Human–AI collaboration in high-stakes decisions: a meta-analysis of healthcare and public sectors

This meta-analysis of 146 experiments in the healthcare and public sectors examines human–AI synergy versus augmentation amid substantial heterogeneity. We find that AI augmentation reliably improves human performance (Hedges’ g = 0.622), whereas synergy effects are generally negative, with AI alone often outperforming human–AI teams (Hedges’ g = −0.380), although publication bias favours positive augmentation results. Additionally, task type, AI transparency, and user expertise significantly moderate outcomes. These results caution against assuming inherent benefits of human–AI collaboration and instead support selective automation of structured tasks with human oversight for ethically complex decisions, guiding policymakers and leaders in optimizing human–AI integration.