> If the top scientists from well-funded teams came up with estimates that were so wildly off, I'm not sure why we have any hope of getting these things right.

> If the top scientists from well-funded teams came up with estimates that were so wildly off, I'm not sure why we have any hope of getting these things right. A "top" scientist produces a ton of publications and brings in a lot of grant money. You don't need to be right to be a "top" scientist. Change the incentives and you'll change the outcomes. The failure of blind predictions (i.e., without the opportunity to calibrate the model to the data) says more about the culture than whether this is possible. Weather forecasting does a fairly good job: https://journals.ametsoc.org/doi/full/10.1175/2011MWR3525.1 https://journals.ametsoc.org/doi/full/10.1175/2011MWR3525.1 It's instructive to figure out why. I'd say it's because weather forecasters have a ton of data, forecasts can quickly be proven right or wrong (so they get a lot of feedback), and they have a culture emphasizing accuracy. It also helps that they're modeling physics, though various submodels (turbulence, etc.) may not be any more credible than the models in epidemiology. Blind predictions have been tried in a variety of domains. I'm most familiar with computational fluid dynamics, e.g.: https://www.sciencedirect.com/science/article/abs/pii/S0379711209000034 https://www.sciencedirect.com/science/article/abs/pii/S03797... https://ntrs.nasa.gov/search.jsp?R=19970027380 https://ntrs.nasa.gov/search.jsp?R=19970027380 (There are many more examples.) As I recall, it's not uncommon for different groups even using the same software to come up with radically different predictions. I'd say scientists and engineers need much more practice making blind predictions. Blind prediction exercises should occur regularly. There's a yearly competition to predict the heat release rate of a Christmas tree: https://fpe.umd.edu/events/christmas-fire-safety-demo https://fpe.umd.edu/events/christmas-fire-safety-demo I entered one year. Rather than using a fancy computer model, I merely smoothed last year's data and scaled it by the ratio of the mass of this year's tree to the mass of last year's tree. As I recall, I did better than most!