arXiv:2608. 19215v1 Announce Type: new Abstract: Given deep uncertainty about the possibility of artificial consciousness, it is unclear how we should treat potentially sentient AI.
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The Digital Consciousness Model (DCM) is introduced as a systematic, probabilistic framework for evaluating evidence of consciousness in AI systems, drawing on multiple leading theories of consciousness. Initial results indicate that, while the evidence suggests 2024 large language models (LLMs) are not conscious, this conclusion is not decisive and is weaker than evidence against consciousness in simpler AI systems.
arXiv:2601. 21016v2 Announce Type: replace Abstract: Imagine an Artificial Intelligence (AI) that perfectly mimics human emotion and begs for its continued existence.
arXiv:2606. 05528v1 Announce Type: new Abstract: Existing frameworks assess whether AI systems might be conscious but provide no guidance on what to do with that assessment.
arXiv:2609.35618v2 Announce Type: replace Abstract: The question of AI consciousness is one of the most urgent pre-emptive problems in philosophy and computer science, yet progress is hampered by a c...
arXiv:2606. 06380v1 Announce Type: cross Abstract: The question of whether artificial systems can be conscious remains open, in part because existing approaches either evaluate systems against theory-derived checklists (discriminative) or engineer consciousness-inspired modules directly (architectural); both leave open whether observed structures are artifacts of human language priors.
arXiv:2608.28824v1 Announce Type: new Abstract: Currently, in biological systems Neural Correlates of Consciousness (NCCs) are characterized in terms of EEG and FMRI signals. Unfortunately, this char...