Priors aren't essential in some models when you're looking for an unbiased estimator and you have a complete, sufficient statistic. Please don't ask me to tell you when that will happen.

Utility functions are necessary if you want to make a decision based off your knowledge. If your goal is simply to state "given model M, parameter A most likely takes this value based on experimental data" then you don't need a utility function.

I think hessenwolf's point is that priors and utility functions are both largely unconstrained functions over the state space of parameters that need to be specified based on the experimenter/reviewer/reader's beliefs and values (respectively). Formulating them and making everybody happy is still an open research topic.

Yes, that was my point. :-))