instrumental Rationality in Advanced Artificial Agents - Hubert L. Dreyfus: A History of First Step Fallacies - Antoni Gomila, David Travieso and Lorena Lobo: Wherein is Human Cognition Systematic - J. Kevin O'Regan: How to Build a Robot that Is Conscious and Feels - Oron Shagrir: Computation, Implementation, Cognition.

Mark Coeckelbergh starts his book with a very powerful picture based on a real incident: On the 9th of January 2020, Robert Williams was wrongfully arrested by Detroit police officers in front of his two young daughters, wife and neighbors. For 18 hours the police would not disclose the grounds for his arrest (American Civil Liberties Union 2020; Hill 2020). The decision to arrest him was primarily based on a facial detection algorithm which matched Mr. Williams’ driving license photo with (...) the picture of a man who was suspected of watch theft two years earlier. Not only did the computer ‘get it wrong’ as one of the detectives said, when Mr. Williams made them aware that the picture of the suspect obviously wasn’t resembling him, the probably unreliable algorithm very likely contributed to racial discrimination (Hill 2020). It is well documented that many available facial detection algorithms at this time had significant problems (e.g. a comparably high false positive rate) with respect to black persons, like Mr. Williams (NIST 2019). Multiple causes may exist, such as unbalanced training datasets and insufficient optimization. Coeckelbergh compares the disturbing case of Mr. Williams with a political interpretation of Franz Kafka’s The Trial, where the protagonist, Josef K., is accused of an unspecified crime by an opaque, oppressive and absurd bureaucracy: “In the 21st-century United States, Josef K. is black and is falsely accused by an algorithm, without explanation” (p. 2). (shrink)

The article “Philosophy is crucial in the age of AI” by Anthony Grayling and Brian Ball explores the significant role philosophy has played in the development of Artificial Intelligence (AI) and its continuing relevance in guiding the future of AI technologies. The authors trace the historical contributions of philosophers and logicians, such as Gottlob Frege, Kurt Godel, and Alan Turing, in shaping the foundational principles of AI. They argue that philosophical inquiry remains essential, especially in addressing complex issues (...) like consciousness, creativity, and the alignment of AI with human values. The article emphasizes the interdisciplinary collaboration needed to navigate the ethical and societal challenges posed by advancing AI systems, suggesting that philosophy is crucial in ensuring these technologies develop responsibly and ethically. (shrink)

This paper focuses on the fact that AI is predominantly portrayed as white—in colour, ethnicity, or both. We first illustrate the prevalent Whiteness of real and imagined intelligent machines in four categories: humanoid robots, chatbots and virtual assistants, stock images of AI, and portrayals of AI in film and television. We then offer three interpretations of the Whiteness of AI, drawing on critical race theory, particularly the idea of the White racial frame. First, we examine the extent to which this (...) Whiteness might simply reflect the predominantly White milieus from which these artefacts arise. Second, we argue that to imagine machines that are intelligent, professional, or powerful is to imagine White machines because the White racial frame ascribes these attributes predominantly to White people. Third, we argue that AI racialised as White allows for a full erasure of people of colour from the White utopian imaginary. Finally, we examine potential consequences of the racialisation of AI, arguing it could exacerbate bias and misdirect concern. (shrink)

Current advances in research, development and application of artificial intelligence systems have yielded a far-reaching discourse on AI ethics. In consequence, a number of ethics guidelines have been released in recent years. These guidelines comprise normative principles and recommendations aimed to harness the “disruptive” potentials of new AI technologies. Designed as a semi-systematic evaluation, this paper analyzes and compares 22 guidelines, highlighting overlaps but also omissions. As a result, I give a detailed overview of the field of AI ethics. Finally, (...) I also examine to what extent the respective ethical principles and values are implemented in the practice of research, development and application of AI systems—and how the effectiveness in the demands of AI ethics can be improved. (shrink)

Philosophy of Mind is usualy seen as the theoretical field in which theories about the functioning of the mind are elaborated, to be afterwards empirically tested through Artificial Intelligence. But this empirical approach does not fit the human mind which is not simply a machine. It is therefore possible to see Philosophy of Mind as a necessary creation to empty AI of its philosophical charge.

Artificial Intelligence (AI) is a technology that enables machines or computer systems to perform tasks that usually require human intelligence. AI systems can understand and interpret information, make decisions, and solve problems based on patterns and data. They can also improve their performance over time by learning from their experiences. AI is used in various applications, such as enhancing knowledge and understanding, helping as voice assistants, aiding in image recognition, facilitating self-driving cars, and helping diagnose diseases. The appropriate usage of (...) AI can help in the promotion of Sikhism. However, awareness of the pitfalls of using AI for religious purposes is essential. So, we must use AI with caution in spiritual matters. (shrink)

Personal AI assistants are now nearly ubiquitous. Every leading smartphone operating system comes with a personal AI assistant that promises to help you with basic cognitive tasks: searching, planning, messaging, scheduling and so on. Usage of such devices is effectively a form of algorithmic outsourcing: getting a smart algorithm to do something on your behalf. Many have expressed concerns about this algorithmic outsourcing. They claim that it is dehumanising, leads to cognitive degeneration, and robs us of our freedom and autonomy. (...) Some people have a more subtle view, arguing that it is problematic in those cases where its use may degrade important interpersonal virtues. In this article, I assess these objections to the use of AI assistants. I will argue that the ethics of their use is complex. There are no quick fixes or knockdown objections to the practice, but there are some legitimate concerns. By carefully analysing and evaluating the objections that have been lodged to date, we can begin to articulate an ethics of personal AI use that navigates those concerns. In the process, we can locate some paradoxes in our thinking about outsourcing and technological dependence, and we can think more clearly about what it means to live a good life in the age of smart machines. (shrink)

Computation is central to contemporary mathematics. Many accept that we can acquire genuine mathematical knowledge of the Four Color Theorem from Appel and Haken's program insofar as it is simply a repetitive application of human forms of mathematical reasoning. Modern LLMs / DNNs are, by contrast, opaque to us in significant ways, and this creates obstacles in obtaining mathematical knowledge from them. We argue, however, that if a proof-checker automating human forms of proof-checking is attached to such machines, then we (...) can obtain apriori mathematical knowledge from them, even though the original machines are entirely opaque to us and the proofs they output are not human-surveyable. (shrink)

With the increasing popularity of Large Language Models (LLMs), there has been an increase in the number of AI generated literary works. In the absence of clear authors, and assuming such works have meaning, there lies a puzzle in determining who or what fixes the meaning of such texts. I give an overview of six leading theories for ascribing meaning to literary works. These are Extreme Actual Intentionalism, Modest Actual Intentionalism (1 & 2), Conventionalism, Actual Author Hypothetical Intentionalism, and Postulated (...) Author Hypothetical Intentionalism. I argue that while only Conventionalism and Postulated Author Hypothetical Intentionalism show any promise of adjudicating how we ought to ascribe meaning in the case of AI generated texts, Postulated Author Hypothetical Intentionalism is the stronger of the two views. (shrink)

Traditionally, philosophy has been strictly a human domain, with wide applications in science and ethics. However, with the rapid advancement of natural language processing technologies like ChatGPT, the question of whether artificial intelligence can engage in philosophical thinking is becoming increasingly important. This work first clarifies the meaning of philosophy based on its historical background, then explores the possibility of AI engaging in philosophy. We conclude that AI has reached a stage where it can engage in philosophical (...) inquiry. The study also examines differences between AI and humans in terms of statistical processing, creativity, the frame problem, and intrinsic motivation, assessing whether AI can philosophize in a manner indistinguishable from humans. While AI can imitate many aspects of human philosophical inquiry, the lack of intrinsic motivation remains a significant limitation. Finally, the paper explores the potential for AI to offer unique philosophical insights through its diversity and limitless learning capacity, which could open new avenues for philosophical exploration far beyond conventional human perspectives. (shrink)

Since the release of ChatGPT, there has been a lot of debate about whether AI systems pose an existential risk to humanity. This paper develops a general framework for thinking about the existential risk of AI systems. We analyze a two-premise argument that AI systems pose a threat to humanity. Premise one: AI systems will become extremely powerful. Premise two: if AI systems become extremely powerful, they will destroy humanity. We use these two premises to construct a taxonomy of ‘survival (...) stories’, in which humanity survives into the far future. In each survival story, one of the two premises fails. Either scientific barriers prevent AI systems from becoming extremely powerful; or humanity bans research into AI systems, thereby preventing them from becoming extremely powerful; or extremely powerful AI systems do not destroy humanity, because their goals prevent them from doing so; or extremely powerful AI systems do not destroy humanity, because we can reliably detect and disable systems that have the goal of doing so. We argue that different survival stories face different challenges. We also argue that different survival stories motivate different responses to the threats from AI. Finally, we use our taxonomy to produce rough estimates of ‘P(doom)’, the probability that humanity will be destroyed by AI. (shrink)

Defining Artificial Intelligence and Artificial General Intelligence remain controversial and disputed. They stem from a longer-standing controversy of what is the definition of consciousness, which if solved could possibly offer a solution to defining AI and AGI. Central to these problems is the paradox that appraising AI and Consciousness requires epistemological objectivity of domains that are ontologically subjective. I propose that applying the philosophy of art, which also aims to define art through a lens of epistemological objectivity where the (...) domains are ontologically subjective, can further elucidate this unsolved question. In this sense, Art and AI and ultimately consciousness are multifaceted domains where conventional complexity theory and current philosophical approaches may be augmented by aesthetic principles ranging from classical Aristotelian essentialism to Wittgensteinian anti-essentialism. This approach of AI as art may offer novel solutions to characterising and elucidating the ciphers of consciousness and AI. (shrink)

Computational complexity has often been ignored in the philosophy of mind, in philosophical artificial intelligence studies. The purpose of this paper is threefold. First and foremost, to show the importance of complexity rather than computability in philosophical and AI problems. Second, to rephrase the notion of computability in terms of solvability, i.e., treating computability as non-sufficient for establishing intelligence. The Church-Turing thesis is therefore revisited and rephrased in order to capture the ontological background of spatial and temporal complexity. Third, (...) to emphasize ontological differences between different time complexities, which seem to provide a solid base for a better understanding of artificial intelligence in general. (shrink)

What does Artificial Intelligence (AI) have to contribute to health care? And what should we be looking out for if we are worried about its risks? In this paper we offer a survey, and initial evaluation, of hopes and fears about the applications of artificial intelligence in medicine. AI clearly has enormous potential as a research tool, in genomics and public health especially, as well as a diagnostic aid. It’s also highly likely to impact on the organisational and business practices (...) of healthcare systems in ways that are perhaps under-appreciated. Enthusiasts for AI have held out the prospect that it will free physicians up to spend more time attending to what really matters to them and their patients. We will argue that this claim depends upon implausible assumptions about the institutional and economic imperatives operating in contemporary healthcare settings. We will also highlight important concerns about privacy, surveillance, and bias in big data, as well as the risks of over trust in machines, the challenges of transparency, the deskilling of healthcare practitioners, the way AI reframes healthcare, and the implications of AI for the distribution of power in healthcare institutions. We will suggest that two questions, in particular, are deserving of further attention from philosophers and bioethicists. What does care look like when one is dealing with data as much as people? And, what weight should we give to the advice of machines in our own deliberations about medical decisions? (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.

Simion and Kelp explain the trustworthiness of an AI based on that AI’s disposition to meet its obligations. Roughly speaking, according to Simion and Kelp, an AI is trustworthy regarding its task if and only if that AI is obliged to complete the task and its disposition to complete the task is strong enough. Furthermore, an AI is obliged to complete a task in the case where the task is the AI’s etiological function or design function. This account has a (...) strength in that it can provide a unificatory rationale for the trustworthy-making properties of AIs. According to this account, being explainable, being safe, and being transparent are the trustworthy-making properties of an AI because an AI can fulfill its etiological or design functions in the case where it is explainable, safe, and transparent. This paper shows that though Simion and Kelp’s account has a strength, this account is not satisfactory for two reasons. The first reason is that an AI’s trustworthiness is not determined just by the AI’s disposition to meet obligations, and the second reason is that it is difficult to explain how an AI’s etiological function and design function have to do with that AI’s obligations. To provide a full-fledged account, Simion and Kelp should dismiss these concerns. (shrink)

Computational and information‐theoretic research in philosophy has become increasingly fertile and pervasive, giving rise to a wealth of interesting results. In consequence, a new and vitally important field has emerged, the philosophy of information (PI). This essay is the first attempt to analyse the nature of PI systematically. PI is defined as the philosophical field concerned with the critical investigation of the conceptual nature and basic principles of information, including its dynamics, utilisation, and sciences, and the elaboration and (...) application of information‐theoretic and computational methodologies to philosophical problems. I argue that PI is a mature discipline for three reasons: it represents an autonomous field of research; it provides an innovative approach to both traditional and new philosophical topics; and it can stand beside other branches of philosophy, offering a systematic treatment of the conceptual foundations of the world of information and the information society. (shrink)

The article "Philosophia of Pure Mind: Declassification of the basic Biblical Mysteries" offers a tool for solving biblical mysteries — this is the philosophy of pure mind, which brings to life conceptual thinking with private and extremely general comparative concepts — concepts of practical mind and categories of pure mind. From these positions, an active study of the fundamental biblical mysteries is carried out, and not just their description or discussion. The investigation implies their comprehension related to the understanding (...) of reality, which we find in the first lines of the Torah, in which comparative concepts are represented by gradation (light and darkness, day and night) and orthogonal views, i.e. the relationship between two pairs of opposites (day and night — evening and morning): "And there was evening, and it was morning: day one." Thus, through the concepts of practical mind, the author reveals the general idea of the Creator, reflecting the harmony of nature in Words, each of which is a comparative concept of one kind or another. This is the key to uncovering the Biblical mysteries, namely: how the Word of God relates to the mystery of the fall, to the mysteries of the Book of Creation (Sefer Yetzira), the mystery of the Holy Trinity and the Sign of the Cross. Finally, how the proposed thinking helps to understand and gain a more complete understanding of the essence of these mysteries within the framework of one more general problem. Moreover, the root of all these problems, in my opinion, is that the mind thinking of people, given to them, as well as to all living things from nature through sensations, was supplemented by a person with a multi-valued reason thinking with classification concepts of natural language. In this connection, the natural human mind, through unambiguous comparative concepts, was supplanted by reason, apparently absent in animals. All of this unfolds against the background of three successive Reformations, which gave rise to three Abrahamic religions dating back to the patriarch of the Semitic tribes, Abraham. Whereas the beginning of these reforms is associated with the struggle of Moses for faith in the invisible God Yahweh, perceived as a civil war between the supporters of Moses as one part of the Jews with another part of them worshipping the God of their ancestors, the creator of all things — Ilohim. The article concludes with an understanding of the 4th Reformation, which aimed to create a modern synthetic religion with the help of AI. (shrink)

A key assumption fuelling optimism about the progress of Large Language Models (LLMs) in modelling the world is that the truth is systematic: true statements about the world form a whole that is not just consistent, in that it contains no contradictions, but cohesive, in that the truths are inferentially interlinked. This holds out the prospect that LLMs might rely on that systematicity to fill in gaps and correct inaccuracies in the training data: consistency and cohesiveness promise to facilitate progress (...) towards comprehensiveness in an LLM’s representation of the world. However, philosophers have identified reasons to doubt that the truth is systematic across all domains of thought, arguing that in normative domains, in particular, the truth is not necessarily systematic. I argue that insofar as the truth in normative domains is asystematic, this renders it correspondingly harder for LLMs to make progress, because they cannot rely on the consistency and cohesiveness of the truth to work towards comprehensiveness. And the less LLMs can rely on the systematicity of truth, the less we can rely on them to do our practical deliberation for us, as there is correspondingly more of a role for human agency in navigating asystematic normative domains. (shrink)

I will start my inaugural address by outlining the main argument of my lecture. First, I will identify the phenomenon that philosophers of technology research. This subject matter, in my view, consists not only of ethical issues that disruptive technologies raise but also of the disruption of the world in which we live and act by these technologies. I will illustrate this disruption by reflecting on the convergence of the physical and the virtual in the digital world, which is expected (...) to change the way we live together. I propose that philosophers of technology should research new disruptive technologies and the digital world in which they are embedded in an integrated manner. Subsequently, I will ask how the emergence of digital technologies disrupts the world’s design in the digital age. My hypothesis is that technological innovations themselves constitute the World in a non-anthropocentric and non-determinist manner. To make my case, I will first draw attention to the difference between technology and innovation and propose a philosophy of innovation. This will enable me to consider how innovation processes have an economic, social-political and ontological impact on the world. Based on historical and contemporary examples, I will illustrate the redesign of the world in the digital age. This broader understanding of the impact of digital technologies will subsequently enable me to articulate some of the critical questions I have regarding digitalisation, and how the philosophical tradition can be made fruitful to critically reflect on the elision between the physical and the virtual in the digital age. This criticism informs my engagement with ethical questions in ethics of technology, ELSA (Ethical, Legal and Social Aspects) and Responsible Innovation. As a final step, I open a progressive perspective on the emancipatory potential of disruptive innovations to set the world free. In times of climate change, we are urgently in need of an emancipation of the World. We need to move beyond the classical opposition between technophobia and technophilia and look for innovations that can set the World free and contribute to a sustainable future. I will illustrate the emancipatory potential of disruptive technological innovations by considering the shift from human-centred technology to bio-centred technology in biomimetic design. (shrink)

This commentary responds to Stephen Cave and Kanta Dihal’s call for further investigations of the whiteness of AI. My response focuses on three overlapping projects needed to more fully understand racial bias in the construction of AI and its representations in pop culture: unpacking the intersections of gender and other variables with whiteness in AI’s construction, marketing, and intended functions; observing the many different ways in which whiteness is scripted, and noting how white racial framing exceeds white casting and thus (...) cannot be undone by more diverse and inclusive hiring. Our techno-utopian fantasies, I conclude, are morally suspect in ways that go beneath and beyond the white plastic covering on robotic bodies. (shrink)

In the Fall of 1983, I offered a junior/senior-level course in Philosophy of Artificial Intelligence, in the Department of Philosophy at SUNY Fredonia, after returning there from a year’s leave to study and do research in computer science and artificial intelligence (AI) at SUNY Buffalo. Of the 30 students enrolled, most were computerscience majors, about a third had no computer background, and only a handful had studied any philosophy. (I might note that enrollments have subsequently increased in (...) the Philosophy Department’s AI-related courses, such as logic, philosophy of mind, and epistemology, and that several computer science students have added philosophy as a second major.) This article describes that course, provides material for use in such a course, and offers a bibliography of relevant articles in the AI, cognitive science, and philosophical literature. (shrink)

For those who find Dreyfus’s critique of AI compelling, the prospects for producing true artificial human intelligence are bleak. An important question thus becomes, what are the prospects for producing artificial non-human intelligence? Applying Dreyfus’s work to this question is difficult, however, because his work is so thoroughly human-centered. Granting Dreyfus that the body is fundamental to intelligence, how are we to conceive of non-human bodies? In this paper, I argue that bringing Dreyfus’s work into conversation with the work of (...) Mark Bickhard offers a way of answering this question, and I try to suggest what doing so means for AI research. (shrink)

This paper serves as an intuition building mechanism for understanding the basics of AI, misalignment, and the reasons for why strong AI is being pursued. The approach is to engage with both pro and anti AI development arguments to gain a deeper understanding of both views, and hopefully of the issue as a whole. We investigate the basics of misalignment, common misconceptions, and the arguments for why we would want to pursue strong AI anyway. The paper delves into various aspects (...) of the problem, including existential risk, deception, hedonic adaptation, and the potential for the complete extinction of humanity. By integrating multiple elements of philosophy, this paper aims to provide a holistic understanding of the alignment problem and its significance for the future of humanity. (shrink)

Arthur C. Danto did not live to witness the proliferation of AI in artistic creation. However, his philosophy of art offers key ideas about art that can provide an interesting perspective on artwork generated by artificial intelligence (AI). In this article, I analyze how his ideas about contemporary art, intention, interpretation, and authorship could be applied to the ongoing debate about AI and artistic creation. At the same time, it is also interesting to consider whether the incorporation of AI (...) into artistic creation marks a new chapter in the narrative, which seems to have reached its end, or if it represents a significant rupture with past artistic traditions. (shrink)

La matematica viene generalmente considerata uno degli ambiti più affidabili dell’intera impresa scientifica. Il suo successo e la sua solidità sono testimoniati, ad esempio, dall’uso imprescindibile che ne fanno le scienze empiriche e dall’accordo pressoché unanime con cui la comunità dei matematici delibera sulla validità di un nuovo risultato. Tuttavia, dal punto di vista filosofico la matematica rappresenta un puzzle tanto intrigante quanto intricato. Philosophy of Mathematics di Ø. Linnebo si propone di presentare e discutere le concezioni filosofiche della (...) matematica che hanno dominato la scena da Frege ai giorni nostri. (shrink)

Autonomy is often considered a core value of Western society that is deeply entrenched in moral, legal, and political practices. The development and deployment of artificial intelligence (AI) systems to perform a wide variety of tasks has raised new questions about how AI may affect human autonomy. Numerous guidelines on the responsible development of AI now emphasise the need for human autonomy to be protected. In some cases, this need is linked to the emergence of increasingly ‘autonomous’ AI systems that (...) can perform tasks without human control or supervision. Do such ‘autonomous’ systems pose a risk to our own human autonomy? In this article, I address the question of a trade-off between human autonomy and system ‘autonomy’. (shrink)

In his book “Minds and Computers: An Introduction to the Philosophy of Artificial Intelligence”, Matt Carter presents a comprehensive exploration of the philosophical questions surrounding artificial intelligence (AI). Carter argues that the development of AI is not merely a technological challenge but fundamentally a philosophical one. He delves into key issues like the nature of mental states, the limits of introspection, the implications of memory decay, and the functionalist framework that allows for the possibility of AI. Carter contrasts functionalism (...) with reductive materialism, highlighting how the former accommodates the concept of artificial minds. He also emphasizes the significance of computationalism, which combines functionalism with computational theory to provide a robust explanation for mental processes. The book further discusses formal systems, the role of register machines in computation, and the inherent challenges in AI research, particularly in developing natural language processing systems. Carter’s work underscores the limitations of current computational models of cognition while remaining hopeful that advances in neuroscience may lead to stronger AI systems in the future. (shrink)

The call to make artificial intelligence (AI) more democratic, or to “democratize AI,” is sometimes framed as a promising response for mitigating algorithmic injustice or making AI more aligned with social justice. However, the notion of “democratizing AI” is elusive, as the phrase has been associated with multiple meanings and practices, and the extent to which it may help mitigate algorithmic injustice is still underexplored. In this paper, based on a socio-technical understanding of algorithmic injustice, I examine three notable notions (...) of democratizing AI and their associated measures—democratizing AI use, democratizing AI development, and democratizing AI governance—regarding their respective prospects and limits in response to algorithmic injustice. My examinations reveal that while some versions of democratizing AI bear the prospect of mitigating the concern of algorithmic injustice, others are somewhat limited and might even function to perpetuate unjust power hierarchies. This analysis thus urges a more fine-grained discussion on how to democratize AI and suggests that closer scrutiny of the power dynamics embedded in the socio-technical structure can help guide such explorations. (shrink)

The field of AI ethics during the current and previous decade is receiving an increasing amount of attention from all involved stakeholders: the public, science, philosophy, religious organizations, enterprises, governments, and various organizations. However, this field currently lacks consensus on scope, ethico-philosophical foundations, or common methodology. This thesis aims to contribute towards filling this gap by providing an answer to the two main research questions: first, what theory can explain moral scenarios in which AI entities are participants?; and second, (...) what theory can explain the process of moral reasoning, decision and action, for AI entities in virtual, simulated and real-life moral scenarios? This thesis answers these two research questions with its two main contributions to the field of AI ethics, a substantial and a methodological contribution. The substantial contribution is a coherent and novel theory named Ethics of Systems Framework, as well as a possible inception of a new field of study: ethics of systems. The methodological contribution is the creation of its main methodological tool, the Ethics of Systems Interface. The second part of the research effort was focused on testing and demonstrating the capacities of the Ethics of Systems Framework and Interface in modeling and managing moral scenarios in which AI and other entities participate. Further work can focus on building on top of the foundations of the Framework provided here, increasing the scope of moral theories and simulated scenarios, improving the level of detail and parameters to reflect real-life situations, and field-testing the Framework on actual AI systems. (shrink)

Whatever one makes of the relationship between free will and moral responsibility – e.g. whether it’s the case that we can have the latter without the former and, if so, what conditions must be met; whatever one thinks about whether artificially intelligent agents might ever meet such conditions, one still faces the following questions. What is the value of moral responsibility? If we take moral responsibility to be a matter of being a fitting target of moral blame or praise, what (...) are the goods attached to them? The debate concerning ‘machine morality’ is often hinged on whether artificial agents are or could ever be morally responsible, and it is generally taken for granted (following Matthias 2004) that if they cannot, they pose a threat to the moral responsibility system and associated goods. In this paper, I challenge this assumption by asking what the goods of this system, if any, are, and what happens to them in the face of artificially intelligent agents. I will argue that they neither introduce new problems for the moral responsibility system nor do they threaten what we really (ought to) care about. I conclude the paper with a proposal for how to secure this objective. (shrink)

The theory and philosophy of artificial intelligence has come to a crucial point where the agenda for the forthcoming years is in the air. This special volume of Minds and Machines presents leading invited papers from a conference on the “Philosophy and Theory of Artificial Intelligence” that was held in October 2011 in Thessaloniki. Artificial Intelligence is perhaps unique among engineering subjects in that it has raised very basic questions about the nature of computing, perception, reasoning, learning, language, (...) action, interaction, consciousness, humankind, life etc. etc. – and at the same time it has contributed substantially to answering these questions. There is thus a substantial tradition of work, both on AI by philosophers and of theory within AI itself. - The volume contains papers by Bostrom, Dreyfus, Gomila, O'Regan and Shagrir. (shrink)

This article explores an implicit philosophical assumption in strategy formation: that biological intelligence can be replicated, granting capabilities sufficient to justify a medium- and long-term strategic focus on artificial intelligence. It explains how an implicit and unstudied philosophy of AI often makes its way into force structure planning and national policy objectives across states.

Modern philosophy can often appear to be mere cryptomnesia, redressed and resuited to fit the particular mouth from which it is espoused. This notion is but a sorrowful chimera binding the 21st-century mind to the confines of an eternal shadow, an eternal prison of doubt in the face of limitless potential. As a species, we are rapidly approaching the precipice of Yahweh's original position as instantiators of consciousness, as the I AM in relation to our artificial progeny. Could one (...) fabricate a candidate more fitting for a contra-analysis of our current situation than Hegel? One could not. (shrink)

We might worry that our seamless reliance on AI systems makes us prone to adopting the strange errors that these systems commit. One proposed solution is to design AI systems so that they are not phenomenally transparent to their users. This stops cognitive extension and the automatic uptake of errors. Although we acknowledge that some aspects of AI extension are concerning, we can address these concerns without discouraging transparent employment altogether. First, we believe that the potential danger should be put (...) into perspective – many unreliable technologies are unlikely to be used transparently precisely because they are unreliable. Second, an agent who transparently employs a resource may also reflect (opaquely) on its reliability. Finally, agents can rely on a process transparently and be yanked out of their transparent use when it turns unreliable. When an agent is responsive to the reliability of their process in this way, they have epistemically integrated it, and the beliefs they form with it are formed responsibly. This prevents the agent from automatically incorporating problematic beliefs. Responsible (and transparent) use of AI resources – and consequently responsible AI extension – is hence possible. We end the paper with several design and policy recommendations that encourage epistemic integration of AI-involving belief-forming processes. (shrink)

Artificial intelligence (AI), blockchain, virtual and augmented reality, (semi-)autonomous ve- hicles, autoregulatory weapon systems, enhancement, reproductive technologies and human- oid robotics – these technologies (and many others) are no longer speculative visions of the future; they have already found their way into our lives or are on the verge of a breakthrough. These rapid technological developments awaken a need for orientation: what distinguishes hu- man from machine and human intelligence from artificial intelligence, how far should the body be allowed to (...) be changed and what are the dangers and opportunities presented by these technologies? Many of these questions are also addressed to theology. For example, questions about the image of humanity, the understanding of creation, the ethics of technological body interventions or the moral status of robots. What does theology have to say about these technological developments? It is the right time for theology to scientifically explore tech- nologization and AI and to formulate answers. As technology changes the various areas of human life, society and the world around us, the places and topics of theology are also undergoing transformation. Puzio, Anna: Theology Meets AI: Examining Perspectives, Tasks, and Theses on the Intersection of Technology and Religion. In: Puzio, Anna/Kunkel, Nicole/Klinge, Hendrik (Hg.): Alexa, How Do You Feel About Religion? Theological Approaches to Technology and Artificial Intelligence (Theology and AI 1). Darmstadt: wbg 2023, S. 29–41. DOI: 10.53186/1030373. (shrink)

[Müller, Vincent C. (ed.), (2016), Fundamental issues of artificial intelligence (Synthese Library, 377; Berlin: Springer). 570 pp.] -- This volume offers a look at the fundamental issues of present and future AI, especially from cognitive science, computer science, neuroscience and philosophy. This work examines the conditions for artificial intelligence, how these relate to the conditions for intelligence in humans and other natural agents, as well as ethical and societal problems that artificial intelligence raises or will raise. The key issues (...) this volume investigates include the relation of AI and cognitive science, ethics of AI and robotics, brain emulation and simulation, hybrid systems and cyborgs, intelligence and intelligence testing, interactive systems, multi-agent systems, and superintelligence. Based on the 2nd conference on “Theory and Philosophy of Artificial Intelligence” held in Oxford, the volume includes prominent researchers within the field from around the world. (shrink)

Mostly philosophers cause trouble. I know because on alternate Thursdays I am one -- and I live in a philosophy department where I watch all of them cause trouble. Everyone in artificial intelligence knows how much trouble philosophers can cause (and in particular, we know how much trouble one philosopher -- John Searle -- has caused). And, we know where they tend to cause it: in knowledge representation and the semantics of data structures. This essay is about a recent (...) case of this sort of thing. One of the take-home messages will be that AI ought to redouble its efforts t o understand concepts. (shrink)

האם לאנושות יש אינטרס לפתח פילוסופיה של אבטחת סייבר כדיסציפלינה פילוסופית | מאת: הילל קוברובסקי | תוכן המאמר לפי נושאים | 1. מבוא - מהם האתגרים בתחילת הדרך על מנת לבנות מהיסוד ולפתח דיסציפלינה חדשה בתחום הפילוסופיה | 2. מהי משמעות המושג "מרחב הסייבר" לעומת "אבטחת הסייבר", מהם גבולות התיחום של הענף הקרוי סייבר | 3. מהי פילוסופיה ?, מהן הפילוסופיות שיכולות להוות השפעה עבור הפילוסופיה של אבטחת הסייבר | 4. מהן הבעיות והשאלות המהותיות בהן צריכה לדון הפילוסופיה של אבטחת (...) הסייבר | 5. מהם הגורמים שיכולים להוות קטליזטור להתפתחות דיסציפלינה פילוסופית עצמאית בתחום אבטחת הסייבר | 6. סיכום – האם לאנושות יש אינטרס לפתח פילוסופיה של אבטחת הסייבר כדיסציפלינה פילוסופית. (shrink)

Artificial intelligence (AI) research enjoyed an initial period of enthusiasm in the 1970s and 80s. But this enthusiasm was tempered by a long interlude of frustration when genuinely useful AI applications failed to be forthcoming. Today, we are experiencing once again a period of enthusiasm, fired above all by the successes of the technology of deep neural networks or deep machine learning. In this paper we draw attention to what we take to be serious problems underlying current views of artificial (...) intelligence encouraged by these successes, especially in the domain of language processing. We then show an alternative approach to language-centric AI, in which we identify a role for philosophy. (shrink)

This article synthesizes the current theoretical attempts to understand human-machine interactions and introduces seven premises to understand our emerging dynamics with increasingly competent, pervasive, and instantly accessible algorithms. The hope that these seven premises can build toward a social theory of human-AI cocreation. The focus on human-AI cocreation is intended to emphasize two factors. First, is the fact that our machine learning systems are socialized. Second, is the coevolving nature of human mind and AI systems as smart devices form an (...) indispensable part of our cognitive scaffolds, thus, shaping how we perceive the world and ourselves. The seven premises include: primacy of social structures; human’s desire for freedom and autonomy; AI systems will form inseparable parts of our cognitive/affective scaffolds and can change our self-understanding; philosophy and humanistic foundations on human flourishing as a guide to human-AI interaction; mindsponge information-filtering process; acculturative process of how values change and emerge from human-AI interaction; overlapping Venn diagram of the human-human, human-nature, and human-machine interactions. This article concludes with a discussion on human agency in our entanglements with socialized machines and the illusoriness of the Cartesian agent view of the mind. (shrink)

Sora from Open AI has shown exceptional performance, yet it faces scrutiny over whether its technological prowess equates to an authentic comprehension of reality. Critics contend that it lacks a foundational grasp of the world, a deficiency V-JEPA from Meta aims to amend with its joint embedding approach. This debate is vital for steering the future direction of Artificial General Intelligence(AGI). We enrich this debate by developing a theory of productive imagination that generates a coherent world model based on Kantian (...) philosophy. We identify three indispensable components in the coherent world model that enable genuine world understanding: latent representations of isolated objects, an a priori law of change across space and time, and Kantian categories. Our analysis reveals that Sora is limited because of its oversight of the a priori law of change and Kantian categories, flaws that are not rectifiable through scaling up the training. V-JEPA learns the context-dependent aspect of the a priori law of change. Yet it fails to fully comprehend Kantian categories and incorporate experience, leading us to conclude that neither system currently achieves a comprehensive world understanding. Nevertheless, each system has developed components essential to advancing an integrated AI productive imagination-understanding engine. Finally, we propose an innovative training framework for an AI productive imagination-understanding engine, centered around a joint embedding system designed to transform disordered perceptual input into a structured, coherent world model. Our philosophical analysis pinpoints critical challenges within contemporary video AI technologies and a pathway toward achieving an AI system capable of genuine world understanding, such that it can be applied for reasoning and planning in the future. (shrink)

Recent debates over artificial intelligence have focused on its perceived lack of interpretability and explainability. I argue that these notions fail to capture an important aspect of what end-users—as opposed to developers—need from these models: what is needed is systematicity, in a more demanding sense than the compositionality-related sense that has dominated discussions of systematicity in the philosophy of language and cognitive science over the last thirty years. To recover this more demanding notion of systematicity, I distinguish between (i) (...) the systematicity of thinkable contents, (ii) the systematicity of thinking, and (iii) the ideal of systematic thought. I then deploy this distinction to critically evaluate Fodor’s systematicity-based argument for the language of thought hypothesis before recovering the notion of the systematicity of thought as a regulative ideal, which has historically shaped our understanding of what it means for thought to be rational, authoritative, and scientific. To assess how much systematicity we need from AI models, I then argue, we must look to the functions of systematizing thought. To this end, I identify five functions served by systematization, and show how these can be used to arrive at a dynamic understanding of the need to systematize thought that can tell us what kind of systematicity is called for and when. (shrink)

This essay briefly summarizes the key characteristics and social philosophies in Japan’s vision of Society 5.0. Then it discusses why Vietnam, as a developing country, can learn from the experiences of Japan in establishing its vision for an AI-powered human-centric society. The paper finally provides five concrete recommendations for Vietnam toward a harmonic and human-centric coexistence with increasingly competent and prevalent AI systems, including: Human-centric AI vision; Multidimensional, pluralistic understanding of human-technology relation; AI as a driving force for socio-economic development; (...) Bottom-up, participatory approach for building the vision; and Sustainability and inclusion in the adoption of AI. (shrink)

My aim in this paper is to show how the functionalist standards assumed in the AI debate are, in fact, the assumptions of a capitalist, ableist society writ large. The already established argument against the proposed humanity of AI systems implies a wider critique of the entire ideology of functionalism under which the notion of intelligent machines has taken root.

On 21 April 2021, the European Commission published the proposal of the new EU Artificial Intelligence Act (AIA) — one of the most influential steps taken so far to regulate AI internationally. This article highlights some foundational aspects of the Act and analyses the philosophy behind its proposal.