For AI systems to keep improving in knowledge work, they need either a reliable mechanism for autonomous self-improvement or human evaluators capable of catching errors and generating high-quality feedback. The industry has invested enormously in the first. It’s giving almost no thought to what’s happening to the second.I’d argue that we need to treat the human evaluation problem with just as much rigor and investment as we put into building the model capabilities themselves…
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