From root: Why should I simulate the real world?

What can a simulation do that a prediction cannot?

It can show you why. With simulations of the real world, in contrast to other predictive AI approaches, you can interrogate the internal state of the system to help validate the assumptions used in making a decision.

This can be a real advantage for decision-making technologies, since human users usually need to justify their decisions through structured reasoning.

Example: Predictions only vs simulations

Prediction only

There is a forecast line, but the internal logic is hidden. If the prediction is wrong, it's difficult to interrogate why.

Simulation/mechanistic model

References and further reading

Epstein, Joshua M. 2008. “Why Model?” Journal of Artificial Societies and Social Simulation 11 (4): 12. https://www.jasss.org/11/4/12.html.

Hardwick, Robert J. 2025. “What are simulations for?” umbralcalculations, November. https://umbralcalc.github.io/posts/what_are_simulations_for.html.

Hardwick, Robert J. 2026. “Why should I simulate the real world?” umbralcalculations, May. https://umbralcalc.github.io/posts/why_should_i_simulate_the_real_world.html.

Leutbecher, Martin, and Tim N. Palmer. 2008. “Ensemble Forecasting.” Journal of Computational Physics 227 (7): 3515–39. https://doi.org/10.1016/j.jcp.2007.02.014.