1. "Mathematical models are a great way to explore questions. They are also a dangerous way to assert answers. Asking models for certainty or consensus is more a sign of the difficulties in making controversial decisions than it is a solution..." https://www.nature.com/articles/d41586-020-01812-9

2. "Modellers must not be permitted to project more certainty than their models deserve; and politicians must not be allowed to offload accountability to models of their choosing."

3. "Most modellers are aware that there is a trade-off between the usefulness of a model and the breadth it tries to capture. But many are seduced by the idea of adding complexity in an attempt to capture reality more accurately."

4. "Complexity is too often seen as an end in itself. Instead, the goal must be finding the optimum balance with error."

[Needless to say I am a fan of simple models, that understand & explain processes]

5. "Opacity about uncertainty damages trust. A message from the field of sociology of quantification is that trust is essential for numbers to be useful. Full explanations are crucial."

[Modellers should spend a lot of time explaining results, call out incorrect use, etc]

6/6. A good read on the use of models in policy. The best summary though is from @Climansen:
1.Mind the assumptions
2.Mind the hubris
3.Mind the framing
4.Mind the consequences
5.Mind the unknowns https://twitter.com/Climansen/status/1275750007711375360

Bonus tweet: My background is mathematics & physics, essentially, I am a modeller. Agree with pretty much all that is in the commentary.

Perhaps the strive to add complexity as precedence over understanding how models do what they do is my biggest concern (of modelling)