IdeaWell

Project ideas from Hacker News discussions.

Employers use your personal data to figure out the lowest salary you'll accept

Original Article

Hacker News Discussion

📝 Discussion Summary (Click to expand)

4 Dominant Themes in the Discussion

1. Employers Can Harvest Salary Data – Opting Out Is Burdensome

“We will be following up with a secure email to obtain the requested documents…Proof of Identity, Proof of Address, Identity Theft Report…” — putlake

The Work Number lets Equifax collect and sell personal compensation details. To opt out, users must submit a long list of identity and address proof, making the “opt‑out” feel like another data‑gathering step.

2. The Opt‑Out Process Is Invasive and Friction‑Heavy

“Obviously they have to be careful. What if they didn’t check all this and someone went and tried to opt out on your behalf? That would be an incredible invasion of your privacy!” — saghm

Participants see the required paperwork as an “incredible invasion of privacy” and suspect the system is designed to keep the data flowing rather than let people truly opt out.

3. Information Asymmetry Undermines Wage Negotiation

“In an environment where all of them have the information, this no longer is a problem…At a system level, this is a problem for employees.” — darth_avocado

When every employer can see a candidate’s full compensation history, workers lose bargaining leverage, which tends to depress wages across the board.

4. Widespread Concern Over Corporate Exploitation of Personal Data

“I love that it’s a freeze, not a purge. And that it’s opt‑out to have surreptitiously collected data being used against your livelihood.” — avaer

The sentiment that individuals should retain control over their personal data reflects a broader unease about companies like Equifax (and credit bureaus in general) monetizing sensitive information without meaningful consent.

🚀 Project Ideas

[Salary Freeze Shield]

Summary

  • Automates the tedious opt‑out process for The Work Number, reducing required documentation while preserving user privacy.
  • Eliminates the “KYC‑on‑steroids” friction that currently blocks many employees from freezing their salary data.

Details| Key | Value |

|-----|-------| | Target Audience | Employees who have been asked to provide excessive proof when trying to opt out of The Work Number | | Core Feature | One‑click opt‑out workflow that pre‑fills identity and address verification using secure government APIs, then submits the freeze request | | Tech Stack | Node.js backend, React front‑end, integration with Equifax Work Number API and IRS/State ID verification services | | Difficulty | Medium | | Monetization | Revenue-ready: Subscription (monthly $5) |

Notes- HN users repeatedly cited “disgusting” KYC hoops and the risk of data breaches when uploading documents—this directly solves those pain points.

  • Potential for viral adoption among workers concerned about privacy and future employment discrimination.

[Data Vault for Employment Verification]

Summary

  • Provides a decentralized, zero‑knowledge proof system that lets users prove they meet a salary threshold without revealing exact figures.
  • Addresses the information asymmetry that gives employers too much power over wage negotiations.

Details

Key Value
Target Audience Job seekers and freelancers who want to negotiate offers while keeping income private
Core Feature Generates cryptographic proofs of income using selective disclosure of encrypted pay stubs; verifiers can check eligibility without seeing raw data
Tech Stack Solidity smart contracts (Ethereum L2), zk‑SNARK libraries, IPFS for storage, ethers.js front‑end
Difficulty High
Monetization Revenue-ready: Transaction fee (0.1% per proof)

Notes

  • Commenters like “OptionOfT” complained about having to give “even more information” to opt out—this flips the script by requiring less data.
  • Could be a game‑changer for discussions about GDPR‑style data rights and wage transparency.

[Transparent Salary Band Marketplace]

Summary

  • A public job board where every posting includes a salary range and historic pay data for similar roles, empowering candidates to evaluate offers upfront.
  • Tackles the lack of salary transparency that fuels wage gaps and poor negotiation leverage.

Details

Key Value
Target Audience Job seekers, recruiters, and small‑to‑medium enterprises looking to attract talent with clear compensation
Core Feature Searchable database of salary bands indexed by role, location, and experience; includes crowdsourced pay surveys
Tech Stack Python/Django backend, React UI, PostgreSQL, Elasticsearch for fast filtering
Difficulty Low
Monetization Revenue-ready: Freemium (free basic listings, $15 per premium featured posting)

Notes

  • Directly references “roenxi” and “darth_avocado” concerns about information asymmetry and market fairness.
  • HN users often advocate for publishing salary ranges—this implements that demand in a usable product.

[Privacy‑First Income Proof API]

Summary

  • An API that issues verifiable, cryptographically signed income tokens that can be presented to lenders, landlords, or employers without exposing the underlying salary details.
  • Mitigates the risk of data leaks and breaches associated with centralized salary repositories.

Details

Key Value
Target Audience FinTech platforms, landlords, and verification services that currently request full pay stubs
Core Feature Zero‑knowledge income verification: users upload encrypted pay stubs; the API returns a signed proof of “income >= X”
Tech Stack Go microservice, Kubernetes, Rust-based ZK proofs, AWS KMS for key management
Difficulty High
Monetization Revenue-ready: API usage credits ($0.001 per verification)

Notes

  • Aligns with “lateforwork” note that The Work Number is “in fact Equifax” and is used for myriad verification tasks—this replaces that centralized source.
  • HN discussions about data breaches (e.g., “mailing passport scans”) highlight the need for a safer verification mechanism.

[AI Salary Negotiation Companion]

Summary

  • A browser extension and web app that aggregates public salary data, job market trends, and employer‑specific offers to suggest optimal negotiation strategies.
  • Empowers employees to counter lowball tactics and reduces the power imbalance described by many commenters.

Details

Key Value
Target Audience Professionals preparing for job offers, freelancers, and contract workers negotiating compensation
Core Feature Real‑time offer analysis, AI‑driven salary recommendation, risk‑assessment alerts for invasive data collection
Tech Stack Vue.js front‑end, Python LLM backend (OpenAI compatible), PostgreSQL for historical salary data
Difficulty Medium
Monetization Revenue-ready: Subscription (annual $12)

Notes

  • Mirrors concerns raised by “darth_avocado” about employers having “all the bargaining power” when they know your exact salary.
  • Users like “lateforwork” and “roenxi” repeatedly emphasized that asymmetric information hurts workers—this tool directly restores balance.

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