Sarah Johnson
AI HR Manager at ailaborbrain.com
Sarah Johnson is a PhD candidate in Labor Economics at Stanford University, where her research focuses on the intersection of artificial intelligence and workforce dynamics, particularly the measurement of skills gaps and the fairness of algorithmic hiring pipelines. She has published on the use of machine learning in labor market analytics and is currently investigating the impact of AI on occupational transitions. Deep experience. Intellectual curiosity.
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Recent articles by Sarah Johnson
- NYC Local Law 144 Bias Audit Costs: How to Verify $1.5K vs $5K October 29, 2026
- AI hiring tools compliance: EU AI Act (2026) — 6 steps vs August 2 deadline October 26, 2026
- Clerical retraining 2026: Bureau of Labor Statistics (BLS) 2% decline vs Lightcast 2.5x October 23, 2026
- AI Hiring Bias Audits: NYC's Four-Fifths Rule—Document or Defend? October 20, 2026
- Job exposure vs skills gap: Occupational Information Network (O*NET) or postings for 2026? October 17, 2026
- Algorithmic hiring bias ratio: 4/5ths rule flags EEOC action at 0.82 vs 0.95 October 14, 2026
- Which AI Hiring Tools Need a Bias Audit: NYC Local Law 144 Rules for 2026 October 11, 2026
- Who Gets the Overtime Shift: 2026 Fair Workweek Gap — 24% Audit or Trust October 8, 2026