I found this 2009 JSA talk by Thad Tarpey to provide a useful explanation and commentary on the Box passage.
Here’s the abstract:
Students of statistics are often introduced to George Box’s famous quote: “all models are wrong, some are useful.” In this talk I argue that this quote, although useful, is wrong. A different and more positive perspective is to acknowledge that a model is simply a means of extracting information of interest from data. The truth is infinitely complex and a model is merely an approximation to the truth. If the approximation is poor or misleading, then the model is useless. In this talk I give examples of correct models that are not true models. I illustrate how the notion of a “wrong” model can lead to wrong conclusions.