Time, Identity and Consciousness in Language Model Agents

Researchers introduce a new framework using Stack Theory to evaluate machine consciousness in AI language models by distinguishing between agents that can talk about having a stable identity versus those actually organized with persistent self-structure. The methodology uses temporal scaffolding and persistence scores to assess whether AI agents demonstrate genuine identity continuity or merely simulate it through language.