The article presents edmund Husserl’s idea of transcendental phenomenology in the perspec‐ tive of the project of science. this aspect of Husserl’s writings was pointed out by, for example, rudolf Bernet, man ed Brelage, Iso Kern, eduard marbach, eugen Fink, Ludwig Landgrebe, and roman Ingarden. the main aim, realised in the article is to prove the main hypothesis claiming that transcendental phenomenology is closely connected with Husserl’s conception of philosophy, the idea of philosophy as a science (eidetic and (...) transcendental). the project of transcendental science and knowledge is also connected with Husserl’s conception of transcen‐ dental reduction taken as a mode of revealing those constitutive achievements of consciousness which were covered in the natural attitude. In the paper, I focus on presenting the most im‐ portant points (epistemological, methodological, and transcendental) connected with Husserl’s evolution of phenomenology in the perspective of the project of science. (shrink)

Landgrebe and Smith (2022) have recently offered an important mathematical argument against the possibility of Artificial General Intelligence (AGI): human intelligence is a complex system; complex systems have some properties that cannot be modelled mathematically; hence we have no viable way to build an AI that would be able to emulate human intelligence. The issue of complexity is thus at the heart of the Landgrebe and Smith approach, and they tackle this issue by postulating a set of conditions, (...) derived from mathematics, for a system to be complex. I argue that Hayek’s “Theory of Complex Phenomena” offers an interesting alternative path to understanding what makes complex systems complex. This offers an argument complementary to that of Landgrebe and Smith, which approaches the issue of complexity from an ontological angle, and which is designed to show that AI systems are not the right kind of entity that may interact meaningfully with complex systems. (shrink)

Since the noun phrase `artificial intelligence' (AI) was coined, it has been debated whether humans are able to create intelligence using technology. We shed new light on this question from the point of view of themodynamics and mathematics. First, we define what it is to be an agent (device) that could be the bearer of AI. Then we show that the mainstream definitions of `intelligence' proposed by Hutter and others and still accepted by the AI community are too weak even (...) to capture what is involved when we ascribe intelligence to an insect. We then summarise the highly useful definition of basic (arthropod) intelligence proposed by Rodney Brooks, and we identify the properties that an AI agent would need to possess in order to be the bearer of intelligence by this definition. Finally, we show that, from the perspective of the disciplines needed to create such an agent, namely mathematics and physics, these properties are realisable by neither implicit nor explicit mathematical design nor by setting up an environment in which an AI could evolve spontaneously. (shrink)

In his “Bridging mainstream and formal ontology”, Augusto (2021) gives an excellent analysis of Dietrich von Freiberg’s idea of using causality as a partitioning principle for upper ontologies. For this Dietrich’s notion of extrinsic principles is crucial. The question whether causation can and indeed should be used as a partitioning principle for ontologies is discussed using mathematics and physics as examples.

Transcript of an Interview on the podcast: Irreverend: Faith and Current Affairs.

The book’s core argument is that an artificial intelligence that could equal or exceed human intelligence—sometimes called artificial general intelligence (AGI)—is for mathematical reasons impossible. It offers two specific reasons for this claim: Human intelligence is a capability of a complex dynamic system—the human brain and central nervous system. Systems of this sort cannot be modelled mathematically in a way that allows them to operate inside a computer. In supporting their claim, the authors, Jobst Landgrebe and Barry Smith, marshal (...) evidence from mathematics, physics, computer science, philosophy, linguistics, and biology, setting up their book around three central questions: What are the essential marks of human intelligence? What is it that researchers try to do when they attempt to achieve "artificial intelligence" (AI)? And why, after more than 50 years, are our most common interactions with AI, for example with our bank’s computers, still so unsatisfactory? Landgrebe and Smith show how a widespread fear about AI’s potential to bring about radical changes in the nature of human beings and in the human social order is founded on an error. There is still, as they demonstrate in a final chapter, a great deal that AI can achieve which will benefit humanity. But these benefits will be achieved without the aid of systems that are more powerful than humans, which are as impossible as AI systems that are intrinsically "evil" or able to "will" a takeover of human society. (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)

An interview by Alex Thomson of UKColumn on Landgrebe and Smith's book: Why Machines Will Never Rule the World. The subtitle of the book is Artificial Intelligence Without Fear, and the interview begins with the question of the supposedly imminent takeover of one profession or the other by artificial intelligence. Is there truly reason to be afraid that you will lose your job? The interview itself is titled 'Where this is no will there is no way', drawing on one (...) thesis of the book to the effect that there will never be anything like the human will on the part of a machine. This is for mathematical reasons. AI is always and in every case a matter of algorithms; thus of applied mathematics. And algorithms are not the sorts of things that can want or desire or intend to do something. It is the human will of those who work at OpenAI or google or microsoft which have given rise to the new shiny objects of AI (ChatGPT and other Large Language Models). And it is the human will of the users of these shiny objects which gives them the resources and power to work their apparent miracles. (shrink)

Implicit stochastic models, including both ‘deep neural networks’ (dNNs) and the more recent unsupervised foundational models, cannot be explained. That is, it cannot be determined how they work, because the interactions of the millions or billions of terms that are contained in their equations cannot be captured in the form of a causal model. Because users of stochastic AI systems would like to understand how they operate in order to be able to use them safely and reliably, there has emerged (...) a new field called ‘explainable AI’ (XAI). When we examine the XAI literature, however, it becomes apparent that its protagonists have redefined the term ‘explanation’ to mean something else, namely: ‘interpretation’. Interpretations are indeed sometimes possible, but we show that they give at best only a subjective understanding of how a model works. We propose an alternative to XAI, namely certified AI (CAI), and describe how an AI can be specified, realized, and tested in order to become certified. The resulting approach combines ontologies and formal logic with statistical learning to obtain reliable AI systems which can be safely used in technical applications. (shrink)

We comment on the collection of papers inspired by our book Why Machines Will Never Rule the World published in volume 12 (5+6) of the journal Cosmos+Taxis. We summarize the arguments made by the contributors about what we say in the book, and then show where we disagree.

Barry Smith recently discussed the diagraphs of book eight of Jacob Lorhard’s Ogdoas scholastica under the heading “birth of ontology” (Smith, 2022; this issue). Here, I highlight the commonalities between the original usage of diagraphs in the tradition of Ramus for didactic purposes and the the usage of their present-day successors–modern ontologies–for computational purposes. The modern ideas of ontology and of the universal computer were born just two generations apart in the breakthrough century of instrumental reason.

Call it the Skynet hypothesis, Artificial General Intelligence, or the advent of the Singularity — for years, AI experts and non-experts alike have fretted (and, for a small group, celebrated) the idea that artificial intelligence may one day become smarter than humans. -/- According to the theory, advances in AI — specifically of the machine learning type that’s able to take on new information and rewrite its code accordingly — will eventually catch up with the wetware of the biological brain. (...) In this interpretation of events, every AI advance from Jeopardy-winning IBM machines to the massive AI language model GPT-3 is taking humanity one step closer to an existential threat. We’re literally building our soon-to-be-sentient successors. -/- Except that it will never happen. At least, according to the authors of the new book Why Machines Will Never Rule the World: Artificial Intelligence without Fear. (shrink)

The view of nature we adopt in the natural attitude is determined by common sense, without which we could not survive. Classical physics is modelled on this common-sense view of nature, and uses mathematics to formalise our natural understanding of the causes and effects we observe in time and space when we select subsystems of nature for modelling. But in modern physics, we do not go beyond the realm of common sense by augmenting our knowledge of what is going on (...) in nature. Rather, we have measurements that we do not understand, so we know nothing about the ontology of what we measure. We help ourselves by using entities from mathematics, which we fully understand ontologically. But we have no ontology of the reality of modern physics; we have only what we can assert mathematically. In this paper, we describe the ontology of classical and modern physics against this background and show how it relates to the ontology of common sense and of mathematics. (shrink)

Health Level 7 (HL7) is an international standards development organisation in the domain of healthcare information technology. Initially the mission of HL7 was to enable data exchange via the creation of syntactic standards which supported point-to-point messaging. Currently HL7 sees its mission as one of creating standards for semantic interoperability in healthcare IT on the basis of its flagship “version 3” (v3). Unfortunately, v3 has been plagued by quality and consistency issues, and it has not been able to keep pace (...) with recent developments either in semantics and ontology or in computer science and engineering. HL7’s response has been to develop its “Services-Aware Interoperability Framework” (SAIF), which is intended to provide a foundation for work on all aspects of standardization in HL7 henceforth. We here summarise the major design principles that must be satisfied by a semantic interoperability framework – principles relating both to static semantics and to computational behaviour. We then assess the SAIF in light of these principles. We conclude that the SAIF is not in a position to support the needed reform of the HL7 v3 family of standards. (shrink)

I respond to Ferrero’s comments on “What are Conditional Intentions?” in three parts. In the first, I address three arguments Ferrero gives for his account and against mine, the argument from requirement of a formal distinction, the argument from continuity, and the argument from the rational pressures of intention. In the second, I raise some problems for Ferrero’s views on the basis drawing out its consequences and testing those against cases. In the third, I consider in a more theoretical vein (...) how reasons and intentions are related, and offer an explanation of why we should not read reasons for intentions into their contents. (shrink)

This paper gives an account of proxy agency in the context of collective action. It takes the case of a group announcing something by way of a spokesperson as an illustration. In proxy agency, it seems that one person or subgroup's doing something counts as or constitutes or is recognized as (tantamount to) another person or group's doing something. Proxy agency is pervasive in institutional action. It has been taken to be a straightforward counterexample to an appealing deflationary view of (...) collective action as a matter of all members of a group making a contribution to bringing about some event. I show that this is a mistake. I give a deflationary account of constitutive rules in terms of essentially collective action types. I then give an account of one form of constitutive agency in terms of constitutive rules. I next give an account of status functions—of which being a spokesperson is one—that also draws on the concept of a constitutive rule. I then show how these materials help us to see how proxy agency is an expression of the agency of all members of the group credited with doing something when the proxy acts. (shrink)

Some defenders of so-called `artificial intelligence' believe that machines can understand language. In particular, Søgaard has argued in his "Understanding models understanding language" (2022) for a thesis of this sort. His idea is that (1) where there is semantics there is also understanding and (2) machines are not only capable of what he calls `inferential semantics', but even that they can (with the help of inputs from sensors) `learn' referential semantics. We show that he goes wrong because he pays insufficient (...) attention to the difference between language as used by humans and the sequences of inert symbols which arise when language is stored on hard drives or in books in libraries. (shrink)

The aim of this article is to show that externalist accounts of cognition such as Clark and Chalmers' (1998) “active externalism” lead to an explosion of knowledge that is caused by online resources such as Wikipedia and Google. I argue that externalist accounts of cognition imply that subjects who integrate mobile Internet access in their cognitive routines have millions of standing beliefs on unexpected issues such as the birth dates of Moroccan politicians or the geographical coordinates of villages in southern (...) Indonesia. Although many externalists propose criteria for the bounds of cognition that are designed to avoid this explosion of knowledge, I argue that these criteria are flawed and that active externalism has to accept that information resources such as Wikipedia and Google constitute extended cognitive processes. (shrink)

Sam Harris is a contemporary illustration of the difficulties standing in the way of coherent interdisciplinary thinking in an age where science and the humanities have drifted so far apart. We are here with Harris’s views on AI, and specifically with his view according to which, with the advance of AI, there will evolve a machine superintelligence with powers that far exceed those of the human mind. This he sees as something that is not merely possible, but rather a matter (...) of inevitability. If, however, we look carefully at what intelligence is, and at how computers really work on the basis of mathematical models, then we can see that it is forever impossible to emulate inside a computer even the intelligence of crows or rabbits, let alone that of human beings. (shrink)

Das in diesem Aufsatz vorgebrachte Argumentationsmuster hat folgende Schritte: 1. Der menschliche Geist ist vom Körper nicht trennbar, sie bilden ein Kontinuum. 2. Unser Bewusstsein und alle darauf aufbauenden geistigen Phänomene sind die Emanation eines materiellen Prozesses, den ein komplexes System verursacht. 3. Komplexe Systeme lassen sich mathematisch nicht modellieren und nicht kausal verstehen. 4. Computer sind Turing-Maschinen. Sie können nur mathematische Modelle berechnen. Es wird niemals Hyper-Turing Maschinen geben, und wenn es sie gäbe, könnten sie auch nur mathematische Modelle (...) berechnen. 5. Es ist nicht möglich, den Körper als Substrat des Geistes durch einen Computer zu ersetzen. Die digitale Unsterblichkeit ist demzufolge ein Ding der Unmöglichkeit. (shrink)

This paper offers an analysis of the logical form of plural action sentences that shows that collective actions so ascribed are a matter of all members of a group contributing to bringing some event about. It then uses this as the basis for a reductive account of the content of we-intentions according to which what distinguishes we-intentions from I-intentions is that we-intentions are directed about bringing it about that members of a group act in accordance with a shared plan.

The goal of creating Artificial General Intelligence (AGI) – or in other words of creating Turing machines (modern computers) that can behave in a way that mimics human intelligence – has occupied AI researchers ever since the idea of AI was first proposed. One common theme in these discussions is the thesis that the ability of a machine to conduct convincing dialogues with human beings can serve as at least a sufficient criterion of AGI. We argue that this very ability (...) should be accepted also as a necessary condition of AGI, and we provide a description of the nature of human dialogue in particular and of human language in general against this background. We then argue that it is for mathematical reasons impossible to program a machine in such a way that it could master human dialogue behaviour in its full generality. This is (1) because there are no traditional explicitly designed mathematical models that could be used as a starting point for creating such programs; and (2) because even the sorts of automated models generated by using machine learning, which have been used successfully in areas such as machine translation, cannot be extended to cope with human dialogue. If this is so, then we can conclude that a Turing machine also cannot possess AGI, because it fails to fulfil a necessary condition thereof. At the same time, however, we acknowledge the potential of Turing machines to master dialogue behaviour in highly restricted contexts, where what is called “narrow” AI can still be of considerable utility. (shrink)

I address a criticism of the use of thought experiments in conceptual analysis advanced on the basis of the survey method of so-called experimental philosophy. The criticism holds that surveys show that intuitions are relative to cultures in a way that undermines the claim that intuition-based investigation yields any objective answer to philosophical questions. The crucial question is what intuitions are as philosophers have been interested in them. To answer this question we look at the role of intuitions in philosophical (...) inquiry. When we have done this, we can see that it is impossible for intuitions properly understood to be relative in the way that has been suggested as they are conceived of as expressions of competence in the concepts deployed in their contents. The remaining methodological issues, though not to be dismissed, present no in principle objection to the method of thought experiments. (shrink)

In this paper, we outline an approach to giving extensional truth-theoretic semantics for what have traditionally been seen as opaque sentential contexts. We outline an approach to providing a compositional truth-theoretic semantics for opaque contexts which does not require quantifying over intensional entities of any kind, and meets standard objections to such accounts. The account we present aims to meet the following desiderata on a semantic theory T for opaque contexts: (D1) T can be formulated in a first-order extensional language; (...) (D2) T does not require quantification over intensional entities­i.e., meanings, propositions, properties, relations, or the like­in its treatment of opaque contexts; (D3) T captures the entailment relations that hold in virtue of form between sentences in the language for which it is a theory; (D4) T has a finite number of axioms. If the approach outlined here is correct, it resolves a longstanding complex of problems in metaphysics, the philosophy of mind and the philosophy of language. (shrink)

The aim of this article is to develop an argument against metaphysical debates about the existence of human races. I argue that the ontology of race is underdetermined by both empirical and non-empirical evidence due to a plurality of equally permissible candidate meanings of "race." Furthermore, I argue that this underdetermination leads to a deflationist diagnosis according to #hich disputes about the existence of human races are non-substantive verbal disputes. $hile this diagnosis resembles general deflationist strategies in contemporary metaphysics" I (...) show that my argument does not presuppose controversial metametaphysical assumptions. (shrink)

This paper attacks an old dogma in the philosophy of action: the idea that in order to intend to do something one must believe that there is at least some chance that one will succeed at what one intends. I think that this is a mistake, and that recognizing this will force us to rethink standard accounts of what it is to intend to do something and to do it intentionally.

This paper clarifies Searle's account of we-intentions and then argues that it is subject to counterexamples, some of which are derived from examples Searle uses against other accounts. It then offers an alternative reductive account that is not subject to the counterexamples.

What is the ontology of collective action? I have in mind three connected questions. 1. Do the truth conditions of action sentences about groups require there to be group agents over and above individual agents? 2. Is there a difference, in this connection, between action sentences about informal groups that use plural noun phrases, such as ‘We pushed the car’ and ‘The women left the party early’, and action sentences about formal or institutional groups that use singular noun phrases, such (...) as ‘The United States declared war on Japan on December 8th, 1941’ and ‘The Supreme Court ruled that segregation is unconstitutional in 1954 in Brown vs. Board of Education’? 3. Under what conditions does it make sense to speak of a group doing something together, and what, if anything, is a collective action? In this paper, I argue that a) understanding action sentences about groups does not commit us to the existence of group agents per se, but only to the existence of individual agents; b) there is no difference in this regard between sentences which attribute actions to informal groups on the one hand and institutional groups on the other; c) collective action can be both intentional and unintentional; d) any random group of agents each of whom does something is also a group which does something together; e) while there is a sense in which groups per se perform no primitive collective actions, and therefore no actions at all, f) there is a sensible extension of talk of actions to groups, though it should be treated strictly speaking, like talk of group agents, as a façon de parler, for g) the only agents per se are individuals and the only actions are theirs. -/-. (shrink)

Ludwig deals with the relations between language, thought, and rationality, and, especially, the role and status of assumptions about rationality in interpreting another’s speech and assigning contents to her psychological attitudes—her beliefs, desires, intentions, and so on. The chapter is organized around three questions: What is the relation between rationality and thought? What is the relation between rationality and language? What is the relation between thought and language? Ludwig argues that some large degree of rationality is required for (...) thought and consequently that same degree of rationality at least is required for language since language requires thought. Thought, however, does not require language. In answering questions and, Ludwig gives particular attention to Davidson’s arguments for the Principle of Charity, according to which it is constitutive of speakers that they are largely rational and largely right about the world, and to Davidson’s arguments for the thesis that without the power of speech we lack the power of thought. (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)

(1) Content properties are nonrelational, that is, having a content property does not entail the existence of any contingent object not identical with the thinker or a part of the thinker.2 (2) We have noninferential knowledge of our conscious thoughts, that is, for any of our..

The aim of this article is to discuss the relation between indigenous and scientific kinds on the basis of contemporary ethnobiological research. I argue that ethnobiological accounts of taxonomic convergence-divergence patters challenge common philosophical models of the relation between folk concepts and natural kinds. Furthermore, I outline a positive model of taxonomic convergence-divergence patterns that is based on Slater's [2014] notion of “stable property clusters” and Franklin-Hall's [2014] discussion of natural kinds as “categorical bottlenecks.” Finally, I argue that this model (...) is not only helpful for understanding the relation between indigenous and scientific kinds but also makes substantial contributions to contemporary debates about natural kinds.to contemporary debates about natural kinds. (shrink)

Donald Davidson has argued that attention to the necessarily public character of language shows that we cannot be massively mistaken about the world around us, and that consequently skeptical doubts about empirical knowledge are misplaced. The arguments Davidson advances rely on taking as the fundamental methodological standpoint for investigating meaning and related concepts the standpoint of the interpreter of another speaker, on the grounds that it is from the interpreter’s standpoint that we discover what constraints are placed on meaning by (...) the public character of language. In this paper, I argue that although Davidson’s arguments reveal important conceptual connections between meaning and belief on the one hand, and truth and interpretation on the other, they do not show that it is impossible that we are massively mistaken about the external world. (shrink)

A sorites argument is a symptom of the vagueness of the predicate with which it is constructed. A vague predicate admits of at least one dimension of variation (and typically more than one) in its intended range along which we are at a loss when to say the predicate ceases to apply, though we start out confident that it does. It is this feature of them that the sorites arguments exploit. Exactly how is part of the subject of this paper. (...) The majority of philosophers writing on vagueness take it to be a kind of semantic phenomenon. If we are right, they are correct in this assumption, which is surely the default position, but they have not so far provided a satisfactory account of the implications of this or a satisfactory diagnosis of the sorites arguments. Other philosophers have urged more exotic responses, which range from the view that the fault lies not in our language, but in the world, which they propose to be populated with vague objects which our semantics precisely reflects, to the view that the world and language are both perfectly in order, but that the fault lies with our knowledge of the properties of the words we use (epistemicism). In contrast to the exotica to which some philosophers have found themselves driven in an attempt to respond to the sorites puzzles, we undertake a defense of the commonsense view that vague terms are semantically vague. Our strategy is to take fresh look at the phenomenon of vagueness. Rather than attempting to adjudicate between different extant theories, we begin with certain pre-theoretic intuitions about vague terms, and a default position on classical logic. The aim is to see whether (i) a natural story can be told which will explain the vagueness phenomenon and the puzzling nature of soritical arguments, and, in the course of this, to see whether (ii) there arises any compelling pressure to give up the natural stance. We conclude that there is a simple and natural story to be told, and we tell it, and that there is no good reason to abandon our intuitively compelling starting point. The importance of the strategy lies in its dialectical structure. Not all positions on vagueness are on a par. Some are so incredible that even their defenders think of them as positions of last resort, positions to which we must be driven by the power of philosophical argument. We aim to show that there is no pressure to adopt these incredible positions, obviating the need to respond to them directly. If we are right, semantic vagueness is neither surprising, nor threatening. It provides no reason to suppose that the logic of natural languages is not classical or to give up any independently plausible principle of bivalence. Properly understood, it provides us with a satisfying diagnosis of the sorites argumentation. It would be rash to claim to have any completely novel view about a topic so well worked as vagueness. But we believe that the subject, though ancient, still retains its power to inform and challenge us. In particular, we will argue that taking seriously the central phenomenon of predicate vagueness—the “boundarylessness” of vague predicates—on the commonsense assumption that vagueness is semantic, leads ineluctably to the view that no sentences containing vague expressions (henceforth ‘vague sentences’) are truth-evaluable. This runs counter to much of the literature on vagueness, which commonly assumes that, though some applications of vague predicates to objects fail to be truth-evaluable, in clear positive and negative cases vague sentences are unproblematically true or false. It is clarity on this, and related points, that removes the puzzles associated with vagueness, and helps us to a satisfying diagnosis of why the sorites arguments both seem compelling and yet so obviously a bit of trickery. We give a proof that semantically vague predicates neither apply nor fail-to-apply to anything, and that consequently it is a mistake to diagnose sorites arguments, as is commonly done, by attempting to locate in them a false premise. Sorites arguments are not sound, but not unsound either. We offer an explanation of their appeal, and defend our position against a variety of worries that might arise about it. The plan of the paper is as follows. We first introduce an important distinction in terms of which we characterize what has gone wrong with vague predicates. We characterize what we believe to be our natural starting point in thinking about the phenomenon of vagueness, from which only a powerful argument should move us, and then trace out the consequences of accepting this starting point. We consider the charge that among the consequences of semantic vagueness are that we must give up classical logic and the principle of bivalence, which has figured prominently in arguments for epistemicism. We argue there are no such consequences of our view: neither the view that the logic of natural languages is classical, nor any plausible principle of bivalence, need be given up. Next, we offer a diagnosis of what has gone wrong in sorites arguments on the basis of our account. We then present an argument to show that our account must be accepted on pain of embracing (in one way or another) the epistemic view of “vagueness”, i.e., of denying that there are any semantically vague terms at all. Next, we discuss some worries that may arise about the intelligibility of our linguistic practices if our account is correct. We argue none of these worries should force us from our intuitive starting point. Finally, we cast a quick glance at other forms of semantic incompleteness. (shrink)

This paper defends the autonomy thesis, which holds that one can intend to do something even though one believes it to be impossible, against attacks by Fred Adams. Adams denies the autonomy thesis on the grounds that it cannot, but must, explain what makes a particular trying, a trying for the aim it has in view. If the autonomy thesis were true, it seems that I could try to fly across the Atlantic ocean merely by typing out this abstract, a (...) palpable absurdity. If we deny the autonomy thesis, we have an easy explanation: one simply cannot try to do something which one believes to be impossible. In response, I argue, first, by means of examples, that one clearly can try and intend to do what one believes to be impossible; and then l show how we can provide an answer to Adams’s challenge even so. (shrink)

Holism in interwar Germany provides an excellent example for social and political in- fluences on scientific developments. Deeply impressed by the ubiquitous invocation of a cultural crisis, biologists, physicians, and psychologists presented holistic accounts as an alternative to the “mechanistic worldview” of the nineteenth century. Although the ideological background of these accounts is often blatantly obvious, many holistic scientists did not content themselves with a general opposition to a mechanistic worldview but aimed at a rational foundation of their holistic projects. (...) This article will discuss the work of Kurt Goldstein, who is known for both his groundbreaking contributions to neuropsychology and his holistic philosophy of human nature. By focusing on Goldstein’s neurolinguistic research, I want to reconstruct the empirical foundations of his holistic program without ignoring its cultural background. In this sense, Goldstein’s work provides a case study for the formation of a scientific theory through the complex interplay between specific empirical evidences and the general cultural developments of the Weimar Republic. (shrink)

We sketch an account according to which the semantic concepts themselves are not pathological and the pathologies that attend the semantic predicates arise because of the intention to impose on them a role they cannot fulfill, that of expressing semantic concepts for a language that includes them. We provide a simplified model of the account and argue in its light that (i) a consequence is that our meaning intentions are unsuccessful, and such semantic predicates fail to express any concept, and (...) that (ii) in light of this it is incorrect to characterize the pathology simply as semantic inconsistency; a more nuanced view of the problem is needed. We also show that the defects of the semantic predicates need not undercut the use of a truth theory in a compositional semantics for a language containing them because the meaning theory per se need not involve commitment to the axioms of the truth theory it exploits. (shrink)

The economic paradigms of Ludwig von Mises on the one hand and of John Maynard Keynes on the other have been correctly recognized as antithetical at the theoretical level, and as antagonistic with respect to their practical and public policy implications. Characteristically they have also been vindicated by opposing sides of the political spectrum. Nevertheless the respective views of these authors with respect to the meaning and interpretation of probability exhibit a closer conceptual affinity than has been acknowledged in (...) the literature. In particular it is argued that in some relevant respects Ludwig von Mises´ interpretation of the concept of probability exhibits a closer affinity with the interpretation of probability developed by his opponent John Maynard Keynes than with the views on probability espoused by his brother Richard von Mises. Nevertheless there also exist significant differences between the views of Ludwig von Mises and those of John Maynard Keynes with respect to probability. One of these is highlighted more particularly: where John Maynard Keynes advocated a monist view of probability, Ludwig von Mises embraced a dualist view of probability, according to which the concept of probability has two different meanings each of which is valid in a particular area or context. It is concluded that both John Maynard Keynes and Ludwig von Mises presented highly nuanced views with respect to the meaning and interpretation of probability. (shrink)

It is natural to think that our ordinary practices in giving explanations for our actions, for what we do, commit us to claiming that content properties are causally relevant to physical events such as the movements of our limbs and bodies, and events which these in turn cause. If you want to know why my body ambulates across the street, or why my arm went up before I set out, we suppose I have given you an answer when I say (...) that I wanted to greet a friend on the other side of the street, and thought that my arm's going up would be interpreted by him as a signal to stop for a moment. This widely held view might be disputed, but I shall not argue for it in this paper. I want to start with the view that our beliefs and desires and other propositional attitudes are causally relevant, in virtue of their modes and particular contents, to our movements, in order to investigate the consequences for analyses of thought content. For this purpose, I argue, in sec. II, for three necessary conditions on causal relevance: (a) a nomic sufficiency condition, (b) a logical independence condition, and (c) a screening-off condition. In sec. III, I apply these conditions to relational and functional theories of thought content, arguing that these theories cannot accommodate the causal relevance of content properties to our behaviour. I argue further that, on two plausible assumptions, one about the dependence of the mental on the physical, and the other about the availability in principle of causal explanations of our movements in terms of our non-relational physical properties, content properties can be causally relevant only if they are nomically type-correlated, relative to certain circumstances, with non-relational physical properties of our bodies. In sec. IV, I respond to a number of objections that might be advanced against this conclusion. (shrink)

How are we able to perceive the world veridically? If we ask this question as a part of the scientific investigation of perception, then we are not asking for a transcendental guarantee that our perceptions are by and large veridical; we presuppose that they are. Unless we assumed that we perceived the world for the most part veridically, we would not be in a position to investigate our perceptual abilities empirically. We are interested, then, not in how it is possible (...) in general for us to perceive the world veridically, but instead in what the relation is between our environment and its properties, of which we have knowledge, on the one hand, and our perceptual mechanisms, on the other, that results in very many, even most of our perceptions being veridical in everyday life. (shrink)

The aim of this article is to propose a methodological externalism that takes knowledge about science to be partly constituted by the environment. My starting point is the debate about extended cognition in contemporary philosophy and cognitive science. Externalists claim that human cognition extends beyond the brain and can be partly constituted by external devices. First, I show that most studies of public knowledge about science are based on an internalist framework that excludes the environment we usually utilize to make (...) sense of science and does not allow the possibility of extended knowledge. In a second step, I argue that science communication studies should adopt a methodological externalism and accept that knowledge about science can be partly realized by external information resources such as Wikipedia. (shrink)

In The Mind Doesn’t Work that Way, Jerry Fodor argues that mental representations have context sensitive features relevant to cognition, and that, therefore, the Classical Computational Theory of Mind (CTM) is mistaken. We call this the Globality Argument. This is an in principle argument against CTM. We argue that it is self-defeating. We consider an alternative argument constructed from materials in the discussion, which avoids the pitfalls of the official argument. We argue that it is also unsound and that, while (...) it is an empirical issue whether context sensitive features of mental representations are relevant to cognition, it is empirically implausible. (shrink)

This article uses the case study of ethnobiological classification to develop a positive and a negative thesis about the state of natural kind debates. On the one hand, I argue that current accounts of natural kinds can be integrated in a multidimensional framework that advances understanding of classificatory practices in ethnobiology. On the other hand, I argue that such a multidimensional framework does not leave any substantial work for the notion “natural kind” and that attempts to formulate a general account (...) of naturalness have become an obstacle to understanding classificatory practices. (shrink)

My primary aim in this chapter is to explain in what the traditional mind–body problem consists, what its possible solutions are, and what obstacles lie in the way of a resolution. The discussion will develop in two phases. The first phase, sections 1.2–1.4, will be concerned to get clearer about the import of our initial question as a precondition of developing an account of possible responses to it. The second phase, sections 1.5–1.6, explains how a problem arises in our attempts (...) to answer the question we have characterized, and surveys the various solutions that can be and have been offered. More specifically, sections 1.2–1.4 are concerned with how to understand the basic elements of our initial question – how we should identify the mental, on the one hand, and the physical, on the other – and with what sorts of relations between them we are concerned. Section 1.2 identifies and explains the two traditional marks of the mental, consciousness and intentionality, and discusses how they are related. Section 1.3 gives an account of how we should understand ‘physical’ in our initial question so as not to foreclose any of the traditional positions on the mind–body problem. Section 1.4 then addresses the third element in our initial question, mapping out the basic sorts of relations that may hold between mental and physical phenomena, and identifying some for special attention. Sections 1.5–1.6 are concerned with explaining the source of the difficulty in answering our initial question, and the kinds of solutions that have been offered to it. Section 1.5 explains why our initial question gives rise to a problem, and gives a precise form to the mind–body problem, which is presented as a set of four propositions, each of which, when presented independently, seems compelling, but which are jointly inconsistent. Section 1.6 classifies responses to the mind–body problem on the basis of which of the propositions in our inconsistent set they reject, and provides a brief overview of the main varieties in each category, together with some of the difficulties that arise for each. Section 1.7 is a brief conclusion about the source of our difficulties in understanding the place of mind in the natural world. (shrink)

The term ‘intelligence’ as used in this paper refers to items of knowledge collected for the sake of assessing and maintaining national security. The intelligence community (IC) of the United States (US) is a community of organizations that collaborate in collecting and processing intelligence for the US. The IC relies on human-machine-based analytic strategies that 1) access and integrate vast amounts of information from disparate sources, 2) continuously process this information, so that, 3) a maximally comprehensive understanding of world actors (...) and their behaviors can be developed and updated. Herein we describe an approach to utilizing outcomes-based learning (OBL) to support these efforts that is based on an ontology of the cognitive processes performed by intelligence analysts. Of particular importance to the Cognitive Process Ontology is the class Representation that is Warranted. Such a representation is descriptive in nature and deserving of trust in its veridicality. The latter is because a Representation that is Warranted is always produced by a process that was vetted (or successfully designed) to reliably produce veridical representations. As such, Representations that are Warranted are what in other contexts we might refer to as ‘items of knowledge’. (shrink)

Current controversies about knowledge integration reflect conflicting ideas of what it means to “take Indigenous knowledge seriously”. While there is increased interest in integrating Indigenous and Western scientific knowledge in various disciplines such as anthropology and ethnobiology, integration projects are often accused of recognizing Indigenous knowledge only insofar as it is useful for Western scientists. The aim of this article is to use tools from philosophy of science to develop a model of both successful integration and integration failures. On the (...) one hand, I argue that cross-cultural recognition of property clusters leads to an ontological overlap that makes knowledge integration often epistemically productive and socially useful. On the other hand, I argue that knowledge integration is limited by ontological divergence. Adequate models of Indigenous knowledge will therefore have to take integration failures seriously and I argue that integration efforts need to be complemented by a political notion of ontological self-determination. (shrink)

This paper evaluates Putnam’s argument in the first chapter of Reason, Truth and History, for the claim that we can know that we are not brains in a vat (of a certain sort). A widespread response to Putnam’s argument has been that if it were successful not only the world but the meanings of our words (and consequently our thoughts) would be beyond the pale of knowledge, because a causal theory of reference is not compatible with our having knowledge of (...) the meanings of our words. I argue that this is not so. I argue also, however, that given how Putnam argues (here) for the causal theory of reference, he cannot after all escape this consequence. (shrink)