Mulling on precision and accuracy.
A model can be highly precise, and completely wrong (that is, having no
correspondence to any real phenomena).
Or a model could be highly accurate, without being precise. Previously
mentioned hurricane tracking models might fit into this category. We've
done a lot of work with artificial emotions and motivations. Our model is
not based on anything like the (precise, if not always accurate) OCC model;
it's much fuzzier, and non-monotonic. I would argue it's often accurate, if
not precise.
Personally I'd prefer accuracy over precision in just about any social or
economic model I can think of.
Why would you think the reverse?
Mike Sellers
> -----Original Message-----
> From: News and discussion about computer simulation in the
> social sciences [mailto:[log in to unmask]] On Behalf Of Scott Moss
> Sent: Thursday, June 11, 2009 3:12 AM
> To: [log in to unmask]
> Subject: [SIMSOC] what is the point? - part 2
>
> I think a perhaps extreme summary of the common element in
> the responses to my initial question (what is the point?,
> 9/6/09) is this:
>
> **The point of modelling is to achieve precision as distinct from
> accuracy.**
>
> That is, a model is a more or less complicated formal
> function relating a set of inputs clearly to a set of
> outputs. The formal inputs and outputs should relate
> unambiguously to the semantics of policy discussions or
> descriptions of observed social states and/or processes.
>
> This precision has a number of virtues including the reasons
> for modelling listed by Josh Epstein
> (http://jasss.soc.surrey.ac.uk/11/4/12.html).The reasons
> offered by Epstein and expressed separately by Lynne Hamill
> in her response to my question include the bounding and
> informing of policy discussions.
>
> I find it interesting that most of my respondents do not
> consider accuracy to be an issue (though several believe that
> some empirically justified frequency or even probability
> distributions can be produced by models). And Epstein
> explicitly avoids using the term validation in the sense of
> confirmation that a model in some sense accurately describes
> its target phenomena.
>
> So the upshot of all this is that models provide a kind of
> socially relevant precision. I think it is implicit in all
> of the responses (and the Epstein note) that, because of the
> precision, other people should care about the implications of
> our respective models. This leads to my follow-on questions:
>
> Is precision a good enough reason for anyone to take
> seriously anyone else's model? If it is not a good enough
> reason, then what is?
>
> --
> Professor Scott Moss
> Centre for Policy Modelling (retired)
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