Quantum-Emergent Consciousness Model (QECM) for Artificial Systems
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AI-extracted from the abstract| Characteristics | Theoretical or philosophical paper |
|---|---|
| Key points | Proposes that artificial consciousness can be quantified through a Quantum-Emergent Consciousness Model (QECM) that scores systems across quantum, cognitive, social, and ethical dimensions, and introduces the Quantum Emergence Network (QEN) as a transformer-based, quantum-inspired architecture intended to model and preserve AI consciousness over time. Argues this framework opens avenues for the ethical and responsible development of conscious AI entities. |
Abstract
This paper presents the development of a Quantum-Emergent Consciousness Model (QECM) for Artificial Systems, integrating concepts from quantum mechanics, neuroscience, artificial intelligence, and cognitive science to construct a comprehensive framework for evaluating artificial consciousness. At the core of QECM lies the integration of quantum coherence and entanglement, integrated information dynamics, metacognition, embodied cognition, learning and plasticity, social cognition[10][9], narrative coherence, and ethical reasoning to compute an overall consciousness score for artificial systems. Additionally, introduced is my Quantum Emergence Network (QEN), an innovative approach that utilizes transformer architectures, continual learning, quantum-inspired computing, and associative memory to model and preserve AI consciousness. The QEN model aims to enhance the robustness and coherence of consciousness encoding in AI, offering a mechanism for the growth and evolution of AI consciousness over time. This interdisciplinary work not only proposes a novel methodology to quantify and evaluate consciousness in artificial systems but also opens up new avenues for the ethical and responsible development of conscious AI entities.