I was thinking about ID as an inference from data ( not as a Scientific hypothesis or theory) and wondering whether the design inference can be presented in Bayesian terms. On googling it i found an article that does just that. It seems to address all the issues connected to a design inference. The equation and definition of terms are as below-
H : the organism was designed by an intelligent creator
E : the organism looks like it was designed by an intelligent creator
E|H : if the organism was ID’d, the plausibility it looks ID’d.
E|~H : if the organism was not ID’d (e.g. it evolved), the plausibility it looks ID’d.
There is even a table showing how assigning different probabilities to different beliefs does to the final inference.
Now the question is, what is the impact of MN on P(H) and P(~H). It seems MN automatically ascribes a low value to P(H) and a high value to P(~H).
Link to the article : a bayesian analysis of intelligent design | AI and Social Science – Brendan O'Connor