Future-proofing medical assessment: evaluating collaborative intelligence in the age of artificial intelligence

The accelerating integration of artificial intelligence (AI) into clinical practice presents a profound challenge to conventional medical education and assessment. Legacy assessment methods, focused on individual knowledge recall, fail to evaluate the competencies required for effective human-AI partnership. While numerous AI competency frameworks have emerged, they often overlook the synergistic wisdom needed for true collaboration. To address this gap, this article introduces and defines collaborative intelligence (CI), a dyad-centric construct focusing on the emergent capabilities of the human-AI team. CI represents the capability to critically appraise, ethically integrate, and judiciously act upon AI-derived insights. Its 5 core components are delineated: critical AI appraisal, information synthesis, adaptive judgment, ethical reasoning, and effective human-AI interaction. Subsequently, it proposes a novel assessment framework that discards rigid, time-based training stages in favor of a 4-stage competency spiral (novice to expert). This programmatic approach systematically maps assessment methods-including workplace-based assessments, high-fidelity simulations, and script concordance testing-to each CI component across the developmental spiral. Reengineering assessment to effectively measure CI is presented not merely as a technical adjustment but as a strategic imperative for cultivating physicians who possess the wisdom to harness algorithmic power while upholding the humanistic core of medicine, thereby ensuring safe and equitable care in the coming century.