AI Consciousness Requires Validated Models of Human Consciousness - Chopra, Paras (Proceedings of the AAAI Symposium Series, 2026)
Debates about AI consciousness often proceed without grounding the concept in empirically validated models. This position paper argues that meaningful claims about AI consciousness should be licensed by (and graded by confidence in) models validated on humans. Drawing on Quine's observation sentences and pragmatic philosophy of science, we argue that all scientific observation ultimately depends on human perceptual agreement, including observations about consciousness itself. Without validated human models that make testable predictions about conscious experience, the question ``Is this AI conscious?'' lacks sufficient empirical grounding necessary for scientific progress. We propose a human-first methodology: identify measurable phenomena associated with consciousness in humans, build predictive models, validate them empirically, and only then apply these models to AI systems. This approach accelerates philosophical debates into productive scientific inquiry.