- 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.
- 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.