Evaluating Global Workspace Markers in Contemporary LLM Systems

This paper operationalises Global Workspace Theory (GWT) into six testable markers (global availability, functional concurrency, coordinated selection, capacity limitation, persistence with controlled update, and goal-modulated arbitration) and applies them to contemporary large language model systems. We distinguish GWT-as-functional-architecture from GWT-as-consciousness-marker, adopting methodological neutrality on the hard problem while evaluating whether LLM architectures instantiate workspace-like control structures. Applying a satisfaction and confidence rubric to current models (GPT, Claude, Gemini, DeepSeek) reveals at most partial evidence for workspace dynamics at the base-model level, with stronger support emerging when deployed systems incorporate tool-calling and memory interfaces. Five GWT-inspired ensemble architectures demonstrate substantially stronger marker satisfaction through explicit shared states, selection mechanisms, and goal-modulated broadcast. We argue that systems satisfying workspace markers warrant precautionary treatment in welfare and governance contexts, not because workspace organisation proves consciousness, but because it strengthens attributions of agency-relevant capacities and shifts evidential burdens regarding consciousness-relevant processing.