- I will remember that I didn't make the world and that it doesn't satisfy my equations.
- Though I will use models boldly to estimate
valueextinction risk, I will not be overly impressed by mathematics. - I will never sacrifice reality for elegance without explaining why I have done so.
- Nor will I give the people who use my model false comfort about its accuracy. Instead, I will make explicit its assumptions and oversights.
- I understand that my work may have
enormoustrivial effects on society and the economy, many of them beyond my comprehension,but I will continue to try to be relevantbut I will continue to advance my science anyway.
This is adapted from Emmanuel Derman and Paul Wilmott’s oath for economic modelers. See if you can spot my modifications. I tried to be subtle.
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As an outsider to the field of ecological modeling (but being well familiar with modeling in psychology) I see the relevance of four of the five points. However, re: point 3, why is sacrificing reality for elegance acceptable as long as you can explain why? Would not reality be the ultimate preference regardless? Yes, obviously models do not need to be real to make useful predictions; most psychology models of behaviour, for example, are function in nature. But... perhaps I'm unclear on your use of "elegance" in this context.
ReplyDeleteThe most important thing is to remember this.
ReplyDeleteI think of elegance from a couple of perspectives. The first is Occam's razor - "entities must not be multiplied beyond necessity" - in this case using as few state variables or covariates as possible to represent the system. "As possible" is largely based on a judgement call when building models for prediction, hence the possibility of overdoing it, and the need for point #3. The other way I think about it is in terms of how to model something - imagine there may be two ways of modeling a process. One is mathematically beautiful, which usually means an analytical solution is available, but makes some egregious assumption that might be true in some obscure case. The other method makes fewer assumptions, but can only be solved numerically on a computer. My math friends will often prefer the former, on the basis of mathematical elegance, because the validity or robustness of the underlying biology is not as important to them as it is to me.
Ah, ok, I see. Personally I hold with the first usage (i.e., simplicity), but probably more from the pragmatic perspective that the best scientific theories generally seem to be the simpler ones (the universe seems to "like" parsimony, and who am I to disagree?) than from any deeply esoteric theories on modeling. I also tend to fall on the side of biology over math, again for the pragmatic reason that it is a biological environment that I exist in, not an abstract mathematical one; or maybe because I'm a mathematic philistine and would rather find my beauty in "wine, women, and song" than proofs. : )
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