Automated Hiring Tools Reject Ethnic Minority Candidates Faster

Automated hiring systems are rejecting job candidates within minutes of application—sometimes before the posting even closes—with ethnic minority applicants bearing the brunt of the impact, according to new research from non-profit People Like Us and Censuswide.

The survey of 2,000 UK job seekers found that 80% have been rejected in the past two years, with nearly three-quarters suspecting at least one rejection was generated automatically without human review. Only 15% say an employer disclosed that automated systems were used in the decision.

The disparities are stark: 70% of ethnically diverse job seekers have altered or hidden elements of their CV—including country of origin, faith, or even their name—out of fear that software would screen them out, compared to 57% of white candidates. These diverse candidates apply for a third more roles than white counterparts and are rejected faster, with 41% receiving rejections within an hour versus 32% for white applicants.

Why it matters

As companies adopt AI and automated tools to manage surging application volumes, the lack of transparency and accountability creates systemic barriers that undermine diversity efforts. While employers may implement these systems in good faith, research analyzing over 100,000 live graduate applications from UCL shows ethnic minority candidates are disproportionately rejected at screening stages despite having similar qualifications—suggesting bias is baked into the process.

Campaign Demands Transparency

In response, People Like Us launched "Reject the Rejections," a campaign created with creative agency Worth Your While that aims to empower rejected applicants and push for employer accountability. The centerpiece is a four-minute film starring actor Ebenezer Gyau, built from actual rejection language sent to ethnic minority candidates.

The campaign also provides a free online tool allowing rejected candidates to request human review of automated decisions—a right that exists under UK Data Protection laws but remains largely unknown. Three-quarters of job seekers are unaware they may have this legal right, and most employers fail to honor it.

The Scale of the Problem

Several findings underscore the scope of automated screening's impact:

• 42% of job seekers have received identical or near-identical rejection emails from different employers, suggesting the same software may be screening out the same people across multiple applications
• 82% of employers who checked their systems found outcomes vary by ethnicity
• 74% of rejected candidates suspect at least one rejection was generated without human review

"Employers aren't the villains here, most resort to automations in good faith to cope with a surging volume of applicants, and four in ten did it believing they were reducing bias," said Sheeraz Gulsher, co-founder of People Like Us. "However, good faith isn't governance—when 82% of the employers who checked found outcomes vary by ethnicity, 'we didn't know' stops being a defence."

The campaign calls for employers to disclose automation use before candidates apply, ensure human accountability when decisions are challenged, and submit to independent bias audits. It also urges the government to consider screening transparency laws.

The findings and campaign details were first reported by Worth Your While and People Like Us.