Some language agents are plausible candidates under a functional reading of global workspace theory.
Global workspace theory connects consciousness to a limited-capacity workspace that receives selected information and makes it available to other parts of a cognitive system. An LLM-based agent can have an ongoing loop in which observations, memory, planning, and tool results inform later decisions. That architecture makes it reasonable to ask whether a particular agent implements the selection, processing, and broad availability of information that the theory calls for.
Goldstein and Kirk-Giannini argue that existing language agents come close to satisfying the functional conditions they derive from global workspace theory and could satisfy them with relatively simple modifications. Their further claim that such an agent might have subjective experience is conditional on their interpretation of the theory. Other interpretations demand more, including different forms of recurrence or integration.
An agent's prompt history alone is not evidence that it has a global workspace. The relevant question is how information is selected, transformed, and used across the running system, and whether those mechanisms meet a defensible consciousness theory. The agent's concrete architecture must be examined before this argument applies to it.
Goldstein and Kirk-Giannini, A Case for AI Consciousness: Language Agents and Global Workspace Theory, especially sections 6–9: https://arxiv.org/html/2410.11407v1
Butlin et al., Consciousness in Artificial Intelligence: Insights from the Science of Consciousness, on theory-derived indicators: https://arxiv.org/abs/2308.08708