When asked this question, Joshua Epstein would reply:

‘You are a modeler.’

In his recent article in JASSS he continues:

“Anyone who ventures a projection, or imagines how a social dynamic—an epidemic, war, or migration—would unfold is running some model.

But typically, it is an implicit model in which the assumptions are hidden, their internal consistency is untested, their logical consequences are unknown, and their relation to data is unknown. But, when you close your eyes and imagine an epidemic spreading, or any other social dynamic, you are running some model or other. It is just an implicit model that you haven’t written down.”(1.2-1.3)

Epstein goes on to imply that he thinks evaluating models by showing that their output matches empirical data isn’t a particularly useful test (as I have discussed previously). He emphasises that by making our implicit models explicit, we allow others to scrutinise the logic and coherence of that model and provide the opportunity for attempts at replication it (and the results).

In our paper reviewing concepts and examples of succession-disturbance dynamics in forest ecosystems George Perry and I used the distinction between modelling for explanation and modelling for prediction to structure our discussion. Epstein takes a similar tack, but the majority of his article seems to imply that he is more interested in the former than the latter. He suggests 16 reasons to model other than to predict. These are to:

1. Explain (very distinct from predict)
2. Guide data collection
3. Illuminate core dynamics
4. Suggest dynamical analogies
5. Discover new questions
6. Promote a scientific habit of mind
7. Bound (bracket) outcomes to plausible ranges
8. Illuminate core uncertainties
9. Offer crisis options in near-real time
10. Demonstrate tradeoffs / suggest efficiencies
11. Challenge the robustness of prevailing theory through perturbations
12. Expose prevailing wisdom as incompatible with available data
13. Train practitioners
14. Discipline the policy dialogue
15. Educate the general public
16. Reveal the apparently simple (complex) to be complex (simple)

After briefly discussing a couple of these points Epstein notably highlights the dictum attributed to George Box: “All models are wrong, but some are useful” (something I hope the students in my class are really beginning to appreciate). This idea leads neatly into Epstein’s final and, for him, most important point:

“To me, however, the most important contribution of the modeling enterprise—as distinct from any particular model, or modeling technique—is that it enforces a scientific habit of mind, which I would characterize as one of militant ignorance—an iron commitment to ‘I don’t know.’ That is, all scientific knowledge is uncertain, contingent, subject to revision, and falsifiable in principle. … One does not base beliefs on authority, but ultimately on evidence. This, of course, is a very dangerous idea. It levels the playing field, and permits the lowliest peasant to challenge the most exalted ruler—obviously an intolerable risk.”(1.16)

So, Why Model? To predict or to explain? As usual that’s probably a false dichotomy. The real point is that there are plenty of reasons to model other than to predict.