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[thread] 1 of 6

A big problem with Ferguson's code is that it doesn't produce the same results if the same seed is offered. Computers are deterministic, and randomness is really *pseudorandomness.* With the same seed, you're supposed to get the same result.
2 of 6

Example (simplified for Twitter):

Function: Random (X)
(X + 2) / 2

X is "randomly" selected, but the same steps always follow. For any given X, the answer is always the same, i.e., for X = 50, (50 + 2) / 2 will always be 26. In this case, X is the "seed."
3 of 6

If you haven't caught on to the problem with Ferguson's code producing different results for the same seed, it would be like saying:

Function: Random (X)
(X + 2) / 2

Run 1, X = 50: Result 26

Run 2, X = 50: Result 17

Run 3, X = 50: Result 4
4 of 6

When different outputs are generated from the same random seed, the problem isn't with the "randomness," but with the deterministic parts that come after. Ferguson's simulation isn't "garbage in, garbage out," but rather "anything in, unreliably random garbage out."
5 of 6

This introduces a series of problems, one of which is that the model is wholly incapable of producing results that can be reproduced. It can't be checked for accuracy.

But the UK shut down over that exact model, and it informed early shutdown in the US before IHME.
6 of 6

I don't expect perfection in any coding project, but I do expect them to operate within acceptable tolerances when they're used for something important. They also need to have reproducible results. Ferguson's model failed on both accounts. This is shameful.
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