Your Name: Literally Sabotaging Your Career (Because Gender Bias Baked Into AI)
- Alex C
- Sep 27
- 4 min read
Plot twist: The hiring game is rigged, and it's not even subtle anymore.
Let's drop a truth bomb that's about to ruin your day: men's names are favored 51.9% of the time versus women's names at just 11.1% in AI screening. But her's where it gets absolutely unhinged... If you're a black man (or have a distinctly black, masculine name), AI systems never - and we mean never - preferred your resume over a white man's. Zero percent of the time.
Yeah, you read that right. We're living in 2025 and hiring algorithms are out here acting like it's 1955.
The Tea: AI is More Biased Than Your Racist Uncle
A groundbreaking study from the University of Washington just exposed what just about every Gen Z jobseeker already suspected: the hiring process is absolutely broken. Researchers tested three top AI screening tools with over 550 real resumes and found that white-associated names were preferred 85% of the time while distinctly Black names got the nod only 9% of the time.
But wait... there's more! Even Federal Reserve Chair Jerome Powell is admitting what we all know: "kids coming out of college and younger people, minorities, are having a hard time finding jobs." When the literal head of the Fed is calling out the nightmare - you know it's real.
The ATS Black Hole Isn't a Bug - It's a Feature
Remember when we told you that 75% of resumes get rejected by ATS systems before humans ever see them? Well, it seems some new data is coming out that shows the stat might be a little skewed. But here's a stat based on what's actually happening: 88% of employers believe they're losing 'highly qualified' candidates who get screened out because they don't have 'ATS-friendly' resumes.
Translation: The system isn't just broken... it's actively working against you.
Gen Z: The Most Discriminated Generation in Hiring
Here's where it gets personal for us. Six in 10 employers are already firing Gen Z workers they hired fresh out of college, and 39% of hiring managers actively avoid hiring recent college graduates in favor of older candidates.
Let that sink in... They'd rather hire someone overqualified than give you a fair shot. 33% of hiring managers think we lack work ethic, 29% call us entitled, and 28% say we're unmotivated.
Plot twist: Maybe we're not unmotivated - maybe we are tired of a rigged system that judges us before we even walk through the door.
The Resume Roulette Nobody Asked For
Here's the kicker about ATS (Applicant Tracking Systems): Around 75% of qualified candidates face rejection due to keyword mismatches or failure to meet specific criteria. But when those criteria are biased from the jump, you're playing a rigged game. One company's ATS searched exclusively for "AngularJS" (a framework discontinued in 2010) when they actually wanted "Angular." Every qualified applicant without the outdated keyword was automatically rejected.
It's not efficiency - it's discrimination and incompetence being masked by fancy technology that just makes it harder to spot.
The Real Talk About "Meritocracy"
Companies love talking about hiring "the best candidate," but research consistently shows that white-sounding names get called back for jobs more than Black ones. A recent massive study involving 83,000 fake applications found white applicants were favored by around 9% over Black applicants with identical qualifications.
Why This Matters for Early Talent
As Gen Z enters the workforce, we're facing a perfect storm:
99% of Fortune 500 companies use ATS platforms
AI adoption is disrupting entry-level roles
54% of Gen Z candidates are reluctant to use outdated application technology
We're stuck navigating systems designed by and for previous generations, using technology that actively discriminates against diversity.
Don't Panic: There's Actual Hope
Here's where enterN comes in to flip the script on the whole broken system:
No More Games: Our platform eliminates the bias lottery. No names, no photos, no demographic identifiers during initial screening. Just your skills, your vibe, and your potential.
Swipe Right on Talent: Forget keyword-stuffed resumes that get eaten by ATS black holes. Our matching system focuses on compatibility: both ways. You swipe on companies and jobs that align with your values, employers swipe on jobseekers who bring the energy they need.
Anti-Ghosting Guarantee: 60% of jobseekers want better communication during the application process. Our platform keeps receipts and displays a responsiveness badge to ensure that every interaction comes with a response. No more sending resumes into an endless void.
Skills Over Spreadsheets: Instead of parsing your resume for keywords, we let you showcase your actual preferences, interest, and abilities through interactive assessments and portfolio pieces. We get that who you are just can't be captured on a Word document.
Real-Time Transparency: You'll always know where you stand in the process. No more wondering if your application made it past the robots.
The Future of Hiring is Just a Swipe Away
The current hiring system isn't just broken - it's actively harmful. But... we don't have to accept it. We can build something better, something fairer, something that actually works for a new generation.
Ready to ditch the resume roulette and join a hiring revolution that puts potential front and center? The enterN platform launches in early 2026 and its about to make biased hiring algorithms as outdated as a fax machine.
Join the waitlist at: https://www.enter-n.com and tell the world that your name shouldn't determine your career - your skills and actual preferences should.
Want to read more on this topic? Check out these recommended articles:
Wilson, K. & Caliskan, A. (2024). University of Washington study on AI hiring bias.
NPR (2023) "Companies are turning to AI for hiring. That could lead to discrimination."
Fortune (2025) "Workday, Amazon AI employment bias claims."
Stack Overflow (2025). "AI vs Gen Z: How AI has changed the career pathway."
Equal Employment Opportunity Commission hearings on AI discrimination
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