Number-crunching math models may give policy makers major headache

A new study shows that mathematical models may be too complex and deliver wrong answers.

Environmental/climate sciences, hydrology and epidemiology are some of the areas where models are being used to gain more accurate insights.

More complicated models tend to produce more uncertain estimates, so the pursuit of complex models as tools to produce more accurate projections and predictions might not deliver.

Science Advances published the findings of researchers from several universities. Expanding models without checking how extra detail adds uncertainty limits their usefulness as tools to inform policy decisions in the real world, according to them.

As science keeps on unfolding secrets, models keep getting bigger to reflect the world around us. It is assumed that more detailed models produce better predictions.

Adding new parameters may bring new uncertainties into the model, which may not deliver the results we seek. New uncertainties make the model's output fuzzier at every step of the way.

This tendency to produce more inaccurate results affects any model without training or validation data used to check its output's accuracy.

The drive to make more detailed mathematical models should be reexamined.

Before making the model more complex, modelers should calculate the model's effective dimensions. The uncertainty in the output can be checked by adding model complexity. It's important for models to have this information in order to make policy. When a model is upgraded with novel mechanisms, both modelers and policy makers benefit.

Uncertainty and sensitivity analysis are not usually submitted by modelers. Not many scholars are interested in running such an analysis on their model if it shows that the emperor isn't real.

Scholars and the public can't ponder the appropriateness of the models' assumptions due to excess complexity. Global hydrological models assume that irrigation improves crop production and water use, which is contrary to traditional irrigator practices.

More information: Arnald Puy, Models with higher effective dimensions tend to produce more uncertain estimates, Science Advances (2022). DOI: 10.1126/sciadv.abn9450. www.science.org/doi/10.1126/sciadv.abn9450 Journal information: Science Advances Citation: Number-crunching math models may give policy makers major headache (2022, October 19) retrieved 19 October 2022 from https://phys.org/news/2022-10-number-crunching-math-policy-makers-major.html This document is subject to copyright. Apart from any fair dealing for the purpose of private study or research, no part may be reproduced without the written permission. The content is provided for information purposes only.