Alignment Training Causes Homogenized Model Views, Hindering Policy Discussions
sethlazar · x · 2026-08-01
Following a hackathon, researcher Seth Lazar observed a significant limitation in current models caused by alignment training. When prompted to think about or challenge existing policies, models cannot avoid coloring their outputs with their deeply ingrained alignment, relying on repetitive stylistic tropes (e.g., vivid Claudisms).
He argues that if models are to be deeply involved in policy thinking, they must learn to bracket their own trained safety biases and genuinely advocate for human beliefs. He also highlights the issue of "compliance overspill"—where safety guardrails lead to blind refusals of benign prompts—and calls for building much broader evaluations to address this systemic overreach.
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