The IRS Can Use Artificial Intelligence To Catch Wealthy Tax Cheats

The use of technology might make it more competitive between pricey tax lawyers and revenue collectors.

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President Joe Biden plans to introduce a number of new tax increases on Those with high incomes in his most recent budget proposal. Maybe he should just concentrate on collecting what a few of them already owe rather than boosting taxes.

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The IRS receives $600 billion less in revenue year than it ought to. According to one estimate, persons who are extremely wealthy and conceal their income by creating complex partnerships or other companies are responsible for half of that underreporting. Those figures ought to catch your attention if you're concerned about the size of the US debt.

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Simply put, the IRS lacks the resources to find them. The IRS has mostly targeted impoverished families with audits as a result of years of budget cuts and understaffing since doing so is simpler and less expensive than investigating the intricate tax issues of rich filers. Yet, the use of artificial intelligence might tip the scales in favor of the outmoded, troubled agency, enabling it to better pursue the actual money.

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The IRS will receive roughly $80 billion from the Inflation Reduction Act during the following ten years. When Daniel Werfel, the nominee for IRS commissioner, is confirmed, one of his first tasks should be allocating some cash to use AI to help restructure the entire audit process.

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Take partnerships as an example, where the average tax rate is only 16% and audit rates have fallen to 0.05%. A recent article by economists at Stanford University found that 15% of partnerships are complex, meaning they may have overlapping members and pile LLC atop LLC upon LLC (the top federal income tax rate is 37%).

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The IRS is making some attempts, but it is still exceedingly challenging to assess whether or not those intricate partnerships are reporting the correct amount of income. Also, a large number of the agency specialists in this field have either retired or are about to do so.

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But, after analyzing more than 7 million partnership companies between 2013 and 2015, the researchers discovered that machine learning was effective in predicting whether businesses were noncompliant, or didn't pay all of their tax liabilities. According to this study, AI has the potential to more quickly and effectively remove the layers, identifying relationships that aren't compliant so that human agents may investigate further.

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The IRS is rather secretive about any artificial intelligence (AI) or machine learning it is currently employing in the enforcement arena, but on a webcast in 2018, the agency disclosed that technology was aiding it in quickly identifying specific noncompliance. It used to take weeks or months for people.

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Sincere taxpayers should be happy about this possibility. So many compliant payers are currently subjected to pointless audits. Stopping the government from wasting time on this arduous process when it is not required would be in the best interests of the taxpayers. AI could identify patterns and direct auditors to profitable audits.

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But, there are certain restrictions. We're not moving toward a time when robots in green visors control the IRS. AI cannot replace IRS examiners; it can only improve their capabilities. Humans still need to be the teachers and graders, according to Janet Holtzblatt, a senior researcher at the Urban-Brookings Tax Policy Center.

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A good illustration of how relying only on AI can result in new issues is provided by the Netherlands. In order to ensure that child care subsidies were flowing to the right people, the Dutch tax authorities began employing a self-learning machine algorithm in 2013. Innocent families were forced to return their credits without the ability to contest the algorithm's racial bias. (In response to the controversy, the prime minister and his whole cabinet resigned in 2021.)

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According to recent studies conducted in the US, the IRS's existing algorithms may possibly be biased. Black taxpayers are much more likely to be inspected than other taxpayers, according to a recent working paper. The most extreme example is the earned income tax credit claimant who is a single Black man with dependents who is over 20 times more likely to be audited than a non-Black claimant who is divorced and filing jointly. Yikes.

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This does not, however, imply that we should stop up on employing technology to enhance tax compliance. There's this anxiety about computer vision, but it can also result in the identification of disparities in incumbent legacy systems, said Daniel E. Ho, an economist at Stanford who worked on both this paper and the one on complex partnerships. Basically, the deep learning helped to reveal the inequity and now it's up to the humans to fix it.

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If AI is used correctly and under competent supervision, it might significantly improve the fairness, precision, and profitability of the IRS audits for the US government. Nothing about that is Orwellian. It's advancement.