Barry Smith

First published in 1986, this book presents the first detailed confrontation between the Austrian school of economics and Austrian philosophy, especially the philosophy of the Brentano school. It contains a study of the roots of Austrian economics in the liberal political theory of the nineteenth-century Hapsburg empire, and a study of the relations between the general theory of value underlying Austrian economics and the new economic approach to human behaviour propounded by Gary Becker and others in Chicago. In addition, it considers the connections between Austrian methodology and contemporary debates in the philosophy of the social sciences.

This is a revised and expanded second edition of Why Machines Will Never Rule the World. Its core argument remains the same: that an artificial intelligence (AI) 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 the human brain and central nervous system, which is a complex dynamic 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, biology, and anthropology, 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 interactions with AI, for example when on the telephone with our bank’s computers, still so unsatisfactory?

Austrian economics starts out from the thesis that the objects of economic science differ from those of the natural sciences because of the centrality of the economic agent. This allows a certain a priori or essentialistic aspect to economic science of a sort which parallels the a priori dimension of psychology defended by Brentano and his student Edmund Husserl. We outline these parallels, and show how the theory of a priori dependence relations outlined in Husserl’s Logical Investigations can throw light on the Austrian account of entrepreneurship.

Common sense is on the one hand a certain set of processes of natural cognition – of speaking, reasoning, seeing, and so on. On the other hand common sense is a system of beliefs (of folk physics, folk psychology and so on). Over against both of these is the world of common sense, the world of objects to which the processes of natural cognition and the corresponding belief-contents standardly relate. What are the structures of this world? How does the scientific treatment of this world relate to traditional and contemporary metaphysics and formal ontology? Can we embrace a thesis of common-sense realism to the effect that the world of common sense exists uniquely? Or must we adopt instead a position of cultural relativism which would assign distinct worlds of common sense to each group and epoch? The present paper draws on recent work in computer science (especially in the fields of naive and qualitative physics), in perceptual and developmental psychology, and in cognitive anthropology, in order to consider in a new light these and related questions and to draw conclusions for the methodology and philosophical foundations of the cognitive sciences.

We present a novel methodology for calculating the improvements obtained in successive versions of biomedical ontologies. The theory takes into account changes both in reality itself and in our understanding of this reality. The successful application of the theory rests on the willingness of ontology authors to document changes they make by following a number of simple rules. The theory provides a pathway by which ontology authoring can become a science rather than an art, following principles analogous to those that have fostered the growth of modern evidence-based medicine. Although in this paper we focus on ontologies, the methodology can be generalized to other sorts of terminology-based artifacts, including Electronic Patient Records.

The influence of Kasimir Twardowski on modern Polish philosophy is all-pervasive. As is well known, almost all important 20th century Polish philosophers went through the hard training of his courses in Lvov. Twardowski instilled in his students an enduring concern for clarity and rigour. He taught them to regard philosophy as a collaborative effort, a matter of disciplined discussion and argument. And he encouraged them to work together with scientists from other disciplines — above all with psychologists, and also with mathematicians — so that the Lvov school of philosophy would gradually evolve into the Warsaw school of logic.

Building Information Modelling (BIM) is a process for managing construction project information in such a way as to provide a basis for enhanced decision-making and for collaboration in a construction supply chain. One impediment to the uptake of BIM is the limited interoperability of different BIM systems. To overcome this problem, a set of Industry Foundation Classes (IFC) has been proposed as a standard for the construction industry. Building on IFC, the ifcOWL ontology was developed in order to facilitate representation of building data in a consistent fashion across the Web by using the Web Ontology Language (OWL). This study presents a critical analysis of the ifcOWL ontology and of the associated interoperability issues. It shows how these issues can be resolved by using Basic Formal Ontology (ISO/IEC 21838-2) as top-level architecture. A set of competency questions is used as the basis for comparison of the original ifcOWL with the enhanced ontology, and the latter is used to align with a second ontology – the ontology for building intelligent environments (DOGONT) – in order to demonstrate the added value derived from BFO by showing how querying the enhanced ifcOWL yields useful additional information.

Intelligent defence support systems are confronted with the need to manage ever-increasing floods of data in a way that raises significant challenges because the data are described and presented using different terminologies and formats. How, on this basis, is it possible to reach a common understanding of the information content of these data among people and software agents? How is it possible to ensure that domain knowledge is reused in consistent fashion in a way that makes this information available for integration and analysis? How can we support the identification, selection, composition, and orchestration of services based on such diverse data providing homogeneous support by a service-oriented architecture? This collection is devoted to the use of ontologies to answer questions such as these. Contents Bill Mandrick: Creating an extensible command and control ontology, 215-231 Chris Partridge; Mike Lambert; Mike Loneragan; Andrew Mitchell; Pawel Garbacz: A novel ontological approach to semantic interoperability between legacy air defence command and control systems, 232-262 Michael Gerz; Olivier Meyer: Defining C2 semantics by a platform-independent JC3IEDM, 263-285 Kevin Gupton; Curtis Blais; Kevin Heffner: Management of C2 data standards with modular OWL ontologies, 286-307

In our daily lives, as in science and in all other domains, we encounter huge numbers of dispositions (tendencies, potentials, powers) which are realized in processes such as sneezing, sweating, shedding, melting. Among this plethora of what we can think of as ‘mere dispositions’ is a subset of dispositions in whose realizations we have an interest – a car responding well when driven on ice, a rabbit’s lungs responding well when it is chased by a wolf, and so on. We call the latter ‘capabilities’ and we attempt to provide an ontological account of what capabilities are that is of sufficient generality to serve a variety of purposes, for example by providing a useful extension to ontology-based research in areas where capabilities data are being collected in siloed fashion.

Mid-level ontologies are used to integrate data across disparate domains using vocabularies more specific than top-level ontologies and more general than domain-level ontologies. There are no clear, defensible criteria for determining whether a given ontology should count as mid-level, because we lack a rigorous characterization of what the middle level of generality is supposed to contain. Attempts to provide such a characterization have failed, we believe, because they have focused on the goal of specifying what is characteristic of those single ontologies that have been advanced as mid-level ontologies. Unfortunately, single ontologies of this sort are generally a mixture of top- and mid-level, and sometimes even of domainlevel terms. To gain clarity, we aim to specify conditions for membership in what we call the middle architecture, which consists solely of mid-level ontologies.

The explosion of interest in large language models (LLMs) has been accompanied by concerns over the extent to which generated outputs can be trusted, owing to the prevalence of bias, hallucinations, and so forth. Accordingly, there is a growing interest in the use of ontologies and knowledge graphs to make LLMs more trustworthy. This rests on the long history of ontologies and knowledge graphs in constructing human-comprehensible justification for model outputs as well as traceability concerning the impact of evidence on other evidence. Understanding the nature of arguments and argumentation is critical to each, especially when LLM output conflicts with what is expected by users. The central contribution of this article is to extend the Arguments Ontology (ARGO) - an ontology specific to the domain of argumentation and evidence broadly construed - into the space of LLM fact-checking in the interest of promoting justification and traceability research through the use of ARGO-based ‘blueprints’.

‘Eruv’ is a Hebrew word meaning literally ‘mixture’ or ‘mingling’. An eruv is an urban region demarcated within a larger urban region by means of a boundary made up of telephone wires or similar markers. Through the creation of the eruv, the smaller region is turned symbolically (halachically = according to Jewish law) into a private domain. So long as they remain within the boundaries of the eruv, Orthodox Jews may engage in activities that would otherwise be prohibited on the Sabbath, such as pushing prams or wheelchairs, or carrying walking sticks. There are eruvim in many towns and university campuses throughout the world. There are five eruvim in Chicago, five in Brooklyn, twenty three in Queens and Long Island, and at least three in Manhattan. The US Supreme Court is (like most other major US Federal Government buildings) located within the eruv of Washington DC. In many cases, not all of those living within or near the area of an actual or proposed eruv will themselves be Orthodox Jews, and this has sometimes led to protests against eruv creation. It is such protests which triggered the writing of this essay.

The World Wide Web Consortium (W3C) has sanctioned languages for ontology formulation, of which the most important is the Web Ontology Language (OWL). These have spawned in their turn powerful open-source software for developing and reasoning with ontologies and for querying data stores aligned to ontologies. Unfortunately, the resultant popularity of semantic technology has itself led to a situation where ontologies are now being created in heterogeneous, uncoordinated ways, thereby leading to a new problem of semantic stovepipes, and thus to a new failure of data integration and reuse. The best practices here described counteract this tendency by providing a set of principles and rules to lead to the development of ontologies in a consistent, non-redundant fashion.

Elon Musk famously predicted that an artificial intelligence superior to the smartest individual human would arrive by the year 2025. In response, Gary Marcus offered Musk a $1 million bet to the effect that he would be proved wrong. In specifying the conditions of this bet (which Musk did not take) Marcus lists the following ‘tasks that ordinary people can perform’ which, he claimed, AI will not be able to perform by the end of 2025. • Reliably drive a car in a novel location that they haven’t previously encountered, even in the face of unusual circumstances like hand lettered signs, without the assistance of other humans. • Learn to ride a mountain bike off-road through forest trails. • Babysit children in an unfamiliar home and keep them safe. • Tend to the physical and psychological needs of an elderly or infirm person. Each of these tasks involves the application of practical or tacit knowledge, or what is also called ‘knowing how’, which is to say knowledge of a sort that is captured not by means of sentences or propositions or explicit rules, but rather through the expertise demonstrated in human actions. The talk addresses the puzzle that nowhere in the AI literature do we find a discussion of knowing how as a feature of human intelligence.

This APA Blog Substack Newsletter extends a discussion with Barry Smith, who is a University at Buffalo (UB) professor of philosophy. Today Smith and his UB colleague and Co-Director of the National Center for Ontological Research John Beverley lead what one might call the academic arm of the Department of Defense and Intelligence Community Ontology Working Group (DIOWG). They outline here how ontology is serving as a career path for logicians and others interested in real-world applications of philosophy.

Ontology has been proposed as a solution to the 'Tower of Babel' problem that threatens the semantic interoperability of information systems constructed independently for the same domain. In information systems research and applications, ontologies are often implemented by formalizing the meanings of words from natural languages. However, words in different natural languages sometimes subdivide the same domain of reality in terms of different conceptual categories. If the words and their associated concepts in two natural languages, or even in two terminological traditions within the same language, do not have common referents in the real world, an ontology based on word meanings will inherit the 'Tower of Babel' problem from the languages involved, rather than solve it. In this paper we present evidence from a preliminary comparison of landscape terms in English with those in the Yindjibarndi language of northwestern Australia demonstrating that this problem is not just hypothetical. Some possible solutions are suggested.

This paper provides an axiomatic formalization of a theory of foundational relations between three categories of entities: individuals, universals, and collections. We deal with a variety of relations between entities in these categories, including the is-a relation among universals and the part-of relation among individuals as well as cross-category relations such as instance-of, member-of, and partition-of. We show that an adequate understanding of the formal properties of such relations – in particular their behavior with respect to time – is critical for formal ontology. We provide examples to support this thesis from the domain of biomedicine.

Batı’da teorik felsefe; Analitik Felsefe (AF), Kıta Felsefesi (KF) ve Felsefe Tarihi (FT) olmak üzere üçe ayrılır. Fakat üçünde de işler yolunda değildir. AF, felsefenin bir bilim olabileceği iddiasından kuşku duyduğu için gerçek dünyayla ilgilenmiyorken başından beri uygun bir teorik yöntem izlemeyen Kıta Felsefesinin uygulanışı, belirli politik ve etik yargılara hizmet edecek şekilde özelleştirilmiştir. FT çalışmalarının gidişatı ise eldeki eserin nesnel değerinden daha çok ilgili filozofun ait olduğu ulus veya kültüre göre bölgesel bir temelde gelişmiştir. Felsefede ilerleme sağlanacaksa bu ancak bahsi geçen tuzaklardan kaçınılarak gerçekleşebilir.

Christian von Ehrenfels was a student of both Franz Brentano and Carl Menger and his thinking on value theory was inspired both by Brentano’s descriptive psychology and by the subjective theory of economic value advanced by Menger, the founder of the Austrian school of economics. Value, for Ehrenfels, is a function of desire, and we ascribe value to those things which we either do in fact desire, or would desire if we were not convinced of their existence. He asserts that the needed theoretical understanding of values is to be achieved by generalizing economic laws of valuation to apply to value in general. The law of marginal utility, for example, is a law to the effect that the n+1st sample of a good which I receive is ceteris paribus less valuable than the nth sample (imagine that the samples in question are, for example, a series of identical ham sandwiches). The essay describes how Ehrenfels provides on this basis an account of the different types of values, both intrinsic and non-intrinsic. It outlines also Ehrenfels views on the problem of interpersonal value-comparisons and on the struggle for survival between different values of different types.

Ontology as a branch of philosophy is the science of what is, of the kinds and structures of objects, properties, events, processes and relations in every area of reality. ‘Ontology’ in this sense is a term often used by philosophers as a synonym of ‘metaphysics’ (a label meaning literally: ‘what comes after the Physics’), a term used by early students of Aristotle to refer to what Aristotle himself called ‘first philosophy’. But in recent years, in a development hardly noticed by philosophers, the term ‘ontology’ has gained currency in the field of computer and information science, and in information-driven research in bioinformatics and related areas. We examine these new developments in applied ontology, and show what lessons they might have for both philosophers and information scientists.

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.

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.