Integrated Method for Policy Making Using Argument Modelling and Computer Assisted Text Analysis
post by staticIP · 2012-09-08T16:13:17.835Z · LW · GW · Legacy · 4 commentsContents
4 comments
IMPACT is conducting original research to develop and integrate formal, computational models of policy and arguments about policy, to facilitate deliberations about policy at a conceptual, language-independent level. These models will be used to develop and evaluate a prototype of an innovative argumentation toolbox for supporting open, inclusive and transparent deliberations about public policy.
The IMPACT project, funded by the EU, is building a tool to make debates easier to keep track of, and presumably more rational. It look sort of like an AI, where all the dirty work and low level stuff is done by humans, but the actual result is determined by the structure of the machine. Certainly you could subvert it by placing incorrect standards of evidence on particular papers/arguments, but on the whole it looks interesting.
Sort of a wiki-decision framework.
What do you think about this type of project? Are there any existing argument modelling languages, like UML for arguments? Is this the best approach?
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comment by roryokane · 2012-10-13T01:10:18.133Z · LW(p) · GW(p)
A decision matrix is a very simple tool that can give an overview of an argument. Points for and against each alternative have positive and negative values.
However, if those values themselves depend on other calculations, or are interdependent, the decision matrix provides no way to display that, so it is not a complete modelling language.
Replies from: staticIP↑ comment by staticIP · 2012-10-13T01:14:11.378Z · LW(p) · GW(p)
Not quite in the same class as the listed software. Useful, I've used them, but they get really complicated with more variables. If you look at what they've got, it doesn't exactly seem bayesian. They don't work of probability, but off of absolute truths. Debating each piece of minutia in a sort of tree structure. It could definitely be improved upon.