Embracing model misspecification

When researchers focus on model design, they often worry whether the model is correct or not. I believe that we should accept the fact that all the models are wrong. The world is too complex to be captured by a single model: we are never able to acknowledge all the variables. Therefore, the answer to the question “Is the model correct?” is always “No”. It should not bother us: from the pragmatic perspective, it is irrelevant whether the model is correct or not. If we embrace the model misspecification, we can switch our attention to the question “What is the impact of deviations from the model on the decision-making?”

Recently, I was reading Making decisions under model misspecification
By Simone Cerreia-Vioglio, Lars Peter Hansen, Fabio Maccheroni, Massimo Marinacci · 2020cerreia2020. I am still in the process of understanding the technical part, but I was charmed by the Introduction, so I want to share quotes I liked from this paper and referenced Science and Statistics
By George E. P. Box · 1976box1976 and Model Uncertainty, Data Mining and Statistical Inference
By Chris Chatfield · 1995chatfield1995.