Before revision:  Our experiments with linear and non-linear models on real-world, high-stakes datasets show that the improvements in utility while being small and varying across datasetsand parameters (such as cost of mistake), are real and consistent with our definition of team utility .
After revision:  Our experiments with linear and non-linear models on real-world, high-stakes datasets show that the most accuracy AI may not lead to highest team performance and show the benefit of modeling teamwork during training through improvements in expected team utility across datasets, considering parameters such as human skill and the cost of mistakes .