Barry Smith

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.