However, it is a very different situation when the importance, or impact or possible use of models is exaggerated to an audience of non-modellers, who are likely to take their pronouncements at face value. This includes promises in grant applications, journal publications, public lectures and discussion with policy actors/advisers. They will not be in a position to properly evaluate the claims made and have to take the results on trust (or ignore them along with the advice of other 'experts' and 'boffins').
The danger is that the reputation of the field will suffer when people rely on models for purposes that they are not established for. The refrain could become "Lies, damned lies, statistics and simulations". This is especially important in this era where scientists are being questioned and sometimes ignored.
Some of the reasons for such hype lies in the issues discussed in previous posts and some seem to lie elsewhere.
- Confusions about purpose, thinking that establishing a simulation for one purpose is enough to suggest a different purpose
- Insufficient validation for the use or importance claimed
- Being deceived by the "theoretical spectacles" effect [note 1] -- when one has worked with a model for a while that we tend to see it through the "lens" of that model. Thus we confuse a way of understanding the world for the truth about it.
- Sheer fraud: we want a grant, or to get published, or to justify a grant, so we bend the truth about our models somewhat. For example promising far more in a grant proposal than we know we will able to deliver.
Note 1: "theoretical spectacles" was a phrase introduced by Thomas Kuhn to describe the effect of only noticing evidence that is consistent with the theory one believes.