In many African AI projects, available datasets are either imported (trained on non-African populations) or incomplete (lacking local language, gender, or cultural nuance). This misalignment risks perpetuating systemic bias under the guise of neutrality.This webinar will offer a deep dive into the Essential Questions of Data Discovery including a case study on the requirement for building effective TFGBV prevention datasets that include African languages.
Registration Link. TBC