The most common approaches to detection and attribution (D&A) of extreme weather events using fraction of attributable risk or risk ratio answer a particular form of research question, namely “What is the probability of a certain class of weather events, given global climate change, relative to a world without?” In a set of recent papers, Trenberth et al. (2015, https://doi.org/10.1038/nclimate2657 ) and Shepherd (2016, https://doi.org/10.1007/s40641‐016‐0033‐y ) have argued that this is not always the best tool for analyzing causes, or for communicating with the public about climate events and extremes. Instead, they promote the idea of a “storyline” approach, which asks complementary questions, such as “How much did climate change affect the severity of a given storm?” From the vantage of history and philosophy of science, a proposal to introduce a new approach or to answer different research questions—especially those of public interest—does not appear particularly controversial. However, the proposal proved highly controversial, with the majority of D&A scientists reacting in a very negative and even personal manner. Some suggested the proposed alternatives amount to a weakening of standards, or an abandonment of scientific method. Here, we address the question: Why is this such a controversial proposition? We argue that there is no “right” or “wrong” approach to D&A in any absolute sense, but rather that in different contexts, society may have a greater or lesser concern with errors of a particular type. How we view the relative risk of overestimation versus underestimation of harm is context‐dependent.