Center for Practical AI
Interactive Tool · AI and Employment

ATS Resume Scanner

75% of resumes are rejected by software before a human sees them. Walk through an annotated resume — section by section — to understand what ATS systems flag, where racial and socioeconomic bias enters, and what you can do as a job seeker and as a policy advocate.

Individual tactics help individuals. Systemic bias requires systemic enforcement. This tool addresses both.

75%

Resumes rejected by ATS before human review

10–50%

Callback gap by perceived name race (Kline et al., 2022)

1st

EEOC AI hiring discrimination settlement: iTutorGroup, 2023

ATS Resume Scanner

What algorithms flag — and why it matters

ATS Flag
Bias Risk
Note
Bias Risk

Name

LaShonda Williams

Finding: Race-associated name

Resume audit studies (Bertrand & Mullainathan, 2004; Kline et al., 2022) consistently find that resumes with names perceived as Black receive 10–50% fewer callbacks than identical resumes with white-perceived names. AI screening tools trained on hiring data reproduce this pattern unless explicitly audited for name bias.

What you can do

No legal requirement to use your preferred name on a resume. Some candidates use a nickname. The deeper fix is enforcement — EEOC guidance on disparate impact applies to AI screening.

Sources:Bertrand & Mullainathan (2004), Kline et al. (2022), EEOC AI in Employment Guidance (2023), HUD Fair Housing & AI Report (2023), MIT Media Lab HireVue analysis (2019). Individual tactics do not fix systemic bias — enforcement does.

← Back to AI and Employment Guide

Teaching AI and employment rights?

The educator guide includes facilitation notes for the ATS scanner, discussion questions on disparate impact theory, and a worker advocacy exercise.