Calibration and transfer in indicator-based assessments of artificial consciousness
Research on artificial consciousness increasingly shifts evaluation from behaviour to internal architecture. Theory-based indicators are used to update probability assignments. This improves on behavioural tests but raises two distinct problems. First, these assignments cannot currently be calibrated against independently established artificial consciousness outcomes. Second, their evidential relevance is transferred from biological cases without independent support that indicator-consciousness relations remain stable across substrates. This commentary distinguishes calibration from transfer and adapts the iterative natural-kind strategy by proposing a preliminary, theory-relative compara...
| Authors | Florentin Koch |
|---|---|
| Primary category | cs.AI |
| Published | 29 March 2026 |
| Last updated at source | 22 September 2026 |
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