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.
By Dr Tom McClelland
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...
By Romain Salvi, Ouri Wolfson
The paper proposes a five‑layer implementation architecture for the S3Q theory of consciousness, mapping its three core conditions—grounded sensorimotor situatedness, internal simulation via a world model, and structural coherence between predictions and observations—to existing computational primitives. It integrates these components into a single pipeline that processes continuous, differentiable per‑object slot vectors, includes a developmental bootstrap sequence, and yields falsifiable predictions that cannot be produced by any subset of the architecture alone. The model further suggests that a basic sense of self emerges from linking actions to outcomes, and that behavior can be categorized into hesitation, curiosity, or avoidance based on outcome unexpectedness and valence.
"whyItMatters":"The architecture provides a concrete, testable framework that unifies theoretical conditions of consciousness with practical computational components, enabling empirical investigation of machine consciousness."
By Tetiana Grinberg, Katrina Schleisman, Patryk Laurent, Bogdan Udrea, Minda Myers, Brian Aufderheide, Luis El Srouji, Doyle Groves, Kevin Schmidt
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...
By Shamil Chandaria, Arvo Mu\~noz Mor\'an, Fernando Rosas, Anil Seth, Henry Shevlin, Marcus Hutter, Thore Graepel, Adam Bales, Iulia Comsa, Murray Shanahan, Ruben Laukkonen, Morten Kringelbach, Chris Frith, Shane Legg
The article explores how analogy informs judgments about consciousness, especially in the context of artificial intelligence. It introduces a causal framework that distinguishes between similarities in underlying factors and similarities in observable behavior, weighting source-target similarity by causal relevance. Applying this framework to biological systems explains why analogical support weakens as causal distance from humans increases, and to AI it shows that behavioral similarity alone offers limited evidence for consciousness due to poorly established causal correspondences.
By Keith J. Holyoak, Martin M. Monti
arXiv:2603.27597v2 Announce Type: replace
Abstract: Research on artificial consciousness increasingly shifts evaluation from behaviour to internal architecture. Theory-based indicators are used to up...
By Florentin Koch