adding to what Raza said - a consideration for both active learning and weak supervision is the need to construct a gold standard labelled dataset for model validation and testing purposes. At Humanloop, in addition to collecting training data, we are also using a form of active learning to speed up the collection of an unbiased test data set.
Another consideration on the weak supervision side (for the snorkel style approach of labelling functions) is that creating labelling functions can be a relatively technical task, which may not be well suited for non-technical domain expert annotators for providing feedback to the model
Another consideration on the weak supervision side (for the snorkel style approach of labelling functions) is that creating labelling functions can be a relatively technical task, which may not be well suited for non-technical domain expert annotators for providing feedback to the model