This probabilistic understanding of risk and safety has a
substantial justification in the Bayesian framework [15]. In
the Bayesian decision theory, probability (in combination
with a notion of utility) is conceived of as representing all
aspects of a decision-maker’s lack of knowledge [16–19].
On a Bayesian construal, all (rational) decisions are fully
representable with precise probabilities, since the rational
decision-maker always, at least implicitly, assigns a
probability value to each potential outcome. Faced with
new information, the agent may change her probability
assessment (in accordance with Bayes’ theorem), but she
always assigns determinable probabilities to all states of
affairs. Thus, in the Bayesian view all uncertainty about
what will happen is codified in the probability assessment