- Most AI hiring tools can’t be fair — by design.
Predictive AI asks:
“Who got hired before?”
That guarantees bias.
If the past favored:
• certain genders
• elite schools
• linguistic mirroring
• socioeconomic proxies
AI doesn’t fix it.
It scales it. - Fairness requires causal reasoning:
“Would this decision change if the candidate were different — but equally capable?”
That’s counterfactual fairness. - We’ve detailed this in our latest whitepaper.
📄 Whitepaper link: https://veriprajna.com/whitepapers/engineering-fairness-ai-recruitment-causal-ai-predictive
For enterprise discussions:
📧 [email protected]
💬 +91 92170 59957
Don’t automate bias.
Engineer fairness.