Barry Smith

When does a human being begin to exist? We argue that it is possible, through a combination of biological fact and philosophical analysis, to provide a definitive answer to this question. We lay down a set of conditions for being a human being, and we determine when, in the course of normal fetal development, these conditions are first satisfied. Issues dealt with along the way include: modes of substance-formation, twinning, the nature of the intra-uterine environment, and the nature of the relation between fetus and mother.

That uses of language not only can, but even normally do have the character of actions was a fact largely unrealised by those engaged in the study of language before the present century, at least in the sense that there was lacking any attempt to come to terms systematically with the action-theoretic peculiarities of language use. Where the action-character of linguistic phenomena was acknowledged, it was normally regarded as a peripheral matter, relating to derivative or non-standard aspects of language which could afford to be ignored.

The problem of self‐knowledge is examined and the linguistic strategy for tackling it is explored. The strategy attempts—as in Davidson's and Wright's discussions of self‐knowledge—to ground knowledge of one's mind on knowledge of what one means in speaking one's mind. If knowing what one is saying in speaking a language is to provide a means of knowing one's own mind, it cannot simply be a part of it. But if no account of knowledge of what one means is offered, there will be a lacuna in the strategy. The paper considers what form a full account should take, and argues that it will have to combine first‐personal, third‐personal and sub‐personal elements of our knowledge of language. All three elements are necessary to explicate what is made available in, and expressed by, instances of disquotational knowledge, such as ‘Snow is white’ means that snow is white.. Immediate and authoritative knowledge of which sentences are grammatical depends on the internal workings of the language faculty and their impact on the conscious experience of the speaker, but immediate and authoritative knowledge of word meaning is not solely a matter internal to the speaker. Knowledge of word meaning is knowledge of public norms that govern our use of words, which introduce third‐personal standards into our first‐personal use. It is argued that our knowledge of word meaning is immediately authoritative about objective standards governing the proper use of our words, and so the authority attaching to these disquotational pronouncements is substantial and not merely an artefact of disquotation. Without an account of that knowledge the lacuna in the linguistic strategy remains.

History has left a territory composed of two municipalitics, whose shape is unique, belonging partly to the Netherlands and partly to Belgium. Earlier both parts belonged to the former Duchy of Brabant, a tenitory that is now split up into the Dutch province of Noord-Brabant (including Baarle-Nassau) and thc Belgian provinces of Antwerp (which includes Baarle-Hertog), Vlaams Brabant, Brussels, and Brabant-Wallon. People are quite comfortable with this situation, even though it raises many complicated and difficult problems that even the most brilliant jurists are puzzled. Baarle-Hertog is called on older Belgian maps Barle-Duc (Hertog = Duke, fr: duc) and must not be confused with the prefectoral town of Bar-le-Duc, Meuse, France.

Definitive diagnosis of malaria requires the demonstration through laboratory tests of the presence within the patient of malaria parasites or their components. Since malaria parasites can be present even in the absence of malaria manifestations, and since symptoms of malaria can be manifested even in the absence of malaria parasites, malaria diagnosis raises important issues for the adequate understanding of disease, etiology and diagnosis. One approach to the resolution of these issues adopts a realist view, according to which the needed clarifications will be derived from a careful representation of the entities on the side of the patient which form the ultimate truthmakers for clinical statements. We here address a challenge to this realist approach relating to the diagnosis of malaria, and show how this challenge can be resolved by appeal to Basic Formal Ontology (BFO) and to the Ontology for General Medical Science (OGMS) constructed in its terms.

Artificial intelligence is man's attempt to use software to emulate the intelligence of human beings. But the complexity of the human neurological system formed in the course of evolution is impossible to replicate: "Human languages and societies are complex systems, indeed complex systems of many complex systems," so much so that their mathematical modeling is impossible. Barry Smith, philosopher and professor at the University at Buffalo. shows no uncertainty about this. His latest book written with Jobst Landgrebe, a mathematician and entrepreneur in the AI field, leaves no doubt – starting with the title: Why machines will never rule the world (Routledge 2023). The book was presented in Turin during an evening organized by the Fondazione CRT and the Bruno Leoni Institute, in which Smith was interviewed based on questions developed by generative Ai. We have accepted the challenge to conduct an interview parallel to the one done with GPT4.

The COVID-19 pandemic prompted immense work on the investigation of the SARS-CoV-2 virus. Rapid, accurate, and consistent interpretation of generated data is thereby of fundamental concern. Ontologies––structured, controlled, vocabularies––are designed to support consistency of interpretation, and thereby to prevent the development of data silos. This paper describes how ontologies are serving this purpose in the COVID-19 research domain, by following principles of the Open Biological and Biomedical Ontology (OBO) Foundry and by reusing existing ontologies such as the Infectious Disease Ontology (IDO) Core, which provides terminological content common to investigations of all infectious diseases. We report here on the development of an IDO extension, the Virus Infectious Disease Ontology (VIDO), a reference ontology covering viral infectious diseases. We motivate term and definition choices, showcase reuse of terms from existing OBO ontologies, illustrate how ontological decisions were motivated by relevant life science research, and connect VIDO to the Coronavirus Infectious Disease Ontology (CIDO). We next use terms from these ontologies to annotate selections from life science research on SARS-CoV-2, highlighting how ontologies employing a common upper-level vocabulary may be seamlessly interwoven. Finally, we outline future work, including bacteria and fungus infectious disease reference ontologies currently under development, then cite uses of VIDO and CIDO in host-pathogen data analytics, electronic health record annotation, and ontology conflict-resolution projects.

Governments standardly deploy a distinction between goods and services in assessing economic health and tracking national income statistics, of which medical goods and services carry significant importance. In what follows we draw on Basic Formal Ontology (BFO) to introduce a third kind of entity called patterns, which help capture the various ways in which goods and services are intertwined and help also to show how many services generate a new kind of non-goods-related products. Patterns are an overlooked yet essential features of many economic sectors including medicine. Studying patterns offers new insights into various components of economic analysis, including outcomes-oriented evaluations of medical services and the value of human capital in the medical sphere.

One famous scene in The Wolf of Wall Street (2013) is the dialogue between the young Jordan Belfort (Leonardo DiCaprio) and the expert trader Mark Hanna (Matthew McConaughey). Hanna is complaining that the stock market is unpredictable; it’s “fugazi … it’s fairy dust. It doesn’t exist. It’s never landed. It is not matter. It’s not on the element chart. It’s not real”. But the fact that something is unpredictable and non-physical does not imply that it does not exist. On the other hand, its unpredictability, non-physicality, and the fact that the stock market trend is largely determined by investors’ beliefs, do make its nature difficult to grasp. This special issue of Rivista di Estetica aims to explore the financial sector from an ontological point of view. While the ontology of money has been extensively studied, few scholars have focused on the stock market and, more generally, on those entities belonging to the investment landscape. Matters are made more complicated by the fact that the financial sector is characterized by an ever-increasing use of digital technology, including software elements that trade in the market themselves. We believe that a careful study of this phenomenon may help us better to understand the role of artificial agents in the social world.

Idee ontologii formalnej zawdzieczamy filozofowi Edmundowi Husserlowi, który w Badaniach logicznych dokonał rozróznienia na logike formalna i formalna ontologie. Przedmiotem pierwszej sa wzajemne zwiazki pomiedzy prawdami (lub znaczeniami zdan w ogólnosci) relacje wynikania, niesprzecznosc, dowód i obowiazywalnosc. Przedmiotem drugiej sa natomiast wzajemne zwiazki pomiedzy rzeczami przedmiotami i własnosciami, czesciami i całosciami, relacjami i kolektywami. Tak jak logika formalna zajmuje sie własnosciami wynikania, które sa formalne w tym sensie, ze stosuja sie do poszczególnych przypadków wynikania jedynie ze wzgledu na ich forme, tak ontologia formalna zajmuje sie własnosciami przedmiotów, które sa formalne w tym sensie, ze ich przykładami, co do zasady, moga byc przedmioty wszystkich materialnych sfer czy dziedzin rzeczywistosci.

How, as Caldwell puts it, does one choose between rival systems all of which claim to rest on a priori foundations? On the nonfallibilistic conception it is difficult to make sense even of the possibility of rival systems of this sort. On the conception here defended, in contrast, the existence of such rival systems can be seen to be a perfectly natural and acceptable consequence of the just-mentioned difficulties we will often fact in coming to know even the intelligible traits of reality: one adjudicates between such systems in the same way in which one adjudicates between all rival scientific hypotheses, namely via a complex mixture of empirical and a priori considerations.

One famous scene in The Wolf of Wall Street (2013) is the dialogue between the young Jordan Belfort (Leonardo DiCaprio) and the expert trader Mark Hanna (Matthew McConaughey). Hanna is complaining that the stock market is unpredictable; it’s “fugazi … it’s fairy dust. It doesn’t exist. It’s never landed. It is not matter. It’s not on the element chart. It’s not real”. But the fact that something is unpredictable and non-physical does not imply that it does not exist. On the other hand, its unpredictability, non-physicality, and the fact that the stock market trend is largely determined by investors’ beliefs, do make its nature difficult to grasp. This special issue of Rivista di Estetica aims to explore the financial sector from an ontological point of view. While the ontology of money has been extensively studied, few scholars have focused on the stock market and, more generally, on those entities belonging to the investment landscape. Matters are made more complicated by the fact that the financial sector is characterized by an ever-increasing use of digital technology, including software elements that trade in the market themselves. We believe that a careful study of this phenomenon may help us better to understand the role of artificial agents in the social world.

In our book, Why Machines Will Never Rule the World, Jobst Landgrebe and I argue that we can engineer machines that can emulate the behaviours only of simple systems, which means: only of those systems whose behaviour we can predict mathematically. The human brain is an example of a complex system, and thus its behaviour cannot be emulated by a machine. We use this argument to debunk the claims of those who believe that large language models are poised to achieve a level of intelligence that will equal or even surpass that of the human brain. The essay was published under the title "Why Machines Will Never Rule the World"

Here we present what we believe is a novel account of what languages are, along with an axiomatically rich representation of languages and language-related data that is based on this account. We propose an account of languages as aggregates of dispositions distributed across aggregates of persons, and in doing so we address linguistic competences and the processes that realize them. This paves the way for representing additional types of language-related entities. Like demographic data of other sorts, data about languages may be of use to researchers in a number of areas, including biomedical research. Data on the languages used in clinical encounters are typically included in medical records, and capture an important factor in patient-provider interactions. Like many types of patient and demographic data, data on a person’s preferred and primary languages are organized in different ways by different systems. This can be a barrier to data integration. We believe that a robust framework for representing language in general and preferred and primary language in particular – which has been lacking in ontologies thus far – can promote more successful integration of language-related data from disparate data sources.

In a development that has still been hardly noticed by philosophers, a conception of ontology has been advanced in recent years in a series of extra-philosophical disciplines as researchers in linguistics, psychology, geography and anthropology have sought to elicit the ontological commitments (‘ontologies’, in the plural) of different cultures or disciplines. Exploiting the terminology of Quine, researchers in psychology and anthropology have sought to establish what individual human subjects, or entire human cultures, are committed to, ontologically, in their everyday cognition, in much the same way in which philosophers of science have attempted to elicit the ontological commitments of the natural sciences. Thus they have engaged in inquiries designed to establish how folk ontologies (or folk biologies, folk theories of physics, folk psychologies, and so on) develop through infancy and childhood, or to establish the degree to which given elements of folk ontologies reflect universal features of the human cognitive system. In a parallel development, researchers in biomedicine developed what they called 'ontologies' as controlled vocabularies to ensure interoperability of the way in which, for example, genomic data is described in different biological disciplines. We describe in what follows some of the relations between these efforts and the more traditional concerns of philosophers.

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.

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.