[2603.27597] From indicators to biology: the calibration problem in artificial consciousness

Computer Science > Artificial Intelligence arXiv:2603.27597 (cs) [Submitted on 29 Mar 2026] Title:From indicators to biology: the calibration problem in artificial consciousness Authors:Florentin Koch View a PDF of the paper titled From indicators to biology: the calibration problem in artificial consciousness, by Florentin Koch View PDF Abstract:Recent work on artificial consciousness shifts evaluation from behaviour to internal architecture, deriving indicators from theories of consciousness and updating credences accordingly. This is progress beyond naive Turing-style tests. But the indicator-based programme remains epistemically under-calibrated: consciousness science is theoretically fragmented, indicators lack independent validation, and no ground truth of artificial phenomenality exists. Under these conditions, probabilistic consciousness attribution to current AI systems is premature. A more defensible near-term strategy is to redirect effort toward biologically grounded engineering -- biohybrid, neuromorphic, and connectome-scale systems -- that reduces the gap with the only domain where consciousness is empirically anchored: living systems. Comments: Subjects: Artificial Intelligence (cs.AI); Neurons and Cognition (q-bio.NC) Cite as: arXiv:2603.27597 [cs.AI]   (or arXiv:2603.27597v1 [cs.AI] for this version)   https://doi.org/10.48550/arXiv.2603.27597 Focus to learn more arXiv-issued DOI via DataCite (pending registration) Submission history From: Florentin Koch ...