Traditional methods of distinguishing between human and artificial intelligence users typically rely on single-point assessments. This paper proposes the Continuous Turing Test (CTT), which evaluates human-like behavior over extended interactions. By incorporating principles from sociology and psychology, CTT aims to identify uniquely human traits through sustained engagement, including emotional consistency, contextual awareness, and authentic personal narrative development. We present a theoretical framework and implementation architecture, along with a comprehensive plan for empirical validation.