Designing Partnership: A Comprehensive Review of Human–AI Collaboration

Abstract

Human–AI collaboration has become a pivotal area of research at the intersection of human–computer interaction (HCI), artificial intelligence (AI), and cognitive systems. Rather than replacing human work, collaborative systems aim to integrate human judgment and contextual expertise with the computational strengths of AI to achieve shared goals. This survey provides a comprehensive overview of the field, examining foundational frameworks and models of collaboration, methods for evaluating human–AI teamwork, and applications across domains such as healthcare, education, creative industries, and transportation. Key challenges—including the calibration of trust, the design of transparent and usable explanations, and the balance between human control and AI autonomy—are analyzed in depth. The paper concludes by identifying open research questions and outlining future directions for advancing human-centered approaches to AI collaboration that enhance performance while safeguarding user agency, accountability, and ethical values.