Abstract

The rapid proliferation of artificial intelligence systems capable of naturalistic interaction has rendered the traditionalparadigm of AI as mere computational tool increasingly obsolete. Contemporary human-AI interaction is characterized byemergent relational dynamics that challenge existing theoretical frameworks and demand new conceptual models rootedin psychological science. This paper proposes the Cognitive-Emotional Symbiosis (CES) framework as a comprehensivetheoretical lens for understanding, designing, and evaluating human-centered artificial intelligence. Drawing uponestablished psychological theories of emotion, cognition, attachment, and social cognition, the CES framework posits thatoptimal human-AI interaction emerges from the dynamic interplay between cognitive processing mechanisms andemotional resonance pathways. The researcher synthesizes findings from affective computing, cognitive science, andhuman-computer interaction to demonstrate that emotional coherence, cognitive load management, and symbolicentrainment constitute the three pillars of sustainable human-AI symbiosis. The framework integrates insights fromTheory of Mind modeling, Load Minimization Theory, and neurosymbolic architectures to provide both explanatory powerand practical design guidance. The paper argues that the future of human-centered AI lies not in replicating humanintelligence but in establishing complementary cognitive-emotional partnerships that respect human psychological needswhile leveraging computational capabilities. This paper contributes a unified theoretical foundation for interdisciplinaryresearch and development, offering specific recommendations for psychologically-informed AI design, empirical validation,and ethical governance. The framework is presented as a hypothesis-generating theoretical contribution that identifiesspecific, testable propositions and measurable constructs for future empirical investigation.