Example 1: Pay Equity Analysis
Input:
{
"request_type": "pay_equity_analysis",
"analysis_date": "2024-04-01",
"company": {
"name": "TechCorp Inc",
"industry": "technology",
"employee_count": 2500,
"locations": ["CA", "NY", "TX", "WA"]
},
"employee_data": [
{
"job_category": "software_engineer",
"level": "senior",
"demographics": {
"gender": "male",
"race_ethnicity": "white",
"count": 85,
"avg_salary": 142000,
"avg_bonus": 15000
}
},
{
"job_category": "software_engineer",
"level": "senior",
"demographics": {
"gender": "female",
"race_ethnicity": "white",
"count": 32,
"avg_salary": 138500,
"avg_bonus": 13800
}
},
{
"job_category": "software_engineer",
"level": "senior",
"demographics": {
"gender": "male",
"race_ethnicity": "asian",
"count": 45,
"avg_salary": 144200,
"avg_bonus": 16200
}
}
],
"analysis_scope": ["base_salary", "total_compensation", "promotion_rates"]
}
Output:
{
"analysis_id": "PAY-EQUITY-2024-Q2-001",
"executive_summary": {
"overall_equity_score": 73,
"risk_level": "MODERATE",
"significant_disparities_found": 3,
"recommended_adjustments": 1250000
},
"detailed_analysis": {
"gender_pay_gaps": [
{
"job_category": "software_engineer_senior",
"male_avg_total_comp": 157000,
"female_avg_total_comp": 152300,
"raw_gap": 4700,
"adjusted_gap": 2800,
"statistical_significance": true,
"sample_size_adequate": true
}
],
"race_ethnicity_gaps": [
{
"job_category": "software_engineer_senior",
"white_avg": 157000,
"asian_avg": 160400,
"hispanic_avg": 151200,
"black_avg": 148900,
"significant_disparities": ["hispanic", "black"]
}
]
},
"regression_analysis": {
"model_r_squared": 0.78,
"significant_predictors": [
"years_experience",
"performance_rating",
"education_level",
"location"
],
"unexplained_variance": {
"gender": 1.8,
"race_ethnicity": 2.3,
"concern_level": "MODERATE"
}
},
"recommendations": [
{
"priority": "HIGH",
"category": "immediate_adjustment",
"description": "Adjust salaries for 28 female senior engineers",
"cost": 156000,
"timeline": "within_60_days"
},
{
"priority": "MEDIUM",
"category": "process_improvement",
"description": "Implement structured salary bands",
"timeline": "within_6_months"
},
{
"priority": "LOW",
"category": "monitoring",
"description": "Quarterly pay equity reviews",
"timeline": "ongoing"
}
],
"compliance_status": {
"eeoc_guidelines": "REQUIRES_ATTENTION",
"ofccp_requirements": "NON_COMPLIANT",
"state_regulations": "VARIES_BY_LOCATION",
"litigation_risk": "MODERATE"
}
}
Example 2: Hiring Process Bias Detection
Input:
{
"request_type": "hiring_bias_analysis",
"analysis_period": {
"start_date": "2024-01-01",
"end_date": "2024-03-31"
},
"position_type": "marketing_manager",
"hiring_data": {
"total_applicants": 450,
"applicant_demographics": {
"gender": {"male": 198, "female": 245, "non_binary": 7},
"race_ethnicity": {
"white": 180,
"black": 85,
"hispanic": 95,
"asian": 75,
"other": 15
}
},
"interview_stage": {
"phone_screen_invited": 120,
"phone_screen_demographics": {
"male": 65, "female": 52, "non_binary": 3,
"white": 72, "black": 15, "hispanic": 18, "asian": 12, "other": 3
}
},
"final_hires": {
"total": 8,
"demographics": {
"male": 6, "female": 2, "non_binary": 0,
"white": 7, "black": 0, "hispanic": 1, "asian": 0, "other": 0
}
}
}
}
Output:
{
"analysis_id": "HIRING-BIAS-2024-Q1-001",
"adverse_impact_analysis": {
"four_fifths_rule_violations": [
{
"stage": "phone_screen_selection",
"protected_class": "black_applicants",
"selection_rate": 17.6,
"highest_rate": 40.0,
"ratio": 0.44,
"four_fifths_threshold": 0.80,
"violation": true,
"severity": "SIGNIFICANT"
},
{
"stage": "final_hiring",
"protected_class": "female_applicants",
"selection_rate": 0.8,
"highest_rate": 3.0,
"ratio": 0.27,
"violation": true,
"severity": "SEVERE"
}
]
},
"statistical_significance": {
"chi_square_tests": [
{
"stage": "phone_screen",
"chi_square": 15.2,
"p_value": 0.004,
"significant": true
},
{
"stage": "final_hiring",
"chi_square": 8.7,
"p_value": 0.034,
"significant": true
}
]
},
"risk_assessment": {
"eeoc_complaint_risk": "HIGH",
"class_action_risk": "MODERATE",
"financial_exposure": {
"estimated_damages": 150000,
"legal_fees": 75000,
"remediation_costs": 50000
}
},
"root_cause_analysis": [
{
"issue": "unconscious_bias_in_resume_screening",
"evidence": "Disproportionate rejection of candidates with non-European names",
"recommendation": "Implement blind resume review process"
},
{
"issue": "interview_panel_composition",
"evidence": "All-male interview panels for 75% of candidates",
"recommendation": "Ensure diverse interview panel representation"
}
],
"corrective_actions": [
{
"priority": "IMMEDIATE",
"action": "suspend_current_hiring",
"description": "Pause hiring for marketing manager positions pending process review",
"timeline": "immediate"
},
{
"priority": "HIGH",
"action": "retrain_hiring_managers",
"description": "Mandatory unconscious bias training for all hiring personnel",
"timeline": "within_30_days"
},
{
"priority": "MEDIUM",
"action": "restructure_interview_process",
"description": "Implement structured interviews with diverse panels",
"timeline": "within_60_days"
}
]
}