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EO eliminates disparate impact: Restoring Equality of Opportunity & Meritocracy

pmags 2y ago
If you're trying to understand the context of this and other EOs, see here: https://www.nytimes.com/2025/04/23/us/politics/trump-executive-order-university-accreditors.html?smid=url-share https://www.nytimes.com/2025/04/23/us/politics/trump-executi...
- rahimnathwani 2y ago
  That article is pretty one-sided: Another restricts the use of the so-called disparate impact rule, which civil rights groups have long said is an important tool for showing discrimination against minorities. If your whole raison d'etre is to 'show discrimination' then obviously you may like a rule that allows you to 'show discrimination' even where none exists.
rahimnathwani 2y ago
'Disparate impact' is the idea that, to assess fairness, you treat individuals not as individuals, but as members of identity groups (e.g., grouped by ethnicity, sex, sexual orientation). Then, if any group doesn't get a proportion of some desirable outcome (e.g., employment at a particular company) matching its proportion in the relevant population, this is presumed to be illegal discrimination. The burden of proof then falls on the decision-maker (e.g. employer), i.e. guilty until proven innocent. This seems crazy when you consider processes with any randomness. There's no reason why every single company, for every role, would naturally have demographic proportions matching the relevant population for every single identity group. If you toss a coin ten times and get 6 heads and 4 tails, that doesn't mean the coin is biased. The EO is right: disparate impact doctrine has forced employers to discriminate based on race, so they can maintain proportions.
- nivrayreteP 2y ago
  I don’t think the example you applied is applicable, you’re using the randomness of a coin flip to a deterministic issue, biasses. Why would it be an issue if 10 homes were sold to a specific identity group and to give preference of the 11th home to a different identity group? I don’t understand why there’s an aversion to promote a heterogenous effect.
  - deleted 2y ago
    [deleted]
  - rahimnathwani 2y ago
    It's an issue because people are individuals and we should treat them fairly as individuals, not discriminate based on the colour of their skin or other irrelevant attributes, including membership in identity groups. Should each NBA team be required to make sure the next player they hire has what you call a 'heterogenous effect' on the team composition with respect to identity groups?
- techpineapple 2y ago
  Ok, great, we want equality of opportunity. How do we measure that? Disparate impact seems like a guide, if an imperfect one, but if you can prove to me that everyone has equal opportunity, I’ll accept that, except I think “equal opportunity” is often just shorthand for “we’ll do nothing”. Do I have an equal opportunity to the guy who’s dad’s name is on one of the buildings?
  - rahimnathwani 2y ago
    Disparate impact is flawed: - It imposes liability for neutral policies based solely on statistical outcomes, ignoring discriminatory motive. Example: Griggs v. Duke Power invalidated a diploma requirement due to impact alone. - It prioritizes group statistical parity over individual qualifications, potentially invalidating useful criteria. Again: Griggs invalidated tests because of their statistical impact. - It incentivizes racial quotas: fear of liability drives companies (and college admissions offices) toward managing numbers by race, undermining the principle of equal treatment. Example: New Haven (Ricci) discarded firefighter exam results specifically to manage racial outcomes. - Trying to avoid disparate impact liability can itself constitute intentional discrimination against another group. (Ricci paradox, same case as above.) - It enables lawsuits against essential, neutral practices based purely on statistical correlations. Example: Challenges to voter ID laws based on disparate ID possession rates. Challenges to 'rat control' regulations based on disparate impact on rents. - The "business necessity" defense is often hard to prove and subject to judicial second-guessing. Example: Duke Power failed to prove its hiring requirements were essential. - It conflicts with the Equal Protection Clause's requirement of discriminatory intent for government liability. - It creates the potential to challenge almost any neutral policy with unequal outcomes. Example: suspensions and other school discipline must be meted out 'fairly' between different races.

If you're trying to understand the context of this and other EOs, see here: https://www.nytimes.com/2025/04/23/us/politics/trump-executive-order-university-accreditors.html?smid=url-share https://www.nytimes.com/2025/04/23/us/politics/trump-executi...

rahimnathwani 2y ago
That article is pretty one-sided: Another restricts the use of the so-called disparate impact rule, which civil rights groups have long said is an important tool for showing discrimination against minorities. If your whole raison d'etre is to 'show discrimination' then obviously you may like a rule that allows you to 'show discrimination' even where none exists.

rahimnathwani 2y ago

'Disparate impact' is the idea that, to assess fairness, you treat individuals not as individuals, but as members of identity groups (e.g., grouped by ethnicity, sex, sexual orientation). Then, if any group doesn't get a proportion of some desirable outcome (e.g., employment at a particular company) matching its proportion in the relevant population, this is presumed to be illegal discrimination. The burden of proof then falls on the decision-maker (e.g. employer), i.e. guilty until proven innocent. This seems crazy when you consider processes with any randomness. There's no reason why every single company, for every role, would naturally have demographic proportions matching the relevant population for every single identity group. If you toss a coin ten times and get 6 heads and 4 tails, that doesn't mean the coin is biased. The EO is right: disparate impact doctrine has forced employers to discriminate based on race, so they can maintain proportions.

nivrayreteP 2y ago
I don’t think the example you applied is applicable, you’re using the randomness of a coin flip to a deterministic issue, biasses. Why would it be an issue if 10 homes were sold to a specific identity group and to give preference of the 11th home to a different identity group? I don’t understand why there’s an aversion to promote a heterogenous effect.
- deleted 2y ago
  [deleted]
- rahimnathwani 2y ago
  It's an issue because people are individuals and we should treat them fairly as individuals, not discriminate based on the colour of their skin or other irrelevant attributes, including membership in identity groups. Should each NBA team be required to make sure the next player they hire has what you call a 'heterogenous effect' on the team composition with respect to identity groups?
techpineapple 2y ago
Ok, great, we want equality of opportunity. How do we measure that? Disparate impact seems like a guide, if an imperfect one, but if you can prove to me that everyone has equal opportunity, I’ll accept that, except I think “equal opportunity” is often just shorthand for “we’ll do nothing”. Do I have an equal opportunity to the guy who’s dad’s name is on one of the buildings?
- rahimnathwani 2y ago
  Disparate impact is flawed: - It imposes liability for neutral policies based solely on statistical outcomes, ignoring discriminatory motive. Example: Griggs v. Duke Power invalidated a diploma requirement due to impact alone. - It prioritizes group statistical parity over individual qualifications, potentially invalidating useful criteria. Again: Griggs invalidated tests because of their statistical impact. - It incentivizes racial quotas: fear of liability drives companies (and college admissions offices) toward managing numbers by race, undermining the principle of equal treatment. Example: New Haven (Ricci) discarded firefighter exam results specifically to manage racial outcomes. - Trying to avoid disparate impact liability can itself constitute intentional discrimination against another group. (Ricci paradox, same case as above.) - It enables lawsuits against essential, neutral practices based purely on statistical correlations. Example: Challenges to voter ID laws based on disparate ID possession rates. Challenges to 'rat control' regulations based on disparate impact on rents. - The "business necessity" defense is often hard to prove and subject to judicial second-guessing. Example: Duke Power failed to prove its hiring requirements were essential. - It conflicts with the Equal Protection Clause's requirement of discriminatory intent for government liability. - It creates the potential to challenge almost any neutral policy with unequal outcomes. Example: suspensions and other school discipline must be meted out 'fairly' between different races.