Ask HN: Why is Pave legal?

Hacker News Discussion ↗

What Pave Is and How It Fits Existing Practices

  • Pave aggregates detailed compensation data (salary, stock, history, sometimes tied to performance) from employers to provide benchmarking and pay bands.
  • Many commenters note this is not new: similar services (Radford, Korn Ferry, ADP, Experian, Carta, VC-run salary surveys) have existed for decades.
  • Some see Pave as a “tech-first” or more granular version of traditional comp surveys.

Is It Wage Fixing or Just Benchmarking?

  • One camp: sharing compensation data among competitors with intent/effect of keeping wages low is classic antitrust territory; algorithmic “stochastic” coordination can still be wage fixing.
  • Other camp: wage fixing requires an agreement to set wages; merely providing historical/aggregate data and no binding recommendations is generally legal and common practice.
  • Disagreement over where the line is: backward-looking “info only” vs forward-looking coordinated pricing.

Comparisons to RealPage (Rent Pricing Case)

  • Strong parallels drawn to RealPage’s rent-pricing software, which the DOJ alleges enabled landlord collusion.
  • Key differences highlighted:
    • RealPage computed specific rent recommendations and contractually pressured clients to follow them.
    • Pave, as described, provides benchmarks but no binding offers and no explicit “don’t compete” mechanism.
  • Others argue the core harm—centralized, non-public data used to reduce competition—is similar.

Effects on Wages and Market Dynamics

  • Some founders and employees report Pave data made them raise salaries they’d been underpaying.
  • Others argue the primary realistic use is to justify “50th percentile” or “45th percentile” targeting and drive wages down or hold them flat.
  • Point that high-skill / in-demand roles may see wage increases while low-skill roles see suppression.

Information Asymmetry & Employee Power

  • Major concern: only employers get fine-grained, up-to-date data; employees rely on coarse tools (Glassdoor, levels.fyi) and occasional public ranges.
  • This deepens negotiation imbalance, especially when combined with internal pay bands and performance matrices employees can’t fully see.
  • Some call for fully open salary data or public tax/comp records to level the field.

Data Sources, Privacy, and Equifax/The Work Number

  • Large subthread on Equifax’s “The Work Number” and payroll providers selling per-paycheck data.
  • Many were unaware employers or payroll vendors report detailed pay history; some froze their files and describe downsides (loan/mortgage friction).
  • Claims that nearly all major payroll vendors sell this data; opting out is difficult or impossible at the employer level.
  • Fears that detailed comp data leaks, breaches, and third-party access create serious privacy and even physical security risks.

Legal Context and Jurisdiction Differences

  • References to US antitrust guidance: sharing “competitively sensitive variables” can be illegal if it enables coordinated behavior; safe-harbor “info sharing” has been narrowed.
  • Mention of class actions over comp surveys in other industries, some settled.
  • Several commenters say similar benchmarking is widespread in EU/UK; others argue GDPR could make person-level sharing illegal, but aggregate/band data is generally allowed.
  • Some expect Pave (and similar tools) to face litigation once market penetration is high enough or regulators focus on labor markets like they did on rents.

Ethical Views and Calls for Regulation

  • Many see Pave-style tools as inherently unethical: codifying employer collusion and exploiting workers’ lack of information.
  • Others frame them as neutral infrastructure that can increase fairness and consistency if combined with transparency to employees.
  • Repeated calls for:
    • Stronger regulation of employment data brokers and payroll data resale.
    • Explicit bans or clearer rules on algorithmic wage/price coordination.
    • Legal reinforcement of employees’ right to share pay and broader salary transparency.

Miscellaneous Themes

  • Analogies to Uber/Airbnb: “do the illegal thing at scale, let lawyers sort it out later,” sometimes successful, sometimes not.
  • Examples from public-sector and Nordic countries where salaries or tax data are public, cited as an alternative model.
  • Side discussion about HN’s moderation of YC-related threads; explanation that automated “flamewar” filters, not YC bias, affected visibility.