Kuhn’s view is that during normal science scientists neither test nor seek to confirm the guiding theories of their disciplinary matrix. Nor do they regard anomalous results as falsifying those theories. (It is only speculative puzzle-solutions that can be falsified in a Popperian fashion during normal science (1970b, 19).) Rather, anomalies are ignored or explained away if at all possible. It is only the accumulation of particularly troublesome anomalies that poses a serious problem for the existing disciplinary matrix. A particularly troublesome anomaly is one that undermines the practice of normal science. For example, an anomaly might reveal inadequacies in some commonly used piece of equipment, perhaps by casting doubt on the underlying theory. If much of normal science relies upon this piece of equipment, normal science will find it difficult to continue with confidence until this anomaly is addressed. A widespread failure in such confidence Kuhn calls a ‘crisis’
Under this view, perhaps a certain set of interpretability techniques might emerge under a paradigm that makes certain assumptions (eg, that ML kernals are “mostly” linear, that systems are “mostly” stateless, that exotic hacks of the underlying hardware aren’t in play, etc). If a series of anomalies were to accumulate that couldn’t be explained within this matrix, you might expect to see a new paradigm needed.
Under this view, perhaps a certain set of interpretability techniques might emerge under a paradigm that makes certain assumptions (eg, that ML kernals are “mostly” linear, that systems are “mostly” stateless, that exotic hacks of the underlying hardware aren’t in play, etc). If a series of anomalies were to accumulate that couldn’t be explained within this matrix, you might expect to see a new paradigm needed.