This is a fantastic moderated conversation between Eugene Fama and Richard Thaler on the question of "Are Markets Efficient?"
While it is fashionable to bash the efficient market hypothesis (EMH) these days, the wonderful discussion highlights many of the nuances.
Fama posits that the EMH is a useful model, even if it is not perfectly true all the time. Pointing out occasional anomalies doesn't invalidate the model. Furthermore, one has to be careful about hindsight bias (bubbles for example) before rejecting the EMH.
It should be understood that the EMH is not a deterministic model in the same sense as physical laws or models (example: Newton's laws of motion). Instead, it bears resemblance to probabilistic or statistical models (example: weather models).
A single anomaly can completely reject a deterministic model.
If a model says "A implies B", and you find a counter-example, where "A does not imply B", then you have to reject or amend the model "A implies B".
A real example might be the belief that heavy objects fall faster than lighter objects (in the absence of air resistance). A single example (or thought experiment) is enough to destroy the model.
On the other hand, anomalies don't necessarily eliminate probabilistic models.
Consider a model that says "A often implies B", such as "cigarette smoking often implies lung cancer". You find someone who smoked a pack everyday and lived to 90. That example is treated as an anomaly, or "the exception that proves the rule".
EMH, perhaps, belongs to the second group.
If you think like a Bayesian, your belief in the model should decrease as the evidence against the model begins piling up.