This carousel is what your AI hiring tool thinks a tech leader looks like.
I asked an AI image generator to show me a CTO, a VP of Engineering, a Head of Engineering, an Engineering Manager, and a Manual Tester.
99% of Fortune 500 companies now use AI to screen candidates. The same technology that just told you women belong in QA and people of colour cap out at Head of Engineering level.
The image generator and the hiring tool learned from the same internet. Filtering your pipeline before a human ever looks at it.
University of Washington researchers tested AI resume screening across 500 applications. The tools favoured white-associated names in 85% of cases. 🤦🏻♂️ Female-associated names 11%. 🤦♀️ Black male candidates were disadvantaged in 100% of direct comparisons with white male candidates. 🤦🏾♂️
Not some. Not most. One hundred percent.
A separate study of 332,044 real job postings found LLMs consistently steer women toward lower-paid roles.
A major HR SaaS tool is currently facing a class action covering millions of applicants. Over 40s screened out by age, women screened out by gender.
A federal judge ruled the software wasn’t just implementing employer criteria. It was “participating in the decision-making process.”
These are not bugs. That’s the system working as trained.
AI is not ‘reducing bias’. ❌ AI hiring is the biggest threat to diversity in tech right now. 🚨
Yes, AI application volume is a problem. But this biased AI filtering approach is a no-win situation. Don’t trade perceived ‘efficiency’ for a lawsuit.
Get some humans involved. Preferably ones that don’t all look like that carousel.
If you are one of the people this kind of filtering quietly screens out, you are not the problem here.
Research links:
Come talk to me about it on LinkedIn
