Source
AI screening transparency & control — found from sitemap — Greenhouse
Checked for Greenhouse on 1 Oct 2026
- Page
- https://www.greenhouse.com/ai-principles
- Checked
- 1 Oct 2026, 11:03 UTC
- How we may use it
- Public page, crawling permitted
Technical details
- type
- page
- http status
- 200
- content hash
- sha256:8cec60b52b48e7ecadbe801903ef2bffbe085fe3e709922f4125fc1704bd87cb
- permission
- robots_ok
- screenshot
- Screenshot on file (internal exhibit, not published)
Cited by
Facts read from this source
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Human decision ownership Report an error
“AI and automation can inform, summarize and surface insight, but it is never the final decision-maker.”
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Explainability Report an error
“Every AI output must be transparent, interpretable and grounded in observable signals.”
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No composite scores Report an error
“Greenhouse does not assign a single numerical score to rank candidates. Instead, we surface discrete categories (e.g., Strong, Good, Partial, Limited) with explanations rather than composite fit scores.”
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AI training data Report an error
“Greenhouse does not use personal data from customers to train internal LLMs, proprietary models or third-party models. Greenhouse AI proprietary models are trained only on anonymized, de-identified data such as job location, time-to-hire metrics and scheduling availability.”
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ISO certifications Report an error
“ISO 27001 covers information security management. ISO 27701 extends that to privacy. ISO 42001 is the AI-specific standard”
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AI ethics committee Report an error
“We have a cross-functional body including legal, privacy, security, product and engineering that evaluates every new AI capability before it ships.”
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Bias audits Report an error
“The AI-powered Talent Matching and AI Interviewer features in Greenhouse undergo independent monthly bias audits conducted by Warden AI, testing across ten protected classes.”
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AI opt out controls Report an error
“Customers can toggle any AI feature on or off at the org level via Configure > AI Tools. Enterprise customers can set features as opt-in by default.”
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Talent matching controls Report an error
“For Talent Matching specifically, candidates can request manual review, and customers can enable or disable the feature by office, department or job.”
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Structured hiring principle Report an error
“Structure is the governing system for how hiring decisions are made, giving AI the context to evaluate role-relevant signals instead of surface-level patterns.”
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Human review enforcement Report an error
“When applied correctly, AI reduces that burden, enforces deliberate human review and produces better decisions with greater focus.”