The article discusses how researchers have been studying instrumental variables to understand cause and effect relationships without needing certain assumptions. They focus on identifying these relationships rather than making inferences. The main findings suggest that new methods can help researchers identify causal effects even without normality, linearity, and additivity assumptions. This can be useful for applied researchers in various fields.