Another is the need for low-resource algorithms that can translate to and from all the world's languages, the vast majority of which do not have large parallel training texts available. This problem is exacerbated by the tendency of many MT approaches to focus on the case where one of the languages is English (Anastasopoulos and Neubig, 2020). ∀ et al. (2020) propose a participatory design process to encourage content creators, curators, and language technologists who speak these low-resourced languages to participate in developing MT algorithms. They pro-low-resourced languages vide online groups, mentoring, and infrastructure, and report on a case study on developing MT algorithms for low-resource African languages.