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.

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)

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)

The complex of problems suggested by the term life-world pervades contemporary thought, even though such a complex is rarely called by this name [...] Time does not allow us, however, to perform an extensive review of the secondary literature on the 'Crisis'. I will only suggest that a survey of this literature, especially the works of Brand, Merleau-Ponty and Habermas, presents us with a dilemma. It seems that there is a difficulty in Husserl's characterization of the life-world. On the one (...) hand, it is understood as the plurality of individually different socio-cultural environments and thus the result of an historical development; on the other hand, it is interpreted as a single structural basis common to all environments and thus an a priori for that history through which they become different. This dilemma concerning the content of Husserl's theory is coupled with a problem having to do with the method of his analysis: how is Husserl's procedure of phenomenological reflection upon a transcendental ego or "monad" able to account for the intersubjective life-world in either of the senses just sketched? Putting the question in this fashion is usually the first step on the way to abandoning a transcendental account of historicity, or, as is the case with Habermas, replacing the transcendental ego with a community of language users. What I want to propose in this essay is precisely what current thinkers seem unanimous in rejecting. I want to argue for a transcendental theory of the life-world and of historicity, and I want to do so by suggesting that a phenomenological reflection upon the transcendental ego - once correctly understood - is the proper procedure for constructing such a theory. In this paper I will discuss such a theory by undertaking a brief study of Husserl's concept of the life-world and by isolating several difficulties which I detect (Part I). I will then introduce a theory of the transcendental reduction as the key to resolving the difficulties I discover (Part II). Finally, I will undertake my own systematic analysis of the a priori of the life-world and will suggest a way of integrating such an analysis with what I will call a transcendental history of the experience of consciousness (Part III). (shrink)

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)

In lieu of an abstract, here is a brief excerpt of the content:NEWMAN'S PSYCHOLOGICAL DISCOVERY: THE ILLATIVE SENSE (Continued) VI THE FACULTIES OF COGNITION AND APPETITION Since the Grammar of Assent gives us a phenorhenological analysis of the art of thinking and often refers to the influence of other faculties in our reasoning processes, it will be very instructive to examine what the author holds about our faculties of cognition and appetition. This will make us better acquainted with the nature (...) of the illative sense. I. THE SENSES 1. The External Senses and their Objects. We had already arrived at the conclusion that Newman rejects the mere subjectivity of our knowledge. When he writes about this matter he explicitly deals with sensation or sensuous cognition. Although he takes exception to the word "immediate perception," 1 we may nevertheless call him an adherent of direct or immediate realism according to Scholastic terminology, because he emphatically excludes the intervention of a reasoning process from sense perception and uses the term "mediate perception" only to express the instrumentality of experience. In this meaning our perception of external objects is mediate or indirect indeed.2 The fact is that as early as 1839 he wrote in his University Sermons: "Of the material we have direct knowledge through the senses"3 and in 1843: "The senses are direct, immediate, and ordinary informants, and act spontaneously without any will or effort on our part."4 On the importance of sense perception for our mental activities he writes in a series of hitherto unpublished notes, entitled Elements of Thought:6 "I grant or I assume that the soul would not think without some external stimulus; that if it were cut off from all communication from the external world, it would pass this life in a sort of torpor... But then, as soon as it is roused, it reflects upon itself, and thereby gains a number of ideas..." 1. See supra V, 14.2. Supra V, 14.3. P. 205. 4.P. 303 ; cf. Gramm., p. 260. 5.See the unpublished Philosophical Papers, note Fcbr. 24, 1859. 40 DR. ZENO, OJM. CAP.41 Apart from the passages already referred to, Newman nowhere enlarges on the doctrine about the senses. He does not speak about the distinctions between sensible objects; he does not explain the difference between sensation and perception, and uses those terms promiscuously.6 There are no statements on the subject which contradict current Scholastic notions, although sometimes his vague terminology may be an occasion for misunderstandings. For instance, some passages in connection with "images" and "impressions," when read apart from the context, would appear to imply that he identifies them with the Scholastic species a sensibili accepta. However, we shall show further on that. Newman means something quite different. He deals with these species and the so-called sensibilia per acci· dens by the way when describing our knowledge of God7 and teaching that we have evidence of the presence of individuals or substances in the phenomena which occur to our senses. We picture those things to ourselves in those phenomena. They are like pictures, he says, but at the same time "they give us no exact measure or character of the unknown things beyond them." "Therefore when we speak of our having a picture of the things which are perceived through the senses, we mean a certain representation, true as far as it goes, but not adequate." 2. The Internal Senses and their Objects. Newman nowhere gives a distinction between external and internal senses, but nevertheless he speaks about those faculties of the mind which by the Scholastics are called the internal senses. These philosophers distinguish a common sense or rather a central sense (sensus communis), which unites the impressions of the external senses into one whole, makes us conscious of the conditions of our body and notifies to us the sensations of our external as well as internal senses; — the imagination or the faculty which preserves and reproduces things perceived; — the sensuous memory, i. e., the power to retain and to reproduce sense images; — and the vis aestimativa or the instinctive faculty, which discovers without any intellectual means, what is good and what is bad for our welfare. 6.It would seem that he generally... (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)

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)

Geleltwort, von L. Landgrebe.--Geschichte und Ünderliefreung, von G. Miyake.--Wahrhelt und Schn̈heit, von K. H. Volkmann-Schluck,--Georg Büchner: Das endlose Drama, von . G. Baumann.--Die Lehre von der Vergangenheit der Kunst, von, J. Patǒcka.--Der Sinn der künstlerischen Revolte, von D. Pejović.--Das problem der Konkretisierung der Transzendentalität, von E. Heintel.--Ontologische Erfahrung. von J. Lohmann.--Philosophie in Orient und Okzident, von S. Moser.--.

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.

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)

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.

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)

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)

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)

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

Zur patientenorientierten Behandlung bei nichteinwilligungsfähigen Patienten werden aktuell der Einbezug oder auch die Entscheidung durch ein Ethikkonsil oder klinisches Ethikkomitee (KEK) gefordert. Damit die Entscheidung des Entscheidungsträgers durch das KEK unterstützt werden kann, müssen Zuständigkeiten, Besetzung und Arbeitsweise des Gremiums klar umschrieben sein.