Human computation is the technique of performing a computational process by outsourcing some of the difficult-to-automate steps to humans. In the social and behavioral sciences, when using humans as measuring instruments, reproducibility guides the design and evaluation of experiments. We argue that human computation has similar properties, and that the results of human computation must be reproducible, in the least, in order to be informative. We might additionally require the results of human computation to have high validity or high utility, but the results must be reproducible in order to measure the validity or utility to a degree better than chance. Additionally, a focus on reproducibility has implications for design of task and instructions, as well as for the communication of the results. It is humbling how often the initial understanding of the task and guidelines turns out to lack reproducibility. We suggest ensuring, measuring and communicating reproducibility of human computation tasks.