Philosophy of Artificial Intelligence

From Turing to Large Language Models
1. Auflage 2026
ISBN: 978-1-041-10621-0
Verlag: Taylor & Francis Ltd

Buch, Englisch, 390 Seiten, Format (B × H): 156 mm x 233 mm, Gewicht: 598 g

Artificial intelligence presents deep and important philosophical questions, ranging from whether computers can think, whether large language models truly understand language, and whether AI can be creative, to moral and political issues, criminal justice, health, and the future of work.

In this much-needed book, Donald and Marco Gillies, a philosopher and computer scientist respectively, introduce and examine some of these key topics in the philosophy and science of AI, including:

- Alan Turing's imitation game and the beginnings of AI and expert systems.

- Induction and logic-based machine learning.

- Bayesianism and AI.

- The development of neural networks and deep learning.

- AI and moral issues, including social media and political radicalisation.

- Generative AI and the arts.

- Is an AI superintelligence possible?

- AI and the future of work.

Adopting a balanced historical and philosophical approach, Philosophy of Artificial Intelligence: From Turing to Large Language Models is ideal for those embarking on the study of this exciting topic, whether coming from philosophy or computer science. It provides a clear and engaging introduction to artificial intelligence.

Zielgruppe

Undergraduate Advanced

Autoren/Hrsg.

Gillies, Donald

Gillies, Marco

Fachgebiete

• Geisteswissenschaften Philosophie Philosophie: Allgemeines, Methoden

Inhaltsverzeichnis

Acknowledgements  Preface  Part 1: Turing and the Project for AI (1950s and 1960s)  1. Turing, Wittgenstein, and the Imitation Game 2. The First Attempts at AI  Part 2: The First Successes of AI and the Development of the Logic-Based Approach (c. 1970 to c. 2010)  3. The Success of Expert Systems 4. Philosophical Views of Induction 5. Induction and Logic-based Machine Learning 6. Successes and Criticisms of the Logic-Based Approach 7. The Dominance of Probability and Statistics in AI from the late 1990s to the early 2010s  Part 3: Neural Networks and Deep Learning  8. The Development of Neural Networks 9. Implications of Deep Learning for the Philosophy of Induction and Knowledge 10. Generative AI, Literature and the Visual Arts 11. Ethical Problems of Contemporary AI  Part 4: The Future of AI and Current Challenges  12. Is an AI Superintelligence Possible? 13. The Real Danger from AI: Mass Unemployment.  Index

Über Autor(innen)

Donald Gillies studied mathematics and philosophy at Cambridge as an undergraduate. In 1966 he began graduate studies in Professor Sir Karl Popper's department at the London School of Economics, and he completed his PhD on the foundations of probability in 1970 with Professor Imre Lakatos as supervisor. From 1968 to 1971, he was a Fellow of King's College, Cambridge, and thereafter followed a career at London University until his retirement in 2009. He is currently Emeritus Professor of Philosophy of Science and Mathematics at University College London. Donald Gillies developed an interest in the philosophy of AI in the 1990s, participating in two AI projects, as well as organizing two further projects in the philosophy of AI.

Marco Gillies is a Professor of Computing at Goldsmiths, University of London, and an expert on AI virtual humans for virtual reality. After completing his PhD at the University of Cambridge, he did post-doctoral work, and, in 2005, he published one of the first papers to apply machine learning to virtual humans. At Goldsmiths, a creative university famous for the Young British Artists Movement, he has helped pioneer the application of AI to the arts, including founding the Creative Computing Degree in 2008. His work since then has focused on human-centred and interdisciplinary AI, including working with dancers, psychologists, game developers, clinicians, and education researchers. His current work focuses on augmenting large language models (LLMs) with body language for natural communication.