"Let S be the proposition that human moral experiences are a product of subjective values functions, and that those value functions are informed primarily by socialization and evolutionary history.The analysis appears to be a partial Bayesian induction, which doesn't go as far as the final calculation. It's just inductive, to the point of weighting, and it's not related to Kolmogorov algorithmic probability in any way. Its premises can be analyzed for any truth value which might inhere. As in any logical conclusions, including inductive of course, if the premises are not valid, true, and grounded in first principles, then they are false. That is the standard of Aristotlelian logic – college logic 101 – and it is the logic used here to analyze the probability claims. This is a failure of Bayes usage: besides being prone to prejudicial misuse, when used for metaphysical claims or unfalsifiable claims, it provides only highly dubious probability at best. It is incapable of objective fact generation, even using empirically derived probabilities. It is incapable of the capacity of deduction's ability to provide unquestionable truth when done properly.
Let O be the proposition that human moral experiences are a product of some apprehension of objective moral values.
Let V be the observation that human moral opinions vary from person to person.
Let C be the observation that human moral opinions tend to vary more between cultures than between individuals.
P(V|O) < P(V|S) P(C|O) << P(V|S) Further, there does not appear to be any further evidence, E, such that P(E|V) > P(E|S)
Further, O is strictly less parsimonious than S.
Hence, we have strong justification for S over O."
A discussion of Induction via Bayesian assumptions is here, for a refresher (It's embedded in the articles):
The probability argument begins:
The term, “moral experiences” is undefined, and seems to be without any value regarding to the actual objective existence of moral principles. The term “experiences” seems to indicate subjective apprehension in both premises, not objective knowledge of anything. Science, for example, is not done on the basis of “human material experiences”; it is done on the basis of objective experimentation, performable by other experimenters as a test of replicability for validation and non-falsifiability. That’s how objectivity is produced in materialist premises.
"Let S be the proposition that human moral experiences are a product of subjective values functions, and that those value functions are informed primarily by socialization and evolutionary history.
Let O be the proposition that human moral experiences are a product of some apprehension of objective moral values."
So O has no bearing on actual existence of objective morality. Using it for such is false.
"Let V be the observation that human moral opinions vary from person to person.This “observation”, C, is beyond dubious, it is prejudiced and prejudicial for purposes of biasing the faux Bayesian analysis below; it is without any supporting data and is highly likely false purely because there are no Atheist moral principles at all which are derivable from Atheism, beyond those “moral” principles each individual Atheist creates for himself. Therefore, given the number of Atheists on the globe – and counting the communists, secularists, Hindus and Buddhists – the number of dissimilar, individually-derived “moralities” is very likely far higher than the objectively held moralities.
Let C be the observation that human moral opinions tend to vary more between cultures than between individuals."
C is merely a prejudicial opinion, not an objective fact. It has no truth value for use in any calculation.
Now for the relative positioning of the premises.
"P(V|O) < P(V|S)"This is a typical Bayesian Probability set up technique. It uses pure opinion, with no possible actual data to support any validity it might have. Especially given that O does not describe any useful information regarding the actual existence of objective morality.
In this case, the relative positioning of the two probabilities is purely by opinion, not by any objective factual probability calculation. In other words, it is a prejudiced personal projection made toward a presupposed objective. Were any actual facts discovered for use here, the relative positioning would likely be reversed.
"P(C|O) << P(V|S)"This placement of relative probabilities also is based not on any fact or data or study, it is purely based on the presuppositional prejudices of the author. Given that both C and O are personal opinion, and obviously prejudicial, there is precisely no actual rational or empirical reason to believe that this is the case.
"Further, there does not appear to be any further evidence, E, such that P(E|V) > P(E|S)"
This is really interesting, given that there is no evidence provided for any of the premises, period. Denial of “further evidence” is in the form of a joke, then.
"Further, O is strictly less parsimonious than S."It is hardly arguable that O is less parsimonious than S; this is a truth claim which has no basis whatsoever for its belief, because O has no actual meaning in the argument. In fact, if parsimony refers to simplicity vs excessive complexity, then O is far MORE parsimonious than S, given the complexity of S. So this is another failure, possibly that of Equivocation of the term, parsimony, but more likely just a blatant biasing of the argument toward the desired conclusion. It is based on no justification of any kind for the declared truth being asserted.
"Hence, we have strong justification for S over O."No, there is absolutely nothing presented here which is anything other than opinion, which is declared to be truth for purposes of biasing “premises” in a phony “probability” calculation. That is not justification, it is propaganda. It is a poor man’s Bayesian exercise, where opinion is plugged in and declared to be factually useful for calculating a probability in the favor of the author.
Bayesian induction is a favorite of individuals who are scamming lesser knowledgeable folks. Bayesian calculations are useful only when prior premises have probabilities which are factually available as empirical determinations (I.e. NOT opinion). One example of successful usage of Bayesian Inference is the Coast Guard’s calculations regarding the probable position of a lost boater, based on prior conditions of wind, currents, tides, time at last known location, and prior routes taken by the boater. These are not opinions, they are facts which can be plugged into the Bayes equation, and the probable current location of the lost boater can then successfully calculated.
Bayesian Induction for metaphysical use is a resort of anti-intellectual scoundrels and scammers.