The article “Context-specific causal discovery for categorical data using staged trees” written by Manuele Leonelli and Gherardo Varando was presented at the 26th International Conference on Artificial Intelligence and Statistics held in Valencia, Spain. A fundamental task in various disciplines of science, including biology, is to find underlying causal relations and make use of them. It is often necessary to discover causal relations by analyzing statistical properties of purely observational data, which is known as causal discovery or causal structure search. The article introduces new machine learning algorithms for identifying complex causal relationships in observational categorical data and showcases their use in a variety of domains, including environmental, medical and social sciences. The article can be found at https://proceedings.mlr.press/v206/leonelli23a/leonelli23a.pdf.