From indicators to biology: the calibration problem in artificial consciousness

• URL: http://arxiv.org/abs/2603.27597v1
• Date: Sun, 29 Mar 2026 09:39:27 GMT
• Title: From indicators to biology: the calibration problem in artificial consciousness
• Abstract summary: Recent work on artificial consciousness shifts evaluation from behaviour to internal architecture.<n>This is progress beyond naive Turing-style tests.<n>But the indicator-based programme remains under-calibrated.
• Score: 0.0
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• 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.

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