This book provides a new perspective on the design of computer systems by focusing on how they support human cognition and communication. It challenges traditional views of artificial intelligence and offers insights into how computers can be designed to enhance human understanding and collaboration.
In 'Representation and Reality', Hilary Putnam critiques functionalism and the computational analogy for understanding mental states. He argues that these models cannot adequately explain belief, reasoning, rationality, and knowledge. The book also explores the indeterminacy of translation and the role of environment in determining meaning, using his famous twin-earth example.
In 'Mind in Life', Evan Thompson synthesizes insights from biology, neuroscience, cognitive science, and phenomenology to explore the connection between life and consciousness. He argues that life and mind share common principles of self-organization, challenging traditional views that separate these concepts. The book offers a new perspective on the nature of life and consciousness, integrating objective and subjective experiences.
In this book, Roger Penrose challenges the idea that human consciousness can be replicated by computers. He delves into various subjects including algorithms, Turing machines, complexity theory, quantum mechanics, and the basics of modern physics to support his argument that human cognition is fundamentally non-computable. Penrose discusses the limitations of Turing machines, the incompleteness of formal systems as shown by Godel's proof, and the necessity of a unified theory of quantum gravity to explain human consciousness. The book is a detailed and thought-provoking journey through mathematics, computer science, philosophy, and physics, making it a must-read for those interested in the nature of mind and the relationship between physics and consciousness.
This book by Douglas Hofstadter is a comprehensive and interdisciplinary work that explores the interrelated ideas of Kurt Gödel, M.C. Escher, and Johann Sebastian Bach. It delves into concepts such as self-reference, recursion, and the limits of formal systems, particularly through Gödel's Incompleteness Theorem. The book uses dialogues between fictional characters, including Achilles and the Tortoise, to intuitively present complex ideas before they are formally explained. It covers a wide range of topics including cognitive science, artificial intelligence, number theory, and the philosophy of mind, aiming to understand how consciousness and intelligence emerge from formal systems[2][4][5].
Professor Mark Bishop does not think that computers can be conscious or have phenomenological states of consciousness unless we are willing to accept panpsychism which is idea that mentality is fundamental and ubiquitous in the natural world, or put simply, that your goldfish and everything else for that matter has a mind. Panpsychism postulates that distinctions between intelligences are largely arbitrary.
Mark’s work in the ‘philosophy of AI’ led to an influential critique of computational approaches to Artificial Intelligence through a thorough examination of John Searle's 'Chinese Room Argument'
Mark just published a paper called artificial intelligence is stupid and causal reasoning wont fix it. He makes it clear in this paper that in his opinion computers will never be able to compute everything, understand anything, or feel anything.
00:00:00 Tim Intro
00:15:04 Intro
00:18:49 Introduction to Marks ideas
00:25:49 Some problems are not computable
00:29:57 the dancing was Pixies fallacy
00:32:36 The observer relative problem, and its all in the mapping
00:43:03 Conscious Experience
00:53:30 Intelligence without representation, consciousness is something that we do
01:02:36 Consciousness helps us to act autonomously
01:05:13 The Chinese room argument
01:14:58 Simulation argument and computation doesn't have phenomenal consciousness
01:17:44 Language informs our colour perception
01:23:11 We have our own distinct ontologies
01:27:12 Kurt Gödel, Turing and Penrose and the implications of their work
Machine Learning Street Talk (MLST) 
