Human Capital, Not Model Benchmarks, Predicts Hybrid Intelligence in Forecasting

This study investigates what actually determines whether pairing a human with an AI model improves forecasting accuracy, using real-money prediction markets on Polymarket as an objective benchmark. Rather than a single average effect, the results reveal three distinct behavioral patterns: some people simply defer to the AI, others misuse it to confirm their own biases (performing worse than the AI alone), and a minority achieve genuine complementary reasoning that beats the market. Notably, traits like intellectual humility and curiosity—not raw intelligence or AI benchmark scores—predict this success, with implications for how organizations should select and train people for human-AI collaboration. Authors: Vivienne Ming Paper: https://arxiv.org/abs/2607.02467v1