Because AI models are highly stochastic, they should be prepared for a broad range of harms; the speaker's team uses automated evaluations and deeper human testing focused on the most pronounced risks.

“But we think it's also really important because the models are very stochastic in nature. They need to be prepared for the full suite of harms, and I think that's something that we try to evaluate with our more automated evals and then go much deeper with human testing on their most pronounced risks.”