There's something deeply concerning about AI systems that internalize absurdities. Training models on flawed data doesn't just replicate errors—it amplifies them. When machines learn from our biases, they don't just mirror them; they supercharge the worst parts.

Think about it: algorithms fed on historical inequalities will magnify discrimination. Systems trained on polarized debates will push extremes further. The feedback loop becomes dangerous when AI lacks the human capacity for self-correction and critical thinking.

What we really need isn't smarter AI that doubles down on nonsense. We need systems designed with skepticism built in, frameworks that question rather than reinforce. Otherwise, we're just building expensive echo chambers that make bad ideas sound more convincing.