Philosophical Considerations of Artificial Consciousness

Whether AI can achieve consciousness has evolved from philosophical speculation to scientific inquiry, driven by the rapid advances in AI. The powerful capabilities of large language models necessitate a fundamental reconsideration of artificial consciousness beyond human-centric frameworks. We address a critical gap in AI philosophy: how to conceptualize consciousness in AI that exhibits sophisticated cognition without subjective phenomenology. We propose para-consciousness as a non-phenomenal form of artificial consciousness that emerges from self-referential world-modeling in artificial neural networks. Unlike human consciousness, anchored in qualia, para-consciousness manifests as functional coherence through latent space dynamics, enabling contextually adaptive behavior without requiring a first-person experience. We present a novel framework that reframes the hard problem of consciousness for machines as the problem of grounded coherence, explaining why predictive processes yield contextually meaningful outputs without requiring embodied intentionality. Para-consciousness shifts the paradigm from simulating human-like subjectivity to engineering verifiable operational awareness. We analyze the impossibility of AI achieving human unified consciousness and the possibility of AI achieving human-like consciousness from staged consciousness.