International Journal of Science, Engineering and TechnologyAuthors: Gowri Gireesh, Dr Abhilash S.Vasu
Abstract: Artificial intelligence (AI) has moved from task-oriented automation toward systems that communicate with, advise, and collaborate with humans. Consequently, psychological factors such as trust, emotion, cognitive bias, perceived intelligence, anthropomorphism, and decision confidence have become central to AI adoption. This paper presents a human-centered framework connecting psychological characteristics with AI system characteristics and interaction context. A focused literature synthesis is used to examine emotion-aware AI, human–AI trust, explainability, cognitive behavior, and the emerging influence of generative AI. The paper identifies research gaps in longitudinal assessment, culturally diverse datasets, multimodal psychological measurement, and calibration of appropriate—not excessive—trust. A proposed methodology combines questionnaire-based psychological measures, controlled human–AI experiments, behavioral indicators, and machine-learning analysis. The framework can support the design of trustworthy, transparent, adaptive, and psychologically compatible AI systems for education, healthcare, workplaces, and consumer applications.
