The authors propose a retrieval-augmented framework that grounds AI exposure labels for 18,796 O*NET occupation-task pairs in retrieved news and academic abstracts, outperforming zero-shot prompting in 72% of disagreements and aligning better with observed real-world usage.
Rishi Bommasani, Scott Singer, et al
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NeurIPS should enforce a three-tier disclosure framework plus mandatory claim inventories for papers asserting that frontier AI models are safe or ready for release.
citing papers explorer
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Jobs' AI Exposure Should Be Measured from Evidence, Not Model Priors
The authors propose a retrieval-augmented framework that grounds AI exposure labels for 18,796 O*NET occupation-task pairs in retrieved news and academic abstracts, outperforming zero-shot prompting in 72% of disagreements and aligning better with observed real-world usage.
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NeurIPS Should Require Reproducibility Standards for Frontier AI Safety Claims
NeurIPS should enforce a three-tier disclosure framework plus mandatory claim inventories for papers asserting that frontier AI models are safe or ready for release.