Studiot said:
Take for instance limit state design.
Or bridge strength assessment.
Or diversity as applied to electrical installation design
Or the error term as applied to many mathematical calculations.
You state that single event probability is either 1 or zero.
In the case of my bridge example this implies that a bridge either collapses or it doesn't.
In reality the bridge may suffer a partial collapse, indeed some bridges may suffer a small partial collapse (=degradation) on every use until finally that last straw walks over it.
I have been doing a lot of practical work in uncertainty analysis (including FORM, SORM and various other engineering techniques). I even did research in advanced methods of uncertainty estimation in complex settings; see
http://arnold-neumaier.at/clouds.html
Thus I make my assertions based on thorough and quite diverse experience.
Predicting a partial collapse is different from predicting a probability of collapse.
The correct modeling would try predict the expected amount of collapse or degradation, not a probability of collapse. Bringing this into play only confuses issues, and I'll disregard it in the following.
Saying that there is a 60% chance that it will rain tomorrow may sound like a probability statement about the single event tomorrow, but it isn't - this statement cannot be verified, whether or not it actually rains, and hence is empty. Instead it is a statement about the known preconditions of the weather tomorrow - namely that they belong to an ensemble described by a stochastic model in which the probability of raining is 60%.
Essentially the same holds for all other of the many engineering uses of probability I have met during my career.
A lot of knowledge (but also prejudice, or more or less justified assumptions) goes into the creation of an appropriate stochastic model for defining the ensemble. In this (and only this) sense, probabilities are knowledge-dependent. But this knowledge-dependence is of the same character as that of anything we say or believe, and hence is not something worth emphasizing.
On the other hand, once the ensemble is fixed, probabilites are objective. Of course, the language assigns probabilities to single events, but (as in the case of tomorrow's weather), these are not properties of these events but of an associated theoretical ensemble chosen
such that averaged over many actual events the predictions are maximally useful.
Thus if two people assign different probabilities to the same event, it means that they have different ensembles in mind for modeling the same situation.
Now suppose that we have a real ensemble, such as whether or not it rains at Vienna airport each day of the next two years, or whether or not some of the bridges in Europe crash in the next two years Then there are objective probabilities associated with them, namely the relative frequencies of the actual events. Again, these are completely independent of the knowledge of any observer or analyst. They are unknown now, but can be determiend in two years time, hence they are objective.
On the other hand, the probabilities we assign to them based on a particular model for predictions are approximations, whose quality depends on the knowledge (but also prejudice, or more or less justified assumptions) of the modeler.
But again, this is nothing surprising, and nothing special for probabilities - the quality of the _description_ of any property of anything depends on the describer's knowledge, although the properties themselves are objectively fixed (if they deserve the name ''property'').
Thus knowledge plays in probability no role different from that it plays everywhere - at least not in those aspects of probability that can be checked in reality.
Subjective probability are a different matter. They are not verifiable or falsifiable, hence do not fall under the above analysis. But because of that, they should have no place in science or engineering.