Google to pay $28M to settle claims it favoured white and Asian employees

Original Article ↗ Hacker News Discussion ↗

Settlement Scale and Per-Employee Impact

  • Many note the payout (~$4.2k per person before legal fees for ~6,600 people) is small relative to Google’s resources and to the alleged career damage.
  • Some see this as “nuisance value” that doesn’t meaningfully compensate harmed employees; others say not getting into or promoted at Google doesn’t necessarily “screw” a career.

Shakedown vs Genuine Misconduct

  • One camp views this as a drive-by class-action shakedown: plaintiffs’ firms exploit low litigation costs vs high settlement pressure on deep-pocketed employers.
  • Others push back: Google has a track record of serious HR-related settlements (e.g., anti‑poaching, high-profile executives), so discriminatory behavior by managers is plausible and not far-fetched.
  • There is debate over “disparate impact” law: some argue companies can be liable for outcomes that only look discriminatory; others point out employers can defend policies as “business necessity” and that such cases are not trivial to win.

Contradictory Discrimination Cases

  • Commenters note Google previously settled a federal case alleging discrimination against Asians; now it settles a case saying Asians and whites were favored.
  • Several argue both can be true at Google scale: different orgs and managers can have opposite biases, and the company tends to settle rather than litigate ideology.

DEI Programs, ERGs, and Perceptions of Fairness

  • Some ex-employees describe DEI culture and ERGs as “eye-for-an-eye,” claiming nonwhite employees got special mentoring and opportunities while white employees were implicitly excluded.
  • Others respond that ERGs exist to support underrepresented or non-dominant groups, that Google has general mentorship open to all, and that assuming nonwhite colleagues are promoted only via preference is itself biased.
  • Debate arises over whether there should be a “white ERG”: one side says all groups should be allowed; the other says majority-culture groups already benefit from default, self-reinforcing networks and would send a different (often threatening) signal.
  • Side discussion on labels like “Latinx”: some say it’s artificial and unwanted by most Latinos; others argue language is fluid and outsiders shouldn’t police usage.

Class Definition and Exclusion of Black Employees

  • Several ask why Black employees were excluded from the class.
  • Answers from the thread:
    • Google argued the initial class (all nonwhite employees) was too broad and that some evidence showed Black employees might be worse off than the rest, giving them distinct or even conflicting interests.
    • There is a separate federal case said to cover Black employees.
    • The final class is narrowly defined to specific Hispanic/Latino/Indigenous/Native categories and explicitly excludes anyone also identifying as Black.
  • Clarification: because this was a settlement, the court did not “agree with” either side on the merits; it just approved the deal.

Statistics, Performance, and Bias

  • Some speculate that whites and Asians may simply perform better on average and that any underpayment claims ignore that. Others highlight this as an unfounded and racist assumption.
  • Several point out statistical pitfalls: applicant pools may not be representative; performance metrics can be biased; and group averages can’t justify decisions about individuals (ecological fallacy).
  • One commenter notes the complaint allegedly claims bias even after controlling for performance ratings, but another questions the objectivity of those ratings given internal culture.

Litigation Dynamics and Corporate Role

  • A few describe how it’s relatively easy and often profitable to bring discrimination claims in the US, leading many employers to settle small cases rather than fight, even when allegations are weak.
  • Others note lawsuits are public record and can stigmatize plaintiffs, and that if “easy money” were really so widespread, far more companies in California would be facing constant payouts.
  • Broader reflection: large tech firms are functionally treated more like public institutions—subject to heavy scrutiny on fairness—compared to small businesses, which rarely face this level of enforcement or expectation.