There's a sub-area of AI, since about the 1970s, that does try to do that, but it's very much at the research level. Modeling even simple "common sense" things is notoriously hard for computers (commonsense reasoning seems to require a large amount of implicit background information), so it's not clear that easy to unit-test coincides well with a human notion of simplicity and predictability.

That's one reason that, in addition to being an interesting challenge domain for AI researchers, it's interesting to logicians, who aim to come up with logics and decision procedures that can capture what a decision procedure in law looks like (classical first-order logic and theorem-proving don't seem to model it well). The main short-term application is to reasoning-support systems that can suggest potentially winning arguments, point out obvious holes in draft arguments you were going to make, etc., sort of the legal analogue of medical diagnostic systems.

A classic paper from 1977: http://www.cs.rutgers.edu/~mccarty/research/hlr77.pdf

A more recent system aimed at interactive use: http://www.ai.rug.nl/~verheij/publications/pdf/ai2004.pdf

A book, albeit priced at the usual Springer price-point that assumes no non-library human will buy it: http://www.amazon.com/gp/product/3642064329/ref=as_li_ss_tl?...