Do Transformers Implement Global Workspace Dynamics?

This paper examines whether transformer language models instantiate a functional analog to Global Workspace Theory (GWT). Through a structured literature review spanning mechanistic interpretability, sparse autoencoders, consciousness theory, and brain-transformer alignment studies (through 2025), four candidate structural mappings are evaluated: the residual stream as shared workspace, attention heads as broadcast specialists, superposition as unconscious processing substrate, and induction-head phase transitions as ignition dynamics. Two critical disanalogies are identified — absence of temporal recurrence and absence of recurrent broadcast — and a falsifiable experimental programme is specified.