C: Quantify the social cost of forecast errors to guide investment in model accuracy.

Sun, 19 Apr 2026 18:32:09 +0000

**C: Quantify the Social Cost of Forecast Errors to Guide Investment in Model Accuracy** In an era driven by data, predicting trends shapes decisions across industries—from finance and healthcare to urban planning and climate policy. But when forecasts fail, the consequences ripple far beyond financial losses. Understanding the true social cost of these errors is critical to making smarter, more responsible investments in model accuracy. This concept is reshaping how decision-makers evaluate risk, allocate resources, and build trust with the public. **Why Quantifying Forecast Errors Is Gaining Broader Attention in the US** Across the United States, rapid technological adoption and rising public scrutiny are amplifying the need to measure how inaccuracies in predictive models affect society. From election modeling missteps to flawed economic forecasting and healthcare risk assessments, high-stakes predictions increasingly influence individual lives and community outcomes. As public awareness grows, stakeholders demand clearer insight into what’s lost when models fall short. This shift reflects a growing expectation: forecasting isn’t just about accuracy—it’s about accountability and protecting social well-being.