Computer Scientists Wield Artificial Intelligence to Battle Tax Evasion by Lynnley Browning.
From the post:
When federal authorities want to ferret out abusive tax shelters, they send an army of forensic accountants, auditors and lawyers to burrow into suspicious tax returns.
Analyzing mountains of filings and tracing money flows through far-flung subsidiaries is notoriously difficult; even if the Internal Revenue Service manages to unravel a major scheme, it typically does so only years after its emergence, by which point a fresh dodge has often already replaced it.
But what if that needle-in-a-haystack quest could be done routinely, and quickly, by a computer? Could the federal tax laws — 74,608 pages of legal gray areas and welters of credits, deductions and exemptions — be accurately rendered in an algorithm?
“We see the tax code as a calculator,” said Jacob Rosen, a researcher at the Massachusetts Institute of Technology who focuses on the abstract representation of financial transactions and artificial intelligence techniques. “There are lots of extraordinarily smart people who take individual parts of the tax code and recombine them in complex transactions to construct something not intended by the law.”
A recent paper by Mr. Rosen and four other computer scientists — two others from M.I.T. and two at the Mitre Corporation, a nonprofit technology research and development organization — demonstrated how an algorithm could detect a certain type of known tax shelter used by partnerships.
I had to chuckle when I read:
“There are lots of extraordinarily smart people who take individual parts of the tax code and recombine them in complex transactions to construct something not intended by the law.”
It would be more accurate to say: “…something not intended by the tax policy wonks at the IRS.”
Or at Justice Sutherland said in Gregory v. Helvering (1934):
The legal right of a taxpayer to decrease the amount of what otherwise would be his taxes, or altogether to avoid them, by means which the law permits, cannot be doubted.
Gregory v. Helvering isn’t much comfort because Sutherland also found against the taxpayer in that case on a “not intended by the law” basis.
Still, if you read the paper you will realize taxpayers are still well ahead vis-a-vis any AI:
Drawbacks are that currently SCOTE has a very simplified view of transactions, audit points and law.
Should we revisit the Turing test?
Perhaps a series of tax code tests, 1040A, 1040 long form, corporate reorganization, each one more complex than the one before.
Pitch the latest AIs against tax professionals?