Eliminate Hiring Bias with AI-Powered CV Anonymisation in HR Duo

Manual shortlisting carries more bias than most hiring managers realise.

Even before an interview, CVs can trigger unconscious decisions based on names, photos, dates of birth, addresses, or educational history. These signals, often unrelated to a candidate’s ability, can influence shortlisting and lead to missed opportunities, biased hiring, and compliance risks.

That’s why HR Duo’s AI-powered CV Anonymisation tool has been built into our applicant tracking system (ATS), helping HR teams and line managers to shortlist candidates fairly, focusing on what matters, and speed up early-stage recruitment without sacrificing due diligence.

Why CV Anonymisation Matters

Unconscious bias still plays a major role in recruitment, even when employers believe they’re being fair.

British citizens from ethnic minority backgrounds have to send, on average, 60% more job applications to get a positive response from employers compared to their white counterparts, according to researchers at Nuffield College's Centre for Social Investigation (CSI). They also found that candidates with white-sounding names were invited to interview 24% more often than those with ethnic minority names, even when CVs were identical in skills and experience.

This shows that bias can creep in during the earliest stages of hiring, before a candidate has even been seen or spoken to. However, it’s not just a moral issue, it’s a business one:

• 83% of Gen Z jobseekers say a company’s commitment to diversity influences their decision to apply.
  
• Companies with diverse teams are 36% more profitable than their less inclusive peers.

By removing personal information from CVs, including names, gendered pronouns, and addresses, CV Anonymisation helps employers:

• Focus on skills, not stereotypes
• Protect against discrimination claims
• Promote fairer hiring decisions
• Boost employer brand and candidate trust
• Improve DEI metrics without compromising on quality

How CV Anonymisation Works in HR Duo

Instead of manually redacting each CV (and hoping nothing gets missed), HR Duo uses machine learning and natural language processing to automatically identify and remove potentially biasing fields. This includes:

1. Name

• Bias risk: Names may suggest ethnic or cultural background

• Example bias: CVs with white-sounding names get 24% more callbacks

• Impact: Can lead to racial or cultural discrimination, often unintentionally

2. Date of Birth and Age

• Bias risk: Assumptions about energy, tech skills, or seniority based on age

• Example bias: Older candidates being overlooked for roles seen as “fast-paced” or “digital-first”

• Impact: Can contribute to ageism and breach age discrimination laws

3. Gendered Pronouns

• Bias risk: Triggers gender bias, including assumptions about ability, assertiveness, or cultural “fit”

• Example bias: Male candidates are considered more suitable for leadership or technical roles

• Impact: Skews hiring decisions away from ability and towards stereotypes

4. Photos

• Bias risk: Visual appearance influences perceptions of professionalism, likability, or suitability

• Example bias: Beauty bias (preferring more conventionally attractive candidates) or appearance-based discrimination

• Impact: Leads to subjective decisions unrelated to job performance

5. Location Data

• Bias risk: Location can signal socioeconomic status or imply commuting challenges

• Example bias: Candidates from certain postcodes are perceived as less reliable or committed

• Impact: Penalises candidates unfairly based on geography, not ability

6. Educational Institutions

• Bias risk: University or school names may suggest class, privilege, or perceived prestige

• Example bias: Favouring Russell Group graduates over equally capable candidates from newer or regional universities

• Impact: Reinforces social inequality and undermines a skills-based hiring approach

7. Other Redactable Biasing Fields

• Race
• Sexual Orientation
• Ethnicity
• Nationality
• Religion
• Social Media handles
• Phone number
• References
• Personal Public Service Number (PPSN)
• National Insurance Number (NIN)

You choose the fields to redact, and HR Duo returns clean, anonymised CVs in the same format, ready for review. All that’s left is what matters: skills, experience, and suitability. No more spreadsheets. No more manual formatting. Just bias-free, consistent shortlisting, handled in seconds.