Philosophy of Artificial Intelligence : From Turing to Large Language Models

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Philosophy of Artificial Intelligence : From Turing to Large Language Models

Gillies, Donald/ Gillies, Marco

ウェブストア価格 ¥13,516（本体¥12,288）
Routledge（2026/09発売）
外貨定価 US$ 57.99
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製本 Paperback:紙装版/ペーパーバック版／ページ数 320 p.
言語 ENG
商品コード 9781041106210

Full Description

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 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.

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