Mid-Market ATS

How to Audit AI Bias in Greenhouse

Greenhouse is a popular ATS for mid-market and growth-stage companies. Its structured hiring approach and AI-assisted candidate scoring need bias auditing to ensure fair outcomes across all demographics.

Bias Risks in Greenhouse

  • Scorecard aggregation algorithms may amplify individual interviewer biases
  • Auto-reject rules based on keyword matching can discriminate against diverse candidates
  • Candidate ranking models trained on historical hire data may perpetuate past biases
  • Automated sourcing recommendations that skew toward homogeneous candidate pools

Step-by-Step Audit Guide

  1. 1Export candidate data from Greenhouse via Harvest API or manual CSV export
  2. 2Include all pipeline stages from application to offer
  3. 3Map EEOC demographic categories to candidate records
  4. 4Run adverse impact analysis across each hiring stage
  5. 5Review AI-assisted scorecard patterns for demographic disparities
  6. 6Document findings and create remediation plan

Data Export Instructions

  1. 1.Go to Greenhouse > Reports > Export to CSV
  2. 2.Select "Candidate Pipeline" report with demographics enabled
  3. 3.Ensure all pipeline stages are included
  4. 4.Upload exported file to OnHirely

Compliance Notes

  • Greenhouse does not perform bias audits on your behalf — you need an independent auditor
  • Companies using Greenhouse in NYC must comply with LL144 regardless of ATS provider
  • Greenhouse EEOC data collection must be enabled to support audit

Related Regulations

Nyc Local Law 144Eeoc Guidelines

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Audit Your Greenhouse Hiring Pipeline

Upload your Greenhouse candidate data and get a comprehensive bias audit report in minutes.

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