I theoretically propose and experimentally test a novel behavioral channel, robot-babysitting, that can impose switching and learning costs on workers when automation is complementary. My theoretical model shows that one can identify these costs by varying the automatability of the production process and observing the resulting change in the demand for automation. The experimental results support the hypothesis that the costs due to robot babysitting are empirically relevant. Subjects with high cognitive flexibility and reflectivity are less susceptible to these costs. I quantify the costs by structurally estimating the model and find that the average learning costs are small, while the average switching costs are large in absolute value but negative. The textual analysis of subjects’ choice reasons reveals that many of them found the task-switching environment stimulating and non-monotonous. My results suggest that the net effect of complementary automation on workers is a priori ambiguous and that complementary automation will be most beneficial for workers with high cognitive flexibility and reflectivity.