Easing bias refers to the tendency in forecasting or data analysis to underestimate extreme outcomes, often favoring more moderate predictions. It is used in risk management and AI training to improve model accuracy by adjusting for overconfidence. Businesses, researchers, and policymakers benefit by making more realistic decisions and reducing costly errors.
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