I would like to collect opinions from the working Bayesians and the theoretical Bayesians on inductive skepticism.

Philosopher Marc Lange gives an overview ([pdf](http://stephanhartmann.org/HHL10_Lange.pdf)) of the debate on Hume's Problem of induction. Chapter 9 (starting on p. 80) is called "Bayesian approaches". I understand it as: the justification for induction might be updating believes from a Bayesian point of view. Lange continues with a fictional dialogue between a Bayesian (B) and an inductive skeptic (S). I summarize:

> B: if you admit Bayesian approaches are valid, what kind of prior do
> you suggest, which fundamentally makes updating believes a
> non-justification of induction.
> 
> S: any distribution with "no degree of confidence to which we are
> entitled regarding predictions regarding unexamined cases" (Lange),
> where "no degree of confidence" does not mean the value zero but no
> value at all [e.g. a NULL in the R language].
> 
> B: this prior violates probability axioms - it is not a distribution
> [and not implementable in R either].

What are your opinions on the last claim in the given context? 

Can the skeptic S consistently defend her skeptical position still including the acceptance of Bayesian techniques by her construction of a prior distribution? 

Alternatively: any opinions about me misinterpreting Lange's paper?