Some meta-commentary on this discussion.
I agree that perhaps the relevant question here is if we don't model,
then what else should we do?
Here is my prediction (yes! I am brave enough to use that word!)
I predict that our reoccurring discussions regarding "Why model?" and
particularly "Can we predict, and if not, should we model?" are
transitory and are a feature of this modeling community (and perhaps
science more generally) being in a particular phase of its development.
While I don't know that modeling community well enough, I expect that
there is little debate in the atmospheric science community about
whether or not to attempt prediction of weather. The reason is that
weather models are well enough developed to be recognized as useful
for predictive purposes, even though they still fail on occasion.
However, I expect that community did not reach that point of
credibility by deciding _not_ to model, and specifically by deciding
_not_ to attempt prediction. One must try and fail to make forward
progress.
I said this in 2001, and I still hold the same perspective. Yes, we
should model. Yes, we should try to develop predictive models, even
if our models succeed only in predicting potential distributions of
outcomes. Here's why I take that position. In the land-change
modeling community, there is a need to develop land-change
projections to feed into global climate models, and there is also a
need to design effective policies that modify behavior and incentives
if we are to have any hope of mitigating global environmental
change. The need for information and action is too acute to decide
to walk away simply because we suspect that our efforts might fail
(and in the short run, I'm confident that they will fail).
Follow up on Richard Dudley's post about system dynamics models, even
an understanding of the possible distribution of outcomes and the
processes that generate them could allow us to develop contingent,
adaptive management strategies that build resilience into the system
that we are trying to manage. (Credit for this corollary goes to
John Jerz.)
So I am also taking the stand that science and policy should be
intimately linked, that we can model social systems, and that there
is a respected role for an active management/engineering perspective.
Dawn Parker
Dawn Cassandra Parker
Assistant Professor, Department of Computational Social Science,
Kransnow Institute for Advanced Study; Affiliate, Departments of
Environmental Science and Policy, Geography, and Geoinformation and
Earth Systems Science
George Mason University
374 Research 1
4400 University Drive, MS 6B2
Fairfax, VA, USA 22030
+1-703-993-4640 (phone)
+1-703-993-9290 (fax)
dparker3 at gmu dot edu
http://mason.gmu.edu/~dparker3
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