HUMAN–AI COLLABORATION IN INTELLIGENT DECISION SUPPORT SYSTEMS

Abstract

Human–AI collaboration has emerged as a central paradigm in the evolution of intelligent decision support systems (IDSS). As artificial intelligence (AI) continues to advance in accuracy, scalability, and analytical depth, integrating human judgment with machine intelligence is essential for enhancing decision quality across domains such as healthcare, finance, governance, manufacturing, and disaster response. This article examines frameworks of human–AI collaboration, interaction models, algorithmic transparency, and shared decision-making methodologies. Two graphs illustrate decision accuracy improvements and the increasing adoption rate of hybrid human–AI systems. The article concludes with challenges—such as ethical concerns, interpretability, trust, and cognitive load—and future opportunities in adaptive collaboration, explainable AI, and context-aware IDSS designs.