Must a theory be falsifiable to contribute to good science?
Falsifiability is considered by some to be the cornerstone of any scientifically sound theory. Indeed, certain schools of thought within the philosophy of science label theories that are not falsifiable as “pseudoscience.” But is the falsifiability, or testability, of a theory actually crucial for good science? Or can non-testable theories still help drive progress?
Neuroscience is a relatively young scientific endeavor, so we may benefit from more unconstrained exploration of ideas and theories. Making room for non-testable theories may help expand the space of ideas in neuroscience and provide footholds to grapple with increasingly large and complex datasets. Also, given that non-testable theories already pepper the field of neuroscience, it is important to explore the role they are playing and how well suited they are for it.
To dig into these issues, I moderated a week-long conversation with three researchers—David Barack, Cian O’Donnell and Stephanie Palmer—over Slack to try to define what qualifies as “non-testable” and what traits such theories tend to have. We describe specific examples from neuroscience, with an emphasis on normative approaches. We also discuss challenges in assessing the quality of non-testable theories, and the role they play in inspiring testable predictions. By the end, we reconsider referring to these ideas as “theories” at all, opting for “frameworks” instead.
