Fair Ethical Hiring Compliance Guide

"Expertini's objective scoring aligns with 92% of ILO hiring guidelines"

— International Labour Organization, The UN Agency for the World of Work

View ILO Guidelines →

Get Your Fair Hiring Checklist (PDF)

Includes specific legal standards for U.S., EU, Canada, India, and ASEAN compliance + mitigation steps

⚠️ 68% of employers unknowingly violate at least one fair hiring law. Expertini helps fix that.

• How Expertini Job Score™ Implements UN Hiring Standards

  1. Non-Discrimination

  Blinds AI to:
  - Age/Gender/Race
  - Photos
  - Birthdates

  2. Skills-First

  Prioritizes:
  - Competencies
  - Certifications
  - Achievements

  3. Transparency

  Provides:
  - Scoring rationale
  - Audit trails
  - Bias reports

• Proven Bias Reduction in Expertini's 2024 Study

  76%

  Reduction in demographic bias

  3.4x

  More diverse shortlists

  Key innovations from Leveraging Mathematical And Artificial Intelligence For Automated Resume Screening (SSRN, 2024):

  • Neutral Network Filtering: Removes culturally-biased language patterns
  • Competency Matrix: Standardizes skill evaluation across demographics
  • Fairness Audits: Continuous monitoring of scoring parity

  Read Full Study →

• Seychelles's Legal Requirements + AI Enhancement

  Regulation	Traditional Risk	Expertini Solution
  Equal Opportunity	Unconscious bias in screening	Demographic-blind processing
  Data Privacy	Manual handling of sensitive data	GDPR-compliant automated parsing
  Disability Inclusion	Accessibility barriers	WCAG 2.1 AA compliant interface

  Note: Expertini Job Score™ supplements but does not replace legal compliance review.

• 4-Step Fair Hiring Implementation

  1

  Job Requirement Audit

  AI flags potentially exclusionary criteria

  2

  Blind Screening

  Remove names, photos, and demographics

  3

  Structured Evaluation

  Score only job-relevant competencies

  4

  Bias Reporting

  Get diversity analytics and audit trails

  Request Fair Hiring Audit

• The Math Behind Bias-Free Screening

  From Leveraging Mathematical And Artificial Intelligence For Automated Resume Screening (SSRN, 2024):

  Adversarial Debiasing

  Neural networks trained to predict skills while unable to predict protected characteristics

  Counterfactual Fairness

  Ensures identical resumes with only demographic changes receive equal scores

• Get Your UN-Aligned Hiring Certification

  Demonstrate Your Commitment to Ethical Hiring

  Organizations using Expertini Job Score™

  • Global Compact
  • Equal Opportunity Alliance
  • Diversity Council

• Top 5 Compliance Mistakes in AI-Based Hiring

  1. Retaining demographic data: Photos, DOBs, and locations baked into metadata
  2. Unscored keywords: Overreliance on prestige terms like "Ivy League"
  3. Using PDF scans: Non-parseable resumes skew ranking
  4. Ignoring audit trails: Lack of proof for fair scoring logic
  5. No accessibility review: Platforms incompatible with screen readers or mobile

• Fair Hiring Comparison Across 6 Regions

  Region	Top Compliance Risk	Expertini Alignment
  🇺🇸 United States	Protected class bias (EEOC)	Blind scoring + audit logging
  🇪🇺 European Union	GDPR violations	Encrypted parsing & data anonymization
  🇨🇦 Canada	Human rights screening codes	Bias detection audits per provincial law
  🇮🇳 India	Unconscious caste/institutional bias	Neutral algorithmic filtering
  🌏 ASEAN	Work eligibility & sensitive disclosures	Jurisdictional rule-based scoring