Scientific knowledge grows through cycles of conjecture and criticism. But in his recent piece, Hypothesis Retrofitting, Dr. Frezza warns us that big data and AI are disrupting this cycle, pulling science firmly toward data collection and away from hypothesis generation. The end result is scientific papers brimming with data yet

A video recently circulated on X in which François Jacob said non-hypothesis-driven research is "very boring". 😯 François Jacob (co-discoverer of gene regulation) asked by Lucy Shapiro (Stanford): "It's always been hypothesis-driven research [..] but a new way is looking at vast amounts of data and not asking a question, just seeing

Models are constructs of reality. They condense knowledge in order to help us understand reality and support our ideas. One way that we can test the validity of a model is to perform an experiment. For instance, if a model accurately predicts an experiment outcome, it is verified. But if

Scientific experiments help us learn more about reality. The design and interpretation of experiments is guided by specific frameworks, each with its own underlying philosophy. But most scientists aren't taught this. It's vital we understand experimental frameworks so that we can be truly aligned with knowledge growth. Here, I'll cover