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naraburns  nihil supernum  1yr ago (text post)   34509 thread views

Culture War Roundup for the week of January 30, 2023

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New Frontiers in Algorithmic Racism - Tax Edition

The New York Times has an article out on the IRS algorithmically targeting black Americans at higher rates than other racial groups. The claim is that there's something in the algorithm that inappropriately biases it against black Americans. Summarized in the opening paragraphs:

Black taxpayers are at least three times as likely to be audited by the Internal Revenue Service as other taxpayers, even after accounting for the differences in the types of returns each group is most likely to file, a team of economists has concluded in one of the most detailed studies yet on race and the nation’s tax system.

The findings do not suggest bias from individual tax enforcement agents, who do not know the race of the people they are auditing. They also do not suggest any valid reason for the I.R.S. to target Black Americans at such high rates; there is no evidence that group engages in more tax evasion than others.

OK, so what exactly is causing them to get audited more if it's not individual bias, the machines are blinded to the race of the individual, and the rules are the same for everyone? Apparently some of it comes down to targeting EITC filings:

Black Americans are disproportionately concentrated in low-wage jobs. They are more likely than whites to claim the E.I.T.C. The authors wondered if that prevalence in claiming the credit might explain why Black taxpayers face more audits, because I.R.S. data show the agency audits people who claim the E.I.T.C. at higher rates than other taxpayers.

But as the research progressed, the authors found the share of Black Americans claiming the E.I.T.C. only explained a small part of the audit differences. Instead, more than three-quarters of the disparity stems from how much more often Black taxpayers who claim the credit are audited, compared with E.I.T.C. claimants who are not Black.

Unless I'm missing something, the article does not explicitly state what the relevant factors are that result in this targeting are. In what I see as typical NYT style, it does leave a breadcrumb that might be suggestive if you're ignoring the narrative quotes embedded in the article:

Black taxpayers appear to disproportionately file returns with the sort of potential errors that are easy for I.R.S. systems to identify, like underreporting certain income or claiming tax credits that the taxpayer does not qualify for, the authors find.

To me, this reads like the most likely explanation for black taxpayers being audited more frequently is that they report their income incorrectly in easy-to-detect ways. Since the IRS already has W-2 data for filers, it's probably not very hard for them to notice when someone reports their income wrong. There isn't really any elaboration that I find after this, so I'm unclear on how much this accounts for auditing disparities. The implication of the article and the quotes from "equity" advocates imply to me that we should figure out a way to make sure that white Americans are audited at least as much as black Americans, regardless of who is misreporting their income more frequently.

As cynical as it sounds, I'm beginning to hear the term "algorithmic bias" as nothing more than a form of projection - algorithm systems frequently detect something real about the world, people with racially motivated politics don't like that outcome, and they seek to shift the algorithm towards a bias in favor of their preferred group. If a program that is optimized for detecting incorrect tax filings works as intended to detect them, but turns up more black Americans than white Americans, the suggestion appears to be to change the weighting until it evens out the races, regardless of the impact on the efficiency of detecting lost revenue. The "algorithmic bias", from my reading of this would be injecting a deliberate racial preference to counter the program noticing actual disparities. I am reminded of the racial resentment scale, in which people who say that "blacks have gotten less than they deserve" are not racially resentful, while those who think things like "Irish, Italian, and Jewish ethnicities overcame prejudice and worked their way up, Blacks should do the same without any special favors" are racially resentful.

Anyway, I'll be curious to see if the study is released more publicly and details what exactly is causing the disparity.

As cynical as it sounds, I'm beginning to hear the term "algorithmic bias" as nothing more than a form of projection - algorithm systems frequently detect something real about the world, people with racially motivated politics don't like that outcome, and they seek to shift the algorithm towards a bias in favor of their preferred group.

I suppose "always was" is a glib response so I'll say:

This tendency is widespread and isn't even specific to algorithms: leftists always first insist that society did a wrong via its social engineering to then demand social engineering to ostensibly "correct" this.

You see this all the time with nebulous complaints about how "the media" brainwashed people into not liking everything from fat people to Africa to the WNBA and therefore have a responsibility to fix it despite very little evidence being adduced for this (and people ignoring more obvious explanations for why these things are low status)

It's just part of a fundamental, distorted Rousseauianism that has swallowed the Left: any inconvenient situation must be blamed on some sort of malignant social programming and, not just that, on the usual villains: white supremacy, Western sexism,etc. (as if minorities can't "program" themselves with awful beliefs).

This tendency is widespread and isn't even specific to algorithms: leftists always first insist that society did a wrong via its social engineering to then demand social engineering to ostensibly "correct" this.

If too many whites or "X" get ahead, the system is broken. Otherwise, the meritocracy is working (like in sports, Hollywood, etc. ) but not in STEM (in which Asians, Whites are overrepresented).

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