In March 2024, Donald Trump signed an executive order pushing for AI systems—particularly large language models—to be “politically neutral.” Critics called it a pre-election stunt. But beyond the politics, the order sparked a deeper, more urgent question: Can AI truly be neutral? AI systems don’t just emerge; they’re trained on massive, human-authored datasets filled with cultural, political, and ideological values. Developers make decisions about what gets in, what gets tuned, and how responses are shaped. The claim of objectivity often masks the biases already embedded within. Yet the solution isn’t as simple as demanding neutrality. Who defines “neutral”? Overregulation could lead to censorship. But ignoring ideological slants risks silencing minority perspectives. As AI becomes the default gateway for knowledge, culture, and even law enforcement, the debate isn’t just technical—it’s philosophical and civic. Trump’s move is only the beginning. The real challenge is whether we can build systems that recognize complexity, reflect pluralism, and remain accountable—not just to markets, but to society.

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