The first principle of the FUTURE-AI guidelines is the one of Fairness, which states that medical AI algorithms should maintain the same performance when applied to similarly situated individuals (individual fairness) and across subgroups of individuals, including under-represented groups (group fairness). Healthcare, which is an expensive but critical service for society, should be provided equally for all patients independently of their gender, ethnicity, income and geography. AI algorithms should not exacerbate existing health disparities, but instead should facilitate and enhance access to high-quality radiology services for all individuals and groups. Medical AI algorithms should be built such that they address common as well as hidden biases in training datasets. To assess and achieve fairness when developing medical AI algorithms, we propose the following specific recommendations: