Consciousness Theories Applied to Artificial Neural Networks [#991178]

Free Download Consciousness Theories Applied to Artificial Neural Networks
English | December 21, 2025 | ASIN: B0GBPFFFP1 | 437 pages | Epub | 421.96 KB
The 21st century presents us with an unparalleled opportunity to interrogate the nature of consciousness. For centuries, the study of the mind was largely confined to philosophical discourse, grappling with abstract concepts and thought experiments. While invaluable, these approaches often lacked the grounding in empirical verification that characterizes modern science. The emergence of Artificial Neural Networks (ANNs), inspired by the biological architecture of the brain, has fundamentally altered this landscape. These complex computational systems, capable of learning, adaptation, and sophisticated information processing, now serve as powerful tools for modeling cognitive functions and, crucially, for empirically testing theories of consciousness. This book is born from the confluence of these disciplines: cognitive science, neuroscience, computer science (with a strong emphasis on Artificial Intelligence), and philosophy of mind. Our central thesis is that ANNs provide a fertile ground for the empirical validation of major consciousness theories. By implementing these theories in computational models, we can derive testable predictions, design experiments, and gather evidence that was previously inaccessible. We will navigate the intricate theoretical frameworks, from Integrated Information Theory (IIT) and Global Workspace Theory (GWT) to Higher-Order Thought (HOT) theories and Predictive Processing, examining their core tenets and their implications for artificial systems. Subsequently, we will explore the architectural foundations of modern ANNs-Recurrent Neural Networks, Transformers, and beyond-as potential substrates for consciousness. The heart of this book lies in its critical examination of the methodologies used to bridge theory and practice: how to derive testable predictions from abstract theories, how to design ANN experiments, and how to interpret the resulting data. We will confront the profound challenges inherent in empirically validating consciousness, including the very definition of consciousness, the problem of subjective experience, and the ethical considerations that arise as we approach the possibility of artificial sentience. This is a rigorous exploration for academics, researchers, and advanced students seeking to understand the empirical frontiers of consciousness research in artificial intelligence, moving beyond speculation towards evidence-based understanding.