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This textbook opens with a simple question: what does it mean for a machine to think? Bridging philosophy, cognitive science, cybernetics, and machine learning, it connects contemporary advancements in artificial intelligence with foundational debates about mind, perception, and truth. By examining the capabilities and limitations of AI systems including the phenomenon of AI hallucinations it interrogates whether machines can truly understand or if their intelligence is ultimately an illusion. This interdisciplinary textbook offers a timely exploration of the evolving relationship between humans and intelligent systems, shedding light on how AI challenges and reframes our understanding of cognition, knowledge, and the nature of intelligence itself and contains helpful key concept lists and summaries making it of great use to graduate students and professionals.
List of contents
Preface.- Acknowledgements.- Part I: What Minds Are Made of.- Chapter 1. Introduction.- Chapter 2. The Mind and the Body.- Chapter 3. Let s Get Physical.- Chapter 4. Cybernetics.- Chapter 5. Artificial General Intelligence.- Part II: How Machines Think.- Chapter 6. The Imitation Game.- Chapter 7. Computation.- Chapter 8. Neural Networks and Machine Learning.- Chapter 9. Deep Learning.- Chapter 10. Large Language Models.- Part III: Why Consciousness Matters.- Chapter 11. Consciousness.- Chapter 12. Hallucinations.- Chapter 13. Machine Consciousness.- Part IV: What Comes Next.- Chapter 14. Explaining AI.- Chapter 15. Quantum Minds.- Chapter 16. Artificial Minds, Human Ethics.- Chapter 17. Hard Problem of Consciousnesses.- Index.
About the author
Kristina Šekrst acquired a Ph. D. in Logic at the University of Zagreb, along with master’s degrees in Cognitive Linguistics, Philosophy, Comparative Linguistics, and Croatian Language. She teaches philosophical and linguistic courses at the University of Zagreb, and, in parallel, consults as a principal software engineer in the field of artificial intelligence, machine learning and AI ethics, combining academic with industrial expertise. Her industrial work includes providing consultancy for large language models for companies dealing with AI alignment, being a part of the team that discovered AI prompt injections, an issue that shaped the development of large language models. She is a co-author of one linguistics textbook, and an author of over 50 papers and talks in the field of artificial intelligence, philosophy of science and linguistics.
Summary
This textbook opens with a simple question: what does it mean for a machine to think? Bridging philosophy, cognitive science, cybernetics, and machine learning, it connects contemporary advancements in artificial intelligence with foundational debates about mind, perception, and truth. By examining the capabilities and limitations of AI systems – including the phenomenon of AI hallucinations – it interrogates whether machines can truly ‘understand’ or if their intelligence is ultimately an illusion. This interdisciplinary textbook offers a timely exploration of the evolving relationship between humans and intelligent systems, shedding light on how AI challenges and reframes our understanding of cognition, knowledge, and the nature of intelligence itself and contains helpful key concept lists and summaries making it of great use to graduate students and professionals.
