Since the second half of the XXth century, researchers in cybernetics and AI, neural nets and connectionism, Artificial Life and new robotics have endeavoured to build different machines that could simulate functions of living organisms, such as adaptation and development, problem solving and learning. In this book these research programs are discussed, particularly as regard the epistemological issues of the behaviour modelling. One of the main novelty of this book consists of the fact that certain projects involving the building (...) of simulative machine models before the advent of cybernetics are been investigated for the first time, on the basis of little known, and sometimes completely forgotten or unpublished, texts and figures. These pre-cybernetics projects can be considered as steps toward the “discovery” of a modelling methodology that has been fully developed by those more recent research programs, and that shares some of their central goals and key methodological proposals. -/- More info in Springer link: http://www.springer.com/new+%26+forthcoming+titles+%28default%29/book/978-1-4020-0606-7 -/- This book is the English translation of La scoperta dell'artificiale, Dunod/Masson, Milan, 1998. (shrink)

Reuben Hersh confided to us that, about forty years ago, the late Paul Cohen predicted to him that at some unspecified point in the future, mathematicians would be replaced by computers. Rather than focus on computers replacing mathematicians, however, our aim is to consider the (im)possibility of human mathematicians being joined by “artificial mathematicians” in the proving practice—not just as a method of inquiry but as a fellow inquirer.

In this paper we want to analyze some philosophical and epistemological connections between a new kind of technology recently developed within robotics, and the previous mechanical approach. A new paradigm about machine-design in robotics, currently defined as ‘Embodied Intelligence’, has recently been developed. Here we consider the debate on the relationship between the hand and the intellect, from the perspective of the history of philosophy, aiming at providing a more suitable understanding of this paradigm. The new bottom-up approach to design (...) is deeply rooted in a new kind of empiricism, which tries to overcome issues connected with the previous approach strongly committed with the Artificial Intelligence (AI) debate and its origin. Since Turing’s time, the AI debate showed a rationalistic bias which remained undisputed until now. The paradigm shift we are witnessing nowadays is a reply to that bias in order to achieve not only a better way to design robots, but also to understand some underlying epistemological remarks. (shrink)

Can artificial entities be worthy of moral considerations? Can they be artificial moral agents (AMAs), capable of telling the difference between good and evil? In this essay, I explore both questions—i.e., whether and to what extent artificial entities can have a moral status (“the machine question”) and moral agency (“the AMA question”)—in light of Kazuo Ishiguro’s 2021 novel Klara and the Sun. I do so by juxtaposing two prominent approaches to machine morality that are central to the (...) novel: the (1) view “from within,” including the standard (or “metaphysical”) perspective on moral agency, and the (2) view “from outside,” which includes behaviorism, functionalism and the social-relational perspective. Importantly, while the story illustrates both views, it exposes the epistemological vulnerability of the first in relation to the practical and social reality imposed by the second. That is, regardless of what metaphysical properties the Artificial Friend Klara can be said to have (from within), her moral status as well as agency ultimately depend on the views of others (from outside), including the others’ own epistemic beliefs about the nature of consciousness and personhood. (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)

The demarcation of pseudoscience has been one of the most important philosophical tasks since the 1960s. During the 1980s, an atmosphere of defeatism started to spread among philosophers of science, some of them claimed the failure of the demarcation project. I defend that the more auspicious approach to the problem might be through the intellectual character of epistemic agents, i.e., from the point of view of vice epistemology. Unfortunately, common lists of undesirable character features are usually based on a (...) priori reasoning, and therefore might be considered artificial or too vague. When we base our position on contemporary behavioural sciences, we can see that the epistemic character of believers in pseudoscience is for the most part determined by two related factors. Firstly, these epistemic agents show a higher level of cognitive laziness. By this I mean an inability or unwillingness to engage in reflective thinking and a reluctance to account for counterevidence. Secondly, they yield more easily to metacognitive overconfidence. This can be broadly understood as so-called “knowledge illusion”, the inability to recognize one’s own intellectual limits. The deficiency usually stems from a misunderstanding of the division of cognitive labour and of the agent’s role in epistemic society. I find the proposed epistemological approach to pseudoscience crucial. Only if we understand the descriptive aspects of the problem, can we think of normative solutions to it. (shrink)

Growing technological advances in intelligent artifacts and bitter experiences of the past have emphasized the need to use and operate ethics in this field. Accordingly, it is vital to discuss the ethical integrity of having intelligent artifacts. Concerning the method of gathering materials, the current study uses library and documentary research followed by attribution style. Moreover, descriptive analysis is employed in order to analyze data. Explaining and criticizing the opposing views in this field and reviewing the related literature, it is (...) concluded that the proof of the ethical integrity of the intelligent artifacts is possible due to the specific features of these artifacts and their own moral system. (shrink)

This paper argues that whereas philosophical discussions of first-person methods often turn on the veridicality of first-person reports, more attention should be paid to the experimental circumstances under which the reports are generated, and to the purposes of designing such experiments. After pointing to the ‘constructedness’ of first-person reports in the science of perception, I raise questions about the criteria by which to judge whether the reports illuminate something about the nature of perception. I illustrate this point with a historical (...) debate between Gestalt psychologist and atomists, both of whom used first-person methods to investigate perception. (shrink)

Modern life sciences research is increasingly relying on artificial intelligence (AI) approaches to model biological systems, primarily centered around the use of machine learning (ML) models. Although ML is undeniably useful for identifying patterns in large, complex data sets, its widespread application in biological sciences represents a significant deviation from traditional methods of scientific inquiry. As such, the interplay between these models and scientific understanding in biology is a topic with important implications for the future of scientific research, yet (...) it is a subject that has received little attention. Here, we draw from an epistemological toolkit to contextualize recent applications of ML in biological sciences under modern philosophical theories of understanding, identifying general principles that can guide the design and application of ML systems to model biological phenomena and advance scientific knowledge. We propose that conceptions of scientific understanding as information compression, qualitative intelligibility, and dependency relation modelling provide a useful framework for interpreting ML-mediated understanding of biological systems. Through a detailed analysis of two key application areas of ML in modern biological research – protein structure prediction and single cell RNA-sequencing – we explore how these features have thus far enabled ML systems to advance scientific understanding of their target phenomena, how they may guide the development of future ML models, and the key obstacles that remain in preventing ML from achieving its potential as a tool for biological discovery. Consideration of the epistemological features of ML applications in biology will improve the prospects of these methods to solve important problems and advance scientific understanding of living systems. (shrink)

Artificial intelligence has historically been conceptualized in anthropomorphic terms. Some algorithms deploy biomimetic designs in a deliberate attempt to effect a sort of digital isomorphism of the human brain. Others leverage more general learning strategies that happen to coincide with popular theories of cognitive science and social epistemology. In this paper, I challenge the anthropomorphic credentials of the neural network algorithm, whose similarities to human cognition I argue are vastly overstated and narrowly construed. I submit that three alternative (...) supervised learning methods—namely lasso penalties, bagging, and boosting—offer subtler, more interesting analogies to human reasoning as both an individual and a social phenomenon. Despite the temptation to fall back on anthropomorphic tropes when discussing AI, however, I conclude that such rhetoric is at best misleading and at worst downright dangerous. The impulse to humanize algorithms is an obstacle to properly conceptualizing the ethical challenges posed by emerging technologies. (shrink)

Μοναδική μελέτη και προσέγγιση της θεωρίας της γνώσης, για την παγκόσμια βιβλιογραφία, της διαλεκτικής πορείας της σκέψης από την λογική πλευρά της και της μελλοντικής μορφής που θα πάρουν οι διαλεκτικές δομές της, στην αδιαίρετη ενότητα γνωσιοθεωρίας, λογικής και διαλεκτικής, με την «μέθοδο του διαλεκτικού υλισμού». Έργο βαρύ με θέμα εξαιρετικά δύσκολο διακατέχεται από πρωτοτυπία και ζωντάνια που γοητεύει τον κάθε ανήσυχο στοχαστή από τις πρώτες γραμμές. Unique study and approach of the theory of knowledge, the world literature, the dialectic (...) course of thought from the logical side and the future form of its dialectical structures, the indivisible unity of knowledge, logic and dialectics, with the "method of dialectical materialism ". A heavy work on an extremely difficult subject is possessed by originality and liveliness that captivates every restless thinker from the first lines..."Εδώ ακριβώς, όπως έχουμε ξαναπεί, βρίσκεται το πρόβλημα. Η διαλεκτική λογική είναι ήδη το ξεπέρασμα της τυπικής λογικής σαν όργανο για τη σύλληψη της πραγματικότητας. Εμείς όμως θέλουμε να την κάνουμε να έχει «ακρίβεια» στα συμπεράσματά της. Και τότε αντιμετωπίζουμε το πρόβλημα που έχει επισημάνει ο Lenine, πως δηλαδή: όχι το αυτονόητο γεγονός της «κίνησης» του κόσμου, αλλά το «πως» να εκφράσουμε την κίνηση αυτή με τις έννοιες, με τις κρίσεις και τους συλλογισμούς και προχωρώντας πιο πέρα, με τη δυνατότητα που προσφέρεται, ύστερα από το Hegel, από τη φορμαλοποίηση κα αξιωματικοποίηση της τυπικής λογικής, να τις εκφράσουμε «συντακτικά» διατυπώνοντας την μεταβολή. Κι αυτός είναι ο «κόμπος» που πρέπει να λυθεί: όχι μονάχα πάνω στη σημαντική περιοχή, αλλά και στη συντακτική. Γιατί οι έννοιες, οι κρίσεις κι οι συλλογισμοί, αφού ήδη εκφράζονται από την τυπική λογική με σύμβολα ικανά να μας δώσουν, με το συνδυασμό τους μονάχα, καινούρια συμπεράσματα, αλλά ταυτόχρονα και τον «έλεγχο» (από την άποψη της τυπικής αλήθειας) των συλλογισμών μας, το κάνουν αυτό πάνω σε προτάσεις που εκφράζουν την ακινησία και τη σταθερότητα. Εδώ, το «μόνο» που χρειάζεται είναι να δώσουμε κίνηση και ζωή στο σύστημα της τυπικο-στατικής λογικής, έτσι που οι προτάσεις της με το συμβολισμό τους να αναφέρονται και στις διαδοχικά επόμενες μέσα στο χρόνο τιμές αλήθειας. Οι προτάσεις, με ενδιάμεσο τη σκέψη πάντοτε, αφού στέκονται όχι μονάχα απέναντι σε μια ακίνητη στιγμή της ροής του κόσμου, αλλά και ταυτόχρονα απέναντι σ' ένα αδιάκοπα μεταβαλλόμενο περιεχόμενο, απέναντι στις αντικειμενικές διακυμάνσεις της πραγματικότητας, θα πρέπει και οι προτάσεις αυτές να πιάνουν ταυτόχρονα: το στατικό και το ρέον. Το στατικό, σα στιγμή ταυτοποίησης και αναγνώρισης των διαδοχικά «μεταβαλλόμενων ακίνητων» στιγμών του περιεχόμενου και το ρέον, σα διαδοχική ολοκλήρωση των στάνταρ-στιγμών του περιεχόμενου των αντικειμενικών προτσές. Μήπως τα μαθηματικά μας βοηθάνε εδώ;....". (shrink)

This article addresses an open problem in the area of cognitive systems and architectures: namely the problem of handling (in terms of processing and reasoning capabilities) complex knowledge structures that can be at least plausibly comparable, both in terms of size and of typology of the encoded information, to the knowledge that humans process daily for executing everyday activities. Handling a huge amount of knowledge, and selectively retrieve it according to the needs emerging in different situational scenarios, is an important (...) aspect of human intelligence. For this task, in fact, humans adopt a wide range of heuristics (Gigerenzer & Todd) due to their “bounded rationality” (Simon, 1957). In this perspective, one of the requirements that should be considered for the design, the realization and the evaluation of intelligent cognitively-inspired systems should be rep- resented by their ability of heuristically identify and retrieve, from the general knowledge stored in their artificial Long Term Memory (LTM), that one which is synthetically and contextually relevant. This requirement, however, is often neglected. Currently, artificial cognitive systems and architectures are not able, de facto, to deal with complex knowledge structures that can be even slightly comparable to the knowledge heuris- tically managed by humans. In this paper I will argue that this is not only a technological problem but also an epistemological one and I will briefly sketch a proposal for a possible solution. (shrink)

An overview of the epistemology of perception, covering the nature of justification, immediate justification, the relationship between the metaphysics of perceptual experience and its rational role, the rational role of attention, and cognitive penetrability. The published version will contain a smaller bibliography, due to space constraints in the volume.

It has been argued that our currently most satisfactory social epistemology of science can’t account for science that is based on artificial intelligence (AI) because this social epistemology requires trust between scientists that can take full responsibility for the research tools they use, and scientists can’t take full responsibility for the AI tools they use since these systems are epistemically opaque. I think this argument overlooks that much AI-based science can be done without opaque models, and that (...) agents can take full responsibility for the systems they use even if these systems are opaque. Requiring that an agent fully understand how a system works is an untenably strong condition for that agent to take full responsibility for the system and risks absolving AI developers from responsibility for their products. AI-based science need not create trust-related social epistemological problems if we keep in mind that what makes both individual scientists and their use of AI systems trustworthy isn’t full transparency of the internal processing but their adherence to social and institutional norms that ensure that scientific claims can be trusted. (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)

Recent third person approaches to thought experiments and conceptual analysis through the method of surveys are motivated by and motivate skepticism about the traditional first person method. I argue that such surveys give no good ground for skepticism, that they have some utility, but that they do not represent a fundamentally new way of doing philosophy, that they are liable to considerable methodological difficulties, and that they cannot be substituted for the first person method, since the a priori knowledge which (...) is our object in conceptual analysis can be acquired only from the first person standpoint. (shrink)

Cybernetics for the 21st Century Vol.1 is dedicated to the epistemological reconstruction of cybernetics, consisting of a series of historical and critical reflections on the subject – which according to Martin Heidegger marked the completion of Western metaphysics. In this anthology, historians, philosophers, sociologists and media studies scholars explore the history of cybernetics from Leibniz to artificial intelligence and machine learning, as well as the development of twentieth-century cybernetics in various geographical regions in the world, from the USA to (...) the Soviet Union, Latin America, France, Poland, China and Japan. The reconstruction shows the various paths of cybernetics and their socio-political implications, which remain unfamiliar to us today. It reveals more than what we thought we knew – and yet we hardly know – and allows us to understand where we are and to reflect on the future of technology, ecology and planetary politics. (shrink)

Since Thomas Kuhn’s The Structure of Scientific Revolutions (1962), historians and philosophers of science have paid increasing attention to the implications of disciplinarity. In this chapter we consider restrictions posed to interdisciplinary exchange between ecology and economics that result from a particular kind of commitment to the ideal of disciplinary purity, that is, that each discipline is defined by an appropriate, unique set of objects, methods, theories, and aims. We argue that, when it comes to the objects of study in (...) ecology and economics, ideas of disciplinary purity have been underwritten by the artificial-natural distinction. We then problematize this distinction, and thus disciplinary purity, both conceptually and empirically. Conceptually, the distinction is no longer tenable. Empirically, recent interdisciplinary research has shown the epistemological and policy-oriented benefits of dealing with models which explicitly link anthropogenic (i.e., “artificial”) and non-anthropogenic factors (i.e., “natural”). We conclude that, in the current age of the Anthropocene, it is to be expected that without interdisciplinary exchange, ecology and economics may relinquish global relevance because the distinct and separate systems to which each “pure” science was originally made to apply will only diminish over time. (shrink)

Root, branch, and blossom, attention is intertwined with epistemology. It is essential to our capacity to learn and decisive of the evidence we obtain, it influences the intellectual connections we forge and those we remember, and it is the cognitive tool whereby we enact decisions about inquiry. Moreover, because it is both an epistemic practice and a site of agency, attention is a natural locus for questions about epistemic morality. This article surveys the emerging epistemology of attention, reviewing (...) the existing literature and sketching avenues for future investigation. It also argues for a reorientation of epistemology itself. This argument is the focus of Section 1. Section 2 briefly reviews philosophical accounts of attention, Section 3 focuses on issues in traditional, individualistic epistemology, and Section 4 turns to social epistemology. (shrink)

How should one react when one has a belief, but knows that other people—who have roughly the same evidence as one has, and seem roughly as likely to react to it correctly—disagree? This paper argues that the disagreement of other competent inquirers often requires one to be much less confident in one’s opinions than one would otherwise be.

In a recent paper in this journal, Carter and Peterson raise two distinctly epistemological puzzles that arise for anyone aspiring to defend the precautionary principle. The first puzzle trades on an application of epistemic contextualism to the precautionary principle; the second puzzle concerns the compatibility of the precautionary principle with the de minimis rule. In this note, I argue that neither puzzle should worry defenders of the precautionary principle. The first puzzle can be shown to be an instance of the (...) familiar but conceptually harmless challenge of adjudicating between relevant interests to reach assessments of threats when applying the precautionary principle. The second puzzle can be shown to rely on a subtle but crucial misrepresentation of the relevant probabilities at play when applying the precautionary principle. (shrink)

The question of authenticity centers in the lives of women of color to invite and restrict their representative roles. For this reason, Gayatri Chakravorty Spivak and Uma Narayan advocate responding with strategic essentialism. This paper argues against such a strategy and proposes an epistemic understanding of the question of authentic- ity. The question stems from a kernel of truth—the connection between experience and knowledge. But a coherence theory of knowledge better captures the sociality and the holism of experience and knowledge.

The chapter discusses the issue of how we may achieve knowledge of essence. It offers a critical survey of the main theories of knowledge of essence that have been proposed within contemporary debates, particularly by Lowe, Hale, Oderberg, Elder, and Kment.

This paper applies a virtue epistemology approach to using the Internet, as to improve our information-seeking behaviours. Virtue epistemology focusses on the cognitive character of agents and is less concerned with the nature of truth and epistemic justification as compared to traditional analytic epistemology. Due to this focus on cognitive character and agency, it is a fruitful but underexplored approach to using the Internet in an epistemically desirable way. Thus, the central question in this paper is: How (...) to use the Internet in an epistemically virtuous way? Using the work of Jason Baehr, it starts by outlining nine intellectual or epistemic virtues: curiosity, intellectual autonomy, intellectual humility, attentiveness, intellectual carefulness, intellectual thoroughness, open-mindedness, intellectual courage and intellectual tenacity. It then explores how we should deploy these virtues and avoid the corresponding vices when interacting with the Internet, particularly search engines. Whilst an epistemically virtuous use of the Internet will not guarantee that one will acquire true beliefs, understanding or even knowledge, it will strongly improve one’s information-seeking behaviours. The paper ends with arguing that teaching and assessing online intellectual virtues should be part of school and university curricula, perhaps embedded in critical thinking courses, or even better, as individual units. (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)

The rapid development of artificial womb technologies means that we must consider if and when it is permissible to kill the human subject of ectogestation—recently termed a ‘gestateling’ by Elizabeth Chloe Romanis—prior to ‘birth’. We describe the act of deliberately killing the gestateling as gestaticide, and argue that there are good reasons to maintain that gestaticide is morally equivalent to infanticide, which we consider to be morally impermissible. First, we argue that gestaticide is harder to justify than abortion, primarily (...) because the gestateling is completely independent of its biological parents. Second, we argue that gestaticide is morally equivalent to infanticide. To demonstrate this, we explain that gestatelings are born in a straightforward sense, which entails that killing them is infanticide. However, to strengthen our overall claim, we also show that if gestatelings are not considered to have been born, killing them is still equivalent to killing neonates with congenital anomalies and disabilities, which again is infanticide. We conclude by considering how our discussion of gestaticide has implications for the permissibility of withdrawing life-sustaining treatment from gestatelings. (shrink)

The classical theory of computation does not represent an adequate model of reality for simulation in the social sciences. The aim of this paper is to construct a methodological perspective that is able to conciliate the formal and empirical logic of program verification in computer science, with the interpretative and multiparadigmatic logic of the social sciences. We attempt to evaluate whether social simulation implies an additional perspective about the way one can understand the concepts of program and computation. We demonstrate (...) that the logic of social simulation implies at least two distinct types of program verifications that reflect an epistemological distinction in the kind of knowledge one can have about programs. Computer programs seem to possess a causal capability (Fetzer, 1999) and an intentional capability that scientific theories seem not to possess. This distinction is associated with two types of program verification, which we call empirical and intentional verification. We demonstrate, by this means, that computational phenomena are also intentional phenomena, and that such is particularly manifest in agent-based social simulation. Ascertaining the credibility of results in social simulation requires a focus on the identification of a new category of knowledge we can have about computer programs. This knowledge should be considered an outcome of an experimental exercise, albeit not empirical, acquired within a context of limited consensus. The perspective of intentional computation seems to be the only one possible to reflect the multiparadigmatic character of social science in terms of agent-based computational social science. We contribute, additionally, to the clarification of several questions that are found in the methodological perspectives of the discipline, such as the computational nature, the logic of program scalability, and the multiparadigmatic character of agent-based simulation in the social sciences. (shrink)

A CONSTRUCTIVE CRITIQUE OF THE FOUNDATIONS OF PHILOSOPHY: Abstract of the Ph.D. Dissertation By Ramesh N. Patel June, 1970 -/- Philosophy pursues a rational explication of our understanding, experiences, and values in terms of objective truth and reality. Conspicuously, its view of rationality has been rigid and preconceived. Application of the preconceived reason in the explication of the essential features of our world fails and issues in a network of dialectical tangles. These artificially created tangles pose a unique intellectual challenge, (...) but the perennial failure to resolve them limits the intellectual response of philosophers to remaining caught in the tangles, or to taking intuitively favorable sides, or to simply denouncing the tangles as meaningless. Each is understandable. -/- Superficially, traditional philosophical reason looks like a correct tool for the explication of our world of common sense, but its applications to the world result in logical tangles showing its inadequacy. The philosopher’s faith in such reason ends up in one of two positions: abandoning our world in the interests of such reason, or embodying itself in the world through a special form of reason. Plato took the first and Aristotle took the second position. My analysis shows that Plato failed to explicate the relation between his world of Forms and our world of particulars, and, more importantly, between the Forms and the intuitive reason which grasps them. Aristotle, in my analysis, cannot conceal that the law of noncontradiction is a mere exhortation and has no descriptive necessity with respect to thought, things, or meaning. We also find such dialectical difficulties in Augustine, Hume and Strawson. -/- “Microphilosophical feasibilism” is our proposal for the best treatment, if not the definitive solution, of these problems. Instead of separating philosophical method into logic, epistemology, axiology, and metaphysics on the one side, and partitioning the projected results of philosophizing into validity, truth, valuation, and reality on the other, we need to start philosophizing with a general distinction between “method employed” and “intended result.” This distinction is not pre-colored by claims to ultimate verities. It is a direct aid to understanding. I consider the basic inevitable paradox that a philosopher should explain not only our understanding of experience but also his philosophizing itself. The circularity between “method employed” and “intended result” needs to be admitted as an initial fact about reason rather than circumvented by an implausibly claimed capacity of philosophical reason to formally transcend everything including this circularity. -/- Presuppositions are reduced to a minimum inevitable number. Being our primary microphilosophical criteria, they are reason, experience, and value in their minimal sense. They cannot be plausibly substituted or further reduced. They cannot be preferred one or more to others arbitrarily. We show how, in microphilosophy they coincide or synchronize. Jointly and basically, they form the minimum method employed. The initial, basic, intended result is called minimum feasibility. The fundamental circularity between method and result leaves no way out but to ground self-reference in such a manner that method and result “logico-genetically” coincide. Two extreme situations are avoided: “the logical zero-situation” where nothing is true or real, and “the credulous open situation” where everything is true or real. Finding a mean manifests a basic value. If the meaning of truth and reality is to be preserved, the basic value must have a clear impact and express descriptive rather than revisionary reason. -/- Several other stringent demands are raised as conditions which microphilosophy should fulfil to achieve feasibility. The final, joint, outcome of both “method” and “result,” in the thesis of microphilosophical feasibilism, is formulated thus: Self refers freely and symbolically to itself, own person, own body, material bodies, other persons’ bodies, other persons, and other selves. -/- Ramesh N. Patel Doctor of Philosophy in Philosophy conferred in June, 1970 University of New Mexico, Albuquerque, N.M. (shrink)

What is it to know someone? Epistemologists rarely take up this question, though recent developments make such inquiry possible and desirable. This paper advances an account of how such interpersonal knowledge goes beyond mere propositional and qualitative knowledge about someone, giving a central place to second-personal treatment. It examines what such knowledge requires, and what makes it distinctive within epistemology as well as socially. It assesses its theoretic value for several issues in moral psychology, epistemic injustice, and philosophy of (...) mind. And it offers an account of the complex content in play if interpersonal knowledge is to be understood in terms of its mental states and their functions. (shrink)

Thanks to mounting discussion about projected technologies’ possibly altering the species mentally and physically, philosophical investigation of what human beings are proceeds robustly. Many thinkers contend that whatever we are has little to do with how we should behave. Yet, tampering with what the human being is may tread upon human rights to be whatever one is. Rights given in widely recognized documents such as the U.N. Declaration of the Rights of Indigenous Peoples assume what humans are and need depends (...) upon ontological assumptions about human existence. Godman turns to human ontology—just what kind of beings humans are (from an angle distinct from the other two books) and how these play into rights. She is concerned with how well the social sciences accord with what we are. Gunkel homes in on a more specific moral topic than Godman's general concern with identity’s role in rights: automata moral status and rights. He enjoins us to inquire into what human rights are before we take on the new technologies’ challenge to it. Schneider’s Artificial You, while not explicitly about rights, poses a rights quandary. Certain individuals with reputable resources and practical backing explicitly seek to evolve the species as they see fit. The urgency among these works concerns how we need a sharper idea of what we are, how we should act and be treated, and how our rights fare among potential human improvements. (shrink)

Beliefs have genealogies. Can tracing a belief’s genealogy illuminate the epistemic quality of the belief? This paper sets out a general epistemology of genealogies. As it turns out, genealogies for beliefs come in two sorts: those that trace a belief to some mental event that doubles as evidence for the belief and those that do not. The former have the potential to undercut the belief, rebut the belief, or—importantly—both. The latter have the potential to reinforce the belief or rebut (...) the belief but—importantly—not undercut it. The ultimate conclusion is that there is a role for genealogies in the epistemic appraisal of our beliefs, but this role will be circumscribed by the availability of clear and compelling genealogies. (shrink)

This paper surveys the epistemology of two attitudes: faith and hope. First, I examine descriptive questions about faith and hope. Faith and hope are resilient attitudes with unique cognitive and conative components; while related, they are also distinct, notably in that hope’s cognitive component is weaker than faith’s. I then turn to faith and hope's epistemic (ir)rationality, and discuss various ways that faith and hope can be rational and irrational. Finally, I discuss the relationship between faith, hope, and knowledge: (...) while it’s controversial whether faith is compatible with knowledge, hope is not compatible with knowledge. (shrink)

We overview the main historical and technological elements characterising the rise, the fall and the recent renaissance of the cognitive approaches to Artificial Intelligence and provide some insights and suggestions about the future directions and challenges that, in our opinion, this discipline needs to face in the next years.

If our experiences are cognitively penetrable, they can be influenced by our antecedent expectations, beliefs, or other cognitive states. Theorists such as Churchland, Fodor, Macpherson, and Siegel have debated whether and how our cognitive states might influence our perceptual experiences, as well as how any such influences might affect the ability of our experiences to justify our beliefs about the external world. This article surveys views about the nature of cognitive penetration, the epistemological consequences of denying cognitive penetration, and the (...) epistemological consequences of affirming cognitive penetration. (shrink)

In this paper I start from a definition of “culture of the artificial” which might be stated by referring to the background of philosophical, methodological, pragmatical assumptions which characterizes the development of the information processing analysis of mental processes and of some trends in contemporary cognitive science: in a word, the development of AI as a candidate science of mind. The aim of this paper is to show how (with which plausibility and limitations) the discovery of the mentioned background (...) might be dated back to a period preceding the cybernetic era, the decade 1930–1940 at least. Therefore a somewhat detailed analysis of Hull's “robot approach” is given, as well as of some of its independent and future developments. -/- Reprinted in R.L. Chrisley (ed.), Artificial Intelligence: Critical Concepts in Cognitive Science, vol. 1, Routledge, London and New York, 2000, pp. 301-326. (shrink)

Following the publication of numerous ethical principles and guidelines, the concept of 'Trustworthy AI' has become widely used. However, several AI ethicists argue against using this concept, often backing their arguments with decades of conceptual analyses made by scholars who studied the concept of trust. In this paper, I describe the historical-philosophical roots of their objection and the premise that trust entails a human quality that technologies lack. Then, I review existing criticisms about 'Trustworthy AI' and the consequence of ignoring (...) these criticisms: if the concept of 'Trustworthy AI' is kept being used, we risk attributing responsibilities to agents who cannot be held responsible, and consequently, deteriorate social structures which regard accountability and liability. Nevertheless, despite suggestions to shift the paradigm from 'Trustworthy AI' to 'Reliable AI', I argue that, realistically, this concept will be kept being used. I end by arguing that, ultimately, AI ethics is also about power, social justice, and scholarly activism. Therefore, I propose that community-driven and social justice-oriented ethicists of AI and trust scholars further focus on (a) democratic aspects of trust formation; and (b) draw attention to critical social aspects highlighted by phenomena of distrust. This way, it will be possible to further reveal shifts in power relations, challenge unfair status quos, and suggest meaningful ways to keep the interests of citizens. (shrink)

Artificial intelligence systems have been widely applied to various contexts, including high-stake decision processes in healthcare, banking, and judicial systems. Some developed AI models fail to offer a fair output for specific minority groups, sparking comprehensive discussions about AI fairness. We argue that the development of AI systems is marked by a central paradox: the less participation one stakeholder has within the AI system’s life cycle, the more influence they have over the way the system will function. This means (...) that the impact on the fairness of the system is in the hands of those who are less impacted by it. However, most of the existing works ignore how different aspects of AI fairness are dynamically and adaptively affected by different stages of AI system development. To this end, we present a use case to discuss fairness in the development of corporate wellness programs using smart wearables and AI algorithms to analyze data. The four key stakeholders throughout this type of AI system development process are presented. These stakeholders are called service designer, algorithm designer, system deployer, and end-user. We identify three core aspects of AI fairness, namely, contextual fairness, model fairness, and device fairness. We propose a relative contribution of the four stakeholders to the three aspects of fairness. Furthermore, we propose the boundaries and interactions between the four roles, from which we make our conclusion about the possible unfairness in such an AI developing process. (shrink)

In this paper we present two distinctly epistemological puzzles that arise for one who aspires to defend some plausible version of the precautionary principle. The first puzzle involves an application of contextualism in epistemology; and the second puzzle concerns the task of defending a plausible version of the precautionary principle that would not be invalidated by de minimis.

his article will focus on the mechanistic origins of the computer metaphor, which forms the conceptual framework for the methodology of the cognitive sciences, some areas of artificial intelligence and the philosophy of mind. The connection between the history of computing technology, epistemology and the philosophy of mind is expressed through the metaphorical dictionaries of the philosophical discourse of a particular era. The conceptual clarification of this connection and the substantiation of the mechanistic components of the computer metaphor (...) is the main goal of this article. The statement is substantiated that the invention of mechanical computing devices, having a long history in the European engineering tradition, formed the prerequisites for the emergence of machine functionalism in the modern philosophy of mind. The idea of multiple implementation stems from the principle that a formal symbol system prescribes rules for the use of rational abstractions through the physical architecture of a computational engine. The article considers the reasons for the conceptual shift and reveals the semantic foundations for the metaphorical transfer of the properties of abstract objects from the theory of automata to the field of modern philosophy of mind. The criticism and ways of protecting the philosophical program of machine functionalism are analyzed by changing the content of the metaphor “Mind as machine”. The reasons for the stability of the information-computer approach in cognitive sciences are also disclosed and explained. (shrink)

Why would we want to develop artificial human-like arithmetical intelligence, when computers already outperform humans in arithmetical calculations? Aside from arithmetic consisting of much more than mere calculations, one suggested reason is that AI research can help us explain the development of human arithmetical cognition. Here I argue that this question needs to be studied already in the context of basic, non-symbolic, numerical cognition. Analyzing recent machine learning research on artificial neural networks, I show how AI studies could (...) potentially shed light on the development of human numerical abilities, from the proto-arithmetical abilities of subitizing and estimating to counting procedures. Although the current results are far from conclusive and much more work is needed, I argue that AI research should be included in the interdisciplinary toolbox when we try to explain the development and character of numerical cognition and arithmetical intelligence. This makes it relevant also for the epistemology of mathematics. (shrink)

The aim of this thesis is to advance a philosophically justifiable account of Artificial Moral Agency (AMA). Concerns about the moral status of Artificial Intelligence (AI) traditionally turn on questions of whether these systems are deserving of moral concern (i.e. if they are moral patients) or whether they can be sources of moral action (i.e. if they are moral agents). On the Organic View of Ethical Status, being a moral patient is a necessary condition for an entity to (...) qualify as a moral agent. This view claims that because artificial agents (AAs) lack sentience, they cannot be proper subjects of moral concern and hence cannot be considered to be moral agents. I raise conceptual and epistemic issues with regards to the sense of sentience employed on this view, and I argue that the Organic View does not succeed in showing that machines cannot be moral patients. Nevertheless, irrespective of this failure, I also argue that the entire project is misdirected in that moral patiency need not be a necessary condition for moral agency. Moreover, I claim that whereas machines may conceivably be moral patients in the future, there is a strong case to be made that they are (or will very soon be) moral agents. Whereas it is often argued that machines cannot be agents simpliciter, let alone moral agents, I claim that this argument is predicated on a conception of agency that makes unwarranted metaphysical assumptions even in the case of human agents. Once I have established the shortcomings of this “standard account”, I move to elaborate on other, more plausible, conceptions of agency, on which some machines clearly qualify as agents. Nevertheless, the argument is still often made that while some machines may be agents, they cannot be moral agents, given their ostensible lack of the requisite phenomenal states. Against this thesis, I argue that the requirement of internal states for moral agency is philosophically unsound, as it runs up against the problem of other minds. In place of such intentional accounts of moral agency, I provide a functionalist alternative, which makes conceptual room for the existence of AMAs. The implications of this thesis are that at some point in the future we may be faced with situations for which no human being is morally responsible, but a machine may be. Moreover, this responsibility holds, I claim, independently of whether the agent in question is “punishable” or not. (shrink)

In a recent paper in this journal, we proposed two novel puzzles associated with the precautionary principle. Both are puzzles that materialise, we argue, once we investigate the principle through an epistemological lens, and each constitutes a philosophical hurdle for any proponent of a plausible version of the precautionary principle. Steglich-Petersen claims, also in this journal, that he has resolved our puzzles. In this short note, we explain why we remain skeptical.

This paper deals with the philosophical problems concerned with research in the field of artificial intelligence (AI), in particular with problems arising out of claims that AI exhibits ‘consciousness’, ‘thinking’ and other ‘inner’ processes and that they simulate human intelligence and cognitive processes in general. The argument is to show how Cartesian mind is non-mechanical. Descartes’ concept of ‘I think’ presupposes subjective experience, because it is ‘I’ who experiences the world. Likewise, Descartes’ notion of ‘I’ negates the notion of (...) computationality of the mind. The essence of mind is thought and the acts of thoughts are identified with the acts of consciousness. Therefore, it follows that cognitive acts are conscious acts, but not computational acts. Thus, for Descartes, one of the most important aspects of cognitive states and processes is their phenomenality, because our judgments, understanding, etc. can be defined and explained only in relation to consciousness and not in relation to computationality. We can only find computationality in machines and not in the mind, which wills, understands and judges. (shrink)

Summary. The prerequisites of this study have three interwoven sources, the natural sciences and philosophical and socio-political ones. They are trends in the way of being of a modern, technogenic civilization. The COVID-19 pandemic caused significant damage to the image of the omnipotent techno-science that has developed in the mentality of this sociocultural type.Our goal was to study the co-evolutionary nature of this phenomenon as a natural consequence of the nature of the evolutionary strategy of our biological species. Technological civilization (...) as a cultural-civilizational type is one of the evolutionary options of Homo sapiens, the ontological basis of which is a stable evolutionary strategy (SESH). The latter is capable to spontaneous development and is consisting from biological, sociocultural, and techno-rationalistic modules. Evolutionary risks inextricably linked with it. At present, humankind has entered an era when its existence should be ensured by the meta-system engineering of its own cultural and ecological niche. By such artificially created elements, it implies the design and implementation of ecological systems of various levels of complexity, from the design of elements of such systems (which are biological individuals, populations and species) to the design of a global ecological system (biosphere). At the same time, there is a sharp jump in the value of anthropogenic and technological risk due to a sharp increase in the instability of the structure of ecological systems. We are witnessing a third wave of breaking and reconstruction of the existing relations between the elements of such systems after the Neolithic revolution and great geographical discoveries. Technological innovations led to sharp violations of normal social ecodynamics, leading to outbreaks of new infections, in particular. Theuncontested development of all sectors of controlled evolution technology is the way out of the last such crisis and the prevention of similar ones in the future. There are global nature of the organization of modern technological civilization and the transformation of the biosphere not so much into the noosphere (according to Vernadsky) but into the technosphere that determines the effect of a cascade reaction: any local co-adaptive conflict between elements of a cultural, socio-ecological niche tends to turnglobal and systemic problems. Humanity is constantly forced to make a choice between the stability and adaptability of the technosphere. (shrink)

This paper discusses the epistemology of the Internet of Things [IoT] by focusing on the topic of trust. It presents various frameworks of trust, and argues that the ethical framework of trust is what constitutes our responsibility to reveal desired norms and standards and embed them in other frameworks of trust. The first section briefly presents the IoT and scrutinizes the scarce philosophical work that has been done on this subject so far. The second section suggests that the field (...) of epistemology is not sufficiently capable of dealing with technologies, and presents a possible solution to this problem. It is argued that knowledge is not only social phenomena, but also a technological one, and that in order to address epistemological issues in technology, we need to carefully depart from traditional epistemic analysis and form a new approach that is technological (termed here Techno-Epistemology). The third and fourth sections engage in an epistemic analysis of trust by dividing it in to various frameworks. The last section argues that these various frameworks of trust can be understood to form a trustworthy large-scale socio-technological system, emphasizing the place of ethical trust as constituting our commitment to give proper accounts for all of the other frameworks. (shrink)

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

This paper reviews current debates in social epistemology about the relations ‎between ‎knowledge ‎and consensus. These relations are philosophically interesting on their ‎own, but ‎also have ‎practical consequences, as consensus takes an increasingly significant ‎role in ‎informing public ‎decision making. The paper addresses the following questions. ‎When is a ‎consensus attributable to an epistemic community? Under what conditions may ‎we ‎legitimately infer that a consensual view is knowledge-based or otherwise ‎epistemically ‎justified? Should consensus be the aim of scientific inquiry, (...) and if so, what ‎kind of ‎consensus? How should dissent be handled? It is argued that a legitimate inference ‎that a ‎theory is correct from the fact that there is a scientific consensus on it requires taking ‎into ‎consideration both cognitive properties of the theory as well as social properties of ‎the ‎consensus. The last section of the paper reviews computational models of ‎consensus ‎formation.‎. (shrink)

Many extant theories of placebo focus on their causal structure wherein placebo effects are those which originate from select features of the therapy (e.g. client expectations or ‘incidental’ features like size, and shape). Although such accounts can distinguish placebos from standard medical treatments, they cannot distinguish placebos from everyday occurrences e.g. when positive feedback improves our performance on a task. Providing a social epistemological account of a treatment context can rule out such occurrences, and furthermore reveal a new way to (...) distinguish clinical placebos from standard medical treatments. (shrink)

This article surveys recent developments in the epistemology of modality.