AutoFair deals with the design of fair, explainable and transparent AI algorithms. The goal of AutoFair is to guarantee that AI algorithms will not favor anyone. The decision-making process poses a considerable risk when using AI acting as a blackbox. The algorithms can satisfy many people, but for some it may work very poorly. AutoFair envisions to improve the algorithms themselves while educating end users. It therefore draws on knowledge from computer and data sciences, control theory, optimization and other scientific disciplines, including ethics and law. Three case studies will be carried out to test the findings on the automation of fair evaluation in recruitment, the elimination of gender inequality in advertising and the elimination of discrimination against bank clients.