David Brin proposes using a computer model to simplify the U.S. tax code

The United States revenue enhancement code is a thing of wonderment in its harebrained complexness . But what if we could massively simplify the code — without exchange anybody ’s tax burden ? David Brin , source of the Uplift novels , has a suggestion .

write in the Daily Kos , Brin suggests a “ no losers ” revamp of the tax code , that eliminates tons of provision but ensures that the nett upshot will not alter the taxation place for 100 representative classes of Americans . You could model the tax computer code on a data processor , and program it to eliminate redundant viands without cause any major changes to revenue enhancement financial obligation . drop a line Brin :

There is nothing on Earth like the US taxation codification . It is an super complex system that nobody understands well . But it is unique among all the complex thing in the macrocosm , in that it ’s complexity is perfectly replicated by the MATHEMATICAL MODEL of the organisation . Because the mathematical model is the system .

Ideapad3i

Hence , one could put the entire US tax code into a redundant reckoner somewhere , try a myriad inputs , outputs … and tweak every parametric quantity to see how outputs change . There are agency who already do this , day by day , in response to congressional queries . alteration of the framework must be tested under a wide stove of boundary condition ( sample taxpayers . ) But if you are thoroughgoing , the results of the model will be the result of the organization .

Now . I ’m tell ( by some people who know about such affair ) that it should be easy enough to create a program that will take the revenue enhancement code and cybernetically experiment with zeroing - out dozens , century of preparation while sliding others upward and then testify , on a spreadsheet , how these simplification would pretend , say , one - hundred representative types of taxpayer .

Check out the rest of his fascinating proposal at the link . [ The Daily KosviaPopSci ]

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