method
active
method:theory-heavy-approachTheory-heavy approach
Assessing consciousness by evaluating whether AI systems perform functions similar to those associated with consciousness by scientific theories.
Neighborhood — ranked by edge-count
Papers (1)
paper
Claims (2)
claim
- Consciousness in AI is best assessed by drawing on neuroscientific theories of consciousness.supportsCentral methodological claim of the paper.
- Preferring architectural/functional assessment over behavioural tests.
Related by similarity (8)
cosine ≥ 0.65 · no typed edgeEntities in the same semantic neighborhood but without a typed relation to this one — candidates for new edges or unrecognized duplicates.
- Evaluation criteria for sentience based solely on observable response patterns, independent of substrate.
- Emerging theoretical work in the field; provides theoretical grounding but lacks practical implementation bridges.
- Foundational framework consisting of systems (wires), processes (boxes), and composition (wirings); basis for quantum and compositional reasoning.
- Formal mathematical framework (Bialek, Tononi, etc.) proposed to characterize autonomous agents and synergies between them.
- Framework treating cognitive processes as continuous dynamical phenomena rather than discrete computational steps; compatible with biogenic view.