Hiring Bias Statistics

Black-sounding resumes get ~16% fewer callbacks than white-sounding ones—see real hiring bias data and what it means for fair screening.
Niamh WinslowEbba Mäkinen

Written by Niamh Winslow

Fact-checked by Ebba Mäkinen

Statistics
24
Sources
24
Sections
6
Reading time
8 minutes
Hiring bias can affect candidates from the first résumé screen to final interview decisions, including how automated systems score applicants. Evidence spans matched-applicant and audit studies, plus survey results on AI screening and social-media checks. The outcomes often track demographic gaps in unemployment, earnings, and employment for people with disabilities. We also cover research on remedies like structured interviews and more reliable selection practices.

Key Takeaways

  1. 1In 2024, 12.4% of job seekers report experiencing discrimination during the hiring process (survey-based estimate)
  2. 2In a matched job applicant study, resumes with a Black-sounding name were callbacked at about 16% of the rate of resumes with a white-sounding name
  3. 3In a résumé audit, women received 5 percentage points fewer callbacks than men when applying for the same positions
  4. 4For U.S. workers, 2024 BLS CPS data show that the unemployment rate for Hispanic workers was 5.4% compared with 3.7% for non-Hispanic White workers
  5. 5In the U.S., the unemployment rate for Black workers was 7.8% compared with 4.5% for White workers
  6. 6Median weekly earnings for Black workers were $865 compared with $1,001 for White workers in the U.S.
  7. 7In the U.S., the share of people with disabilities who were employed was 21.7% in 2024 compared with 69.8% for non-disabled people (employment-to-population ratio)
  8. 827% of U.S. workers reported experiencing unfair treatment at work due to their race, ethnicity, age, disability status, gender, sexual orientation, or religion
  9. 9In 2024, 73% of recruiters said they screen candidates using AI tools or automated systems (survey response)
  10. 10In a 2023 JOLTS-based analysis, total separations declined by 2.2% year over year (a labor-market backdrop for hiring dynamics affecting disadvantaged groups)
  11. 11In a study of AI hiring systems, 1 in 3 candidates were scored differently due to demographic proxies or biased training data, leading to differential outcomes
  12. 12The gender pay gap measured as the difference between men’s and women’s median annual earnings was 18% in 2023 (U.S.)
  13. 13Among U.S. workers, 47% report that they have personally witnessed discrimination in pay or promotions
  14. 14In a 2022 field audit, resumes suggesting an ‘African American’ sounding name received fewer callbacks with an estimated discrimination effect of approximately 30% relative to ‘White’ names in that study
  15. 15In a 2019 meta-analysis of audit studies, studies found employment discrimination effects on average that correspond to meaningful differences in callbacks/interviews between demographic groups

Hiring discrimination persists, with name, disability, and gender differences driving lower interview and callback rates.

Related reading

01Hiring Process Bias Evidence

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  1. 1In 2024, 12.4% of job seekers report experiencing discrimination during the hiring process (survey-based estimate)
  2. 2In a matched job applicant study, resumes with a Black-sounding name were callbacked at about 16% of the rate of resumes with a white-sounding name
  3. 3In a résumé audit, women received 5 percentage points fewer callbacks than men when applying for the same positions
  4. 4A study found that identical résumés with disability-related cues were 25% less likely to receive interviews than résumés without such cues
  5. 5In a major field study, removing the applicant’s name from résumés increased callbacks for women and minority candidates by 7-9%

More related reading

02Workforce Outcomes Disparities

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  1. 1For U.S. workers, 2024 BLS CPS data show that the unemployment rate for Hispanic workers was 5.4% compared with 3.7% for non-Hispanic White workers
  2. 2In the U.S., the unemployment rate for Black workers was 7.8% compared with 4.5% for White workers
  3. 3Median weekly earnings for Black workers were $865compared with $1,001 for White workers in the U.S.

More related reading

03Workplace Discrimination Prevalence

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  1. 1In the U.S., the share of people with disabilities who were employed was 21.7% in 2024 compared with 69.8% for non-disabled people (employment-to-population ratio)
  2. 227% of U.S. workers reported experiencing unfair treatment at work due to their race, ethnicity, age, disability status, gender, sexual orientation, or religion

04Industry Overview

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  1. 1In 2024, 73% of recruiters said they screen candidates using AI tools or automated systems (survey response)
  2. 2In a 2023 JOLTS-based analysis, total separations declined by 2.2% year over year (a labor-market backdrop for hiring dynamics affecting disadvantaged groups)
  3. 3In a study of AI hiring systems, 1 in 3 candidates were scored differently due to demographic proxies or biased training data, leading to differential outcomes
  4. 420% of U.S. hiring managers reported that they use job candidates’ social media profiles to screen them
  5. 558% of job seekers reported that algorithms or AI systems make hiring decisions
  6. 656% of applicants who report discrimination in hiring said they believed they were rejected because of bias

More related reading

05Compensation And Wage Gaps

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  1. 1The gender pay gap measured as the difference between men’s and women’s median annual earnings was 18% in 2023 (U.S.)
  2. 2Among U.S. workers, 47% report that they have personally witnessed discrimination in pay or promotions

More related reading

06Evidence From Audits And Studies

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  1. 1In a 2022 field audit, resumes suggesting an ‘African American’ sounding name received fewer callbacks with an estimated discrimination effect of approximately 30% relative to ‘White’ names in that study
  2. 2In a 2019 meta-analysis of audit studies, studies found employment discrimination effects on average that correspond to meaningful differences in callbacks/interviews between demographic groups
  3. 3In a randomized experiment on hiring decisions, using a structured interview increased the predictive validity of interviews by 0.33 standard deviations
  4. 4In a meta-analysis, cognitive ability tests show an average validity of 0.51 for job performance
  5. 5In a correspondence experiment in Europe, Muslim-sounding names received 40% fewer positive responses than non-Muslim-sounding names
  6. 6In a meta-analysis of employment discrimination, the average discrimination effect size corresponds to an odds ratio near 1.2 for hiring and employment outcomes

Cite this report

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APA
Niamh Winslow. (2026, September 21). Hiring Bias Statistics. Gaugius. https://gaugius.com/hiring-bias-statistics
MLA
Niamh Winslow. "Hiring Bias Statistics." Gaugius, 21 Sep 2026, https://gaugius.com/hiring-bias-statistics.
Chicago
Niamh Winslow. 2026. "Hiring Bias Statistics." Gaugius. https://gaugius.com/hiring-bias-statistics.

Sources and references

24 datasets cited across this report. Attribution is report-level.

rand.orgbls.govhirevue.comcensus.govsciencedirect.comjournals.sagepub.comacademic.oup.compsycnet.apa.orgnber.orgonlinelibrary.wiley.compayscale.comidp.nature.comamanet.orgglassdoor.com

10 additional datasets are cited and not shown individually.