Distinguishing Computational Intelligence, Sentience, and Consciousness in Artificial Systems: A Hybrid Framework and Scenario-Based Analysis

Computational intelligence, sentience, and consciousness are distinct concepts that must be separated to advance AI development and ethics. Computational intelligence simulates rational decision-making without subjective experience, while sentient architectures model emotional states and inner conflict. Authentic self-awareness and meta-cognition differ from both computational logic and simulated feeling. A Hybrid Evaluation Framework combining Integrated Information Theory, Global Neuronal Workspace Theory, and ethical reasoning is proposed for scenario-based testing of AI systems.

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Abstract

This paper examines the critical distinctions between computational intelligence, sentience, and consciousness in artificial systems.It argues that clearly separating these concepts is essential for advancing technical development, ethical frameworks, and responsible societal integration of AI.By analysing how computational intelligence simulates rational decision-making but lacks internal subjective experience, and how sentient architectures introduce models of emotional states and simulated inner conflict, this work demonstrates the necessity of understanding both the capabilities and limitations of current AI.Consciousness theory is explored to show how authentic self-awareness and meta-cognitive processes differ from both computational logic and simulated feeling.These distinctions inform pressing questions regarding AI safety, ethical governance, and human-AI interaction.A Hybrid Evaluation Framework integrating Integrated Information Theory (IIT), Global Neuronal Workspace Theory (GNWT), and ethical reasoning is proposed and illustrated through scenario-based testing.