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\"This 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: 1. Human intelligence is a capability of the human brain and central nervous system, which is a complex dynamic system 2. 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 with our bank's computers, still so unsatisfactory? The First Edition was published the same week that ChatGPT was unleashed onto the world. In this Second Edition, shows how their arguments apply to new Large Language Models and bring up to date their other arguments relating to the limits of AI. They show why AI systems are best viewed as pieces of mathematics, which cannot think, feel, or will. They also demolish the idea that, with the help of AI, we could \"solve physics\" in a way that would allow us to create, in the cloud, a perfect simulation of reality in which we could enjoy digital immortality. Such ideas reveal a lack of understanding of physics, mathematics, human biology, and computers. There is still, as they demonstrate in an updated 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, and which are as impossible as AI systems that are intrinsically \"evil\" or able to \"will\" a takeover of human society. Key Changes to the Second Edition Shows how the arguments of the First Edition apply also to new Large Language Models Adds a treatment of human practical intelligence - of knowing how vs. knowing that - a topic that is ignored by the AI community Demonstrates why \"AI ethics\" should be relabeled \"ethics of human uses of AI\" Adds a new chapter showing the essential limitations of physics, providing a thorough grounding for the arguments of the book Demolishes the idea that we might already be living in a simulation. Jobst Landgrebe is a scientist and entrepreneur with a background in philosophy, mathematics, neuroscience, medicine, and biochemistry. Landgrebe is also the founder of Cognotekt, a German AI company which has since 2013 provided working systems used by companies in areas such as insurance claims management, real estate management, and medical billing. After more than 15 years in the AI industry he has developed an exceptional understanding of the limits and potential of AI in the future. Barry Smith is one of the most widely cited contemporary philosophers. He has made influential contributions to the foundations of ontology and data science, especially in the biomedical domain. Most recently, his work has led to the creation of an international standard in the ontology field (ISO/IEC 21838), which is the first example of a piece of philosophy that has been subjected to the ISO standardization process\"-- Provided by publisher.

In the era of \"big data,\" science is increasingly information driven, and the potential for computers to store, manage, and integrate massive amounts of data has given rise to such new disciplinary fields as biomedical informatics. Applied ontology offers a strategy for the organization of scientific information in computer-tractable form, drawing on concepts not only from computer and information science but also from linguistics, logic, and philosophy. This book provides an introduction to the field of applied ontology that is of particular relevance to biomedicine, covering theoretical components of ontologies, best practices for ontology design, and examples of biomedical ontologies in use.After defining an ontology as a representation of the types of entities in a given domain, the book distinguishes between different kinds of ontologies and taxonomies, and shows how applied ontology draws on more traditional ideas from metaphysics. It presents the core features of the Basic Formal Ontology (BFO), now used by over one hundred ontology projects around the world, and offers examples of domain ontologies that utilize BFO. The book also describes Web Ontology Language (OWL), a common framework for Semantic Web technologies. Throughout, the book provides concrete recommendations for the design and construction of domain ontologies.

First published in 1986, this book presents a reissue of 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. 1. Austrian Economics and Austrian Philosophy 2. The Second Austrian School of Value Theory 3. Intellectual Foundations of Austrian Liberalism 4. Markets and Morality: Austrian Perspectives on the Economic Approach to Human Behaviour 5. Brentano on Preference, Desire and Intrinsic Value 6. Emanuel Herrmann: On an Almost Forgotten Chapter of Austrian Intellectual History 7. The Austrian Connection: Hayek's Liberalism and the Thought of Carl Menger 8. Austrian Economics under Fire: The Hayek-Sraffa Duel in Retrospect

Ontology is the philosophical discipline which aims to understand how things in the world are divided into categories and how these categories are related together. This is exactly what information scientists aim for in creating structured, automated representations, called ‘ontologies,’ for managing information in fields such as science, government, industry, and healthcare. Currently, these systems are designed in a variety of different ways, so they cannot share data with one another. They are often idiosyncratically structured, accessible only to those who created them, and unable to serve as inputs for automated reasoning. This volume shows, in a non-technical way and using examples from medicine and biology, how the rigorous application of theories and insights from philosophical ontology can improve the ontologies upon which information management depends.

The majority of the papers in the present volume were presented at, or prepared in conjunction with, meetings of the Seminar for Austro-German Philosophy, a group of philosophers interested in the work of Brentano and Husserl and of the various thinkers who fell under their influence. One long-standing concern of the Seminar has been to trace the origins of present-day structuralism and related movements in the thought of nineteenth-century central Europe.

Why the current Bretton Woods-like international financial system, featuring large current account deficits in the center country, the United States, and massive reserve accumulation by the periphery, is not sustainable.