Digital Humanities

ImageNet's Western-centric labeling shaped how every major AI sees race, gender, and culture. 14 million images. One worldview. This is how bias became infrastructure.

When an algorithm trained on biased arrest data deemed Black defendants 'high risk' at twice the rate of whites, it exposed how 'objective' AI amplifies injustice.

Amazon's AI recruiter systematically downgraded women's resumes — not by design, but by learning from a decade of biased hiring data. The past shapes the future.

A 2016 proof shows algorithmic fairness definitions cannot coexist. Tech giants promised the impossible—here's why nobody admits it.

The EU demanded auditable AI. Tech giants responded with deeper black boxes. Inside the structural limits of algorithmic accountability.

Tech companies claim they've 'fixed' biased AI. But their solutions often increase model complexity, burying discrimination under proprietary layers.