You’ve got 147 resumes in your inbox for an open role, and two hours to screen them all before your next meeting. By the time you’ve completed your rapid-fire review, this shortlist looks a lot like your last one (and the one before that).
Hiring teams are under increasing pressure fueled by time constraints, reduced headcount and an influx of applicant volume driven by AI. Under these conditions, it’s easy for screening to slip from evaluating true capability to pure pattern recognition.
This approach leaves teams wide open to a big hiring problem: unconscious bias.
When bias creeps into hiring
Bias in recruitment rarely happens on purpose; most talent professionals are actively trying to do right by every candidate. But unconscious bias creeps in when many decisions need to be made quickly. The brain takes shortcuts, leaving even the most well-intentioned hiring teams at risk. It can take many forms, but some of the most common forms it takes in recruitment are:
Name bias: Bertrand & Mullainathan’s landmark 2004 study found that applicants with ‘white-sounding’ names needed only 10 resumes sent to get a callback, compared to 15 for applicants with names originating from culturally diverse backgrounds (a 50% gap). Two decades on, the problem hasn’t really shifted. A US study sent over 83,000 fictitious applications to 108 of the largest employers and found that resumes with more diverse names still received fewer callbacks than identical resumes with white-sounding names.
Gender bias: Some research indicates women are 30% less likely to be called for a job interview compared to a man with equivalent skills.
Age bias: Resumes showing graduation dates from earlier decades receive around 40% fewer callbacks than equivalent resumes from recent graduates.
Prestige bias. A big-name employer on a resume signals competence to a reviewer’s brain in seconds. A startup nobody’s heard of signals risk. Neither judgment has anything to do with whether the candidate’s actual skills match the role.
Time-to-decision bias. Research cited by Forbes shows that 60% of hiring decisions are made within the first 15 minutes of an interview, and 25% within the first five – hardly enough time for an in-depth decision to be made about the candidate’s suitability for the role.
While most bias is unconscious, unfortunately some isn’t. And regardless, good intentions haven’t been enough to stop it from perpetuating. The best way to keep bias out of your recruitment process is to build systems that prevent it from being a factor in the first place.
6 tips to remove bias from your hiring process
1. Audit your job ads first
Job ads loaded with gender-coded language (“dominant,” “competitive,” “rockstar”) measurably discourage women or gender-diverse applicants from applying, and long “nice-to-have” wish lists discourage jobseekers who may not check every box.
What to do:
- Keep language welcoming and gender-neutral.
- Separate “must-have” from “nice-to-have,” and keep must-have requirements focused on skills key to the role.
Head here for some more tips on how to write a stand-out job ad.
2. Show diverse people and stories on your career site
Candidates self-select out of applying long before a recruiter sees their resume. If every photo, testimonial, and “day in the life” story on your careers page features the same kind of person, you’re signalling (perhaps unintentionally) who belongs there.
What to do:
- Feature employees across different backgrounds, career paths, and seniority levels.
- Include stories from people who didn’t take the traditional route: career switchers, internal promotions.
- Audit your imagery and language with the same scrutiny you would apply to a job ad, and ensure it’s reflective of your company culture.
3. Commit to skills-based hiring
Skills-based hiring means evaluating candidates on what they can actually do, rather than where they studied or have worked. Skills are 5 times more predictive of job performance than education, and taking a skills-based approach can increase your talent pool by up to 9 times. It’s not just fairer, it’s also more effective, with 90% of employers who adopt skills-based hiring reporting an increase in workplace diversity, and 56% of people leaders reporting improved retention.
What to do:
- Define the specific skills a role requires before starting to look at candidates
- Score every applicant against the same rubric, not a gut-feel of “good fit.”
- Replace resume screening with skills assessments or work samples where possible.
4. Give your interviews more structure
Time-to-decision bias means most interviewers have made up their mind in the first few minutes of meeting a candidate, before there’s enough evidence to justify it. Creating interview structure can slow this down, and ensure a fairer evaluation.
What to do:
- Ask every candidate for a role the same core questions, in the same order, scored against the same rubric.
- Use a panel process and have each interviewer score independently before comparing notes, so one person’s early read doesn’t anchor the rest of the panel.
- Build in a short gap between the interview and the decision. Even waiting until the next day reduces the risk of snap judgments.
5. Screen with anonymisedanonymized profiles
AnonymisingAnonymizing profiles at the first screening stage removes the name, photo, and graduation year that bias could latch onto, so the initial call is made on skills and experience alone.
This approach is supported by the right tech. PageUp’s screening tools let hiring teams de-identify particular details until a candidate has already cleared the skills bar.
Read more about how PageUp’s anonymisedanonymized screening works.
6. Get help from AI that’s actually been proven bias-free
AI was introduced as a fix for hiring bias, as algorithms (should) be more objective than humans. But an algorithm is only as fair as the data it learns from, and most hiring data is full of exactly the patterns outlined above. Train a model on your past “successful hires”, and it will learn your past biases too.
PageUp’s Skills Matching sidesteps this by scoring candidates against the job, not your hiring history. It extracts the required skills directly from the job description and rates every applicant, from ‘Excellent Match’ to ‘Not a Match’, on skills fit alone. Every output is source-cited, and bias-free by design, so you can get a little help without worrying about the integrity of the data. With help from Paige, our new agentic hiring assistant, all this information is one easy conversation away (forget manual rankings or sifting through modules).
Want proof, not a promise? Warden AI independently audits PageUp Skills Matching monthly to ensure outputs remain bias-free. See our latest results here.
Let’s bias-proof your hiring
A fairer hiring process and a stronger hiring process are two sides of the same coin. With the right tech, it’s easy to replace snap judgments and pattern-matching with bias-free, skills-based systems. Book a demo with PageUp to see how it works.
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