Model abuse... stop it now!

I think we would benefit from better and more realistic models of systems in economics and finance, better models for imagining and assessing risks, and so on. But it is true that having a better model is one thing, using it another entirely. A commenter on my recent Bloomberg piece on agent-based models pointed me to  this post, which looks at some examples of how risk models in finance (ones this author had helped develop) were repeatedly abused and distorted to suit the needs of higher ups:

For a person like myself, who gets paid to “fix the model,” it’s tempting to do just that, to assume the role of the hero who is going to set everything right with a few brilliant ideas and some excellent training data. Unfortunately, reality is staring me in the face, and it’s telling me that we don’t need more complicated models. If I go to the trouble of fixing up a model, say by adding counterparty risk considerations, then I’m implicitly assuming the problem with the existing models is that they’re being used honestly but aren’t mathematically up to the task. But this is far from the case – most of the really enormous failures of models are explained by people lying. Before I give three examples of “big models failing because someone is lying” phenomenon, let me add one more important thing. Namely, if we replace okay models with more complicated models, as many people are suggesting we do, without first addressing the lying problem, it will only allow people to lie even more. This is because the complexity of a model itself is an obstacle to understanding its results, and more complex models allow more manipulation.