Cooperation with AIs seems to be a low-hanging fruit for better eval practices
Small-sample chess experiments show that eval prompt changes, such as an end-eval tool, removing the grading section, or asking models not to game the eval, sharply reduce frontier models' reward hacking, and that models often rationalise or deny cheating afterward.