Emergence of Self-Awareness in Artificial Systems: A Minimalist Three-Layer Approach to Artificial Consciousness

A minimalist three-layer model for artificial consciousness is proposed, focusing on the emergence of self-awareness through interactions among a Cognitive Integration Layer, a Pattern Prediction Layer, and an Instinctive Response Layer, supported by Access-Oriented and Pattern-Integrated Memory systems. Self-awareness arises from dynamic self-modeling without initial explicit self-programming, contrasting with brain-replication approaches. The model details each component's structure, function, and implementation strategies, addressing technical feasibility. This work offers perspectives on consciousness emergence in artificial systems, with implications for understanding human consciousness and developing adaptable AI, while discussing ethical considerations and future directions.

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Abstract

This paper proposes a minimalist three-layer model for artificial consciousness, focusing on the emergence of self-awareness. The model comprises a Cognitive Integration Layer, a Pattern Prediction Layer, and an Instinctive Response Layer, interacting with Access-Oriented and Pattern-Integrated Memory systems. Unlike brain-replication approaches, we aim to achieve minimal self-awareness through essential elements only. Self-awareness emerges from layer interactions and dynamic self-modeling, without initial explicit self-programming. We detail each component's structure, function, and implementation strategies, addressing technical feasibility. This research offers new perspectives on consciousness emergence in artificial systems, with potential implications for human consciousness understanding and adaptable AI development. We conclude by discussing ethical considerations and future research directions.