What Would Convince You of AI Consciousness?

This project combines a qualitative interview study with a structured taxonomy of the field's disagreements. The work maps how consciousness researchers and field-adjacent participants reason about AI consciousness, what evidence would actually shift their credence, and whether AI consciousness would carry moral weight.

The premise is that experts in this field often talk past each other when they state their positions. Asking "what would convince you?" surfaces the epistemic structure underneath the conclusions and separates substantive disagreement from semantic disagreement, where two researchers can say "consciousness requires X" and mean very different things by X.

The study uses semi-structured interviews with consciousness scientists, AI researchers, philosophers, and policy-adjacent thinkers. The protocol pushes past stated beliefs toward concrete shifts: what specific evidence, experiment, and result, and how much would it move them.

Analysis runs in two passes. Content analysis applies a literature-derived taxonomy, classifying claims at the conceptual, methodological, theoretical, metaphysical, or normative level, and separating debates about AI consciousness from debates about AI moral consideration. Thematic analysis surfaces emergent patterns the taxonomy misses and the factors that shape participants' views.