How AI Reinforces Inequality—And How We Fight Back

What if the biggest threat of AI isn’t sentience—but systemic bias?

In Episode 23 of The Neuvieu AI Show, we examine how artificial intelligence, when trained on historically biased data, can perpetuate—and even amplify—the very inequalities it’s supposed to fix. From healthcare to housing, finance to policing, we explore how AI turns injustice into infrastructure.

We break down:

• How AI systems learn from—and repeat—past discrimination
• Why algorithmic feedback loops make bias harder to detect over time
• Real-world consequences, like mortgage discrimination costing Black and Latino homeowners $500M+ annually
• The danger of “techwashing”—where biased systems are falsely perceived as neutral
• And how open-source tools like IBM’s AI Fairness 360 show we can build better, more equitable systems—if we commit to transparency and reform

This episode calls for coordinated, structural action—not just code fixes—to prevent algorithms from becoming digital gatekeepers of systemic oppression.