a theory though may or may not predict something and yet still have scientific value in that it can still provide understanding.
I don't dispute the value of a model that doesn't provide testable observables, what I dispute is the notion that science requires prediction for model validation is only someone's opinion. This is not an opinion, this is a fact. A model can be preferred over another because of pragmatic, aesthetic, explanatory, or other epistemological or logical reasons, however prediction and observation are the key centerholds of validating a model.
Scientists can still praise a model that doesn't provide observables if there is mathematical, logical, epistemological, aesthetic, etc basis to do so, however these features of a theory of themselves do not entail a successful theory. Successful theories are driven by observables. This, I think, is the nature of science and which is why the Nobel Prize is handed out only for those models meeting this empirical criteria.
Dick's model does not provide these predictive characteristics and therefore holds little value. Not to mention, it is poorly framed as a philosophical solution to Hume's problem of induction, and therefore I see no reason for anyone to consider it further.
Hawking Quote: The loss of particles and information down black holes meant that the particles that came out were random. One could calculate probabilities, but one could not make any definite predictions. Thus, the future of the universe is not completely determined by the laws of science, and its present state, as Laplace thought. God still has a few tricks up his sleeve.
This misapplies the criteria of prediction as being a deterministic criteria. Probablistic phenomena can meet the criteria of prediction as readily as a deterministic phenomena, which has been shown countless times in quantum and statistical physics.