Modern data science is often exploratory in nature, with hundreds or thousands of hypotheses being regularly tested on scientific datasets. The false discovery rate (FDR) has emerged as a dominant error metric in multiple hypothesis testing over the last two decades. I will argue that both (a) the FDR error metric, as well as (b) the current framework of multiple testing, where the scientist...