Content Inhalt » ƒon.space » Content 1. How is an Image Created in the Brain? 1.1 Synchronisation as a Basic Principle 1.2 First-Order Social and Neuronal Synchronisation 1.3 Second-Order Social and Neuronal Synchronisation 1.4 Third-Order Social and Neuronal Synchronisation 1.5 AI-Enhanced Synchronisation Levels 1.6 Computer Vision – How AI Learnt to See Brief History of Perception 2. How can an Image be Created in a Resonant Space? 2.1 Artificial Resonance Spaces 2.1.1 The Intertwining of Resonance and Synchronisation 2.2 Hyper Scanning: The Neural Basis of the Human-Human Interaction and the Emergence of Common Images 2.3 Human-Human vs. Machine-to-Machine Interaction: A Comparative Analysis 2.4 Human-Machine Interaction: The Emergence of Shared Visions and Imaginations 2.5 The Centaur Model 2.6 What is the Significance of Emergence, Entropy and Synchronization in Human-Machine Interaction? 2.7 The Emergence of an Entity of Entropy: The Future Centaur Model and its Implications for Global Challenges 3. The Vision of Distributed Superintelligence 3.1 Distributed Superintelligence and the Future Centauren: A Human-GAN Model for Ethical and Participatory KI Development 3.2 AI-Based Perspective Generation for Communities: Balancing Local Resonances and Global Challenges 3.3 From Individualisation to Global Resonance: Transforming Reward Systems in the Age of AI-Supported Perspective Generation 4. Human-AI Design for the 21st Century 4.1 Modelling Social and Global Entropy Using the Example of the Worldwide Water Balance 4.2 Indicator Selection and Weighting in the Human-GAN Model 4.3 Future Scenarios of Coevolution 4.4 Application of Social Entropy in the Context of a Human-AI-GAN Model for the Further Development of the Education System 4.5 Ethical Safety Precautions in Human-GAN-Concept