Organizations want more decision-useful evidence, while individuals want meaningful control over how employment-related data is collected, interpreted, shared, corrected, and reused.

Employers report difficulty finding and retaining qualified people, creating demand for stronger signals. Workers and applicants are wary of automated high-stakes decisions, surveillance, opaque scores, and secondary use. Trust depends on purpose, proportionality, transparency, access, correction, appeal, human review, and deletion—not on collecting the most data possible.

Contents (6 sections)

Evidence snapshot

Supported by cited sources
FindingScope or qualification
Roughly half of small employer firms reported hiring or retaining qualified staff as an operational challenge.Large weighted nonprobability survey; qualified is employer-defined.
71% of U.S. adults opposed AI making final hiring decisions and 66% would not want to apply to an employer using AI.Pew probability survey; attitudes are not observed adoption behavior.
47% thought AI could treat applicants more consistently, versus 15% who thought it would be worse.Concern is conditional, not simple anti-technology sentiment.
81% were concerned about company data use and 73% felt little or no control in a separate Pew survey.Broad consumer-data context.

What the evidence does not prove

Supported by cited sources

Hiring difficulty does not prove a data shortage; more data can create false confidence. Worker control must coexist with legitimate organizational records, and privacy, evidence, employment, and discrimination rules differ by use.

Why different stakeholders can care

Proposed

Employers gain trustworthy evidence; workers gain agency and due process; regulators gain auditable practices; and the public gains innovation without invisible high-stakes scoring.

Question to investigate

Open question

What The Solar Guild must test

Research question

Can contributors understand and control the evidence lifecycle while reviewers still find the record useful—and does funding influence judgment?

Core sources

Supported by cited sources
Federal Reserve — 2024 Employer FirmsPew — AI in HiringPew — Data Privacy RisksEEOC/DOJ — Algorithmic Tools

References and limits

This page is published by The Solar Guild. Sources are listed so readers can inspect the basis of the page. A project statement is not independent proof unless the page identifies supporting outside evidence.

  • Problem 17 in The Solar Guild — Twenty Problems Worth Testing v1.0
  • Direct source links are provided above; quantitative claims retain their stated scope and qualification
  • The Solar Guild's response is explicitly separated from evidence that the problem exists