Khross wrote:
Experts in the field disagree; consequently, RangerDave, any Appeal to Expertise on AIGW is an Appeal to Authority as well.
Not to mention the circle-jerk of what it takes to be considered an a climate expert these days. Not agreeing with the AIGW theory disqualifies you from becoming a climate expert. So even if there is a consensus among climate experts, it signifies precisely nothing other than selection bias.
RangerDave wrote:
Sure, but "Jim is an automotive expert; therefore his analysis of a highly technical issue related to cars is much more likely to be true than is the analysis of someone who is not an automotive expert" is not a fallacy. Nor is "Bob is not an automotive expert; therefore his analysis of a highly technical issue related to cars probably isn't very reliable."
There's two problems with this:
1) That depends entirely on whether the
Bayesian interpretation of probability is valid. Which is...less than clear.
And even if Bayesian theory is "right", it (like all conditional probabilities) breaks down if you gain or lose information. That is, the probability that a fair six-sided die will roll < 3 is 1/3. However, once the die has been cast, the probability is no longer 1/3, but strictly either 0 or 1 (100%). In the same way, it might be true that Bob is less likely to make a correct theory than an automotive expert, but as soon as Bob actually makes a theory, the probability is now entirely up to the information of the theory. It's not unlike quantum superpositions collapsing upon observation.
2) Even with respect to unknown theories, the validity of your Bayesian analysis depends entirely on how you've defined your "cookie jars". That is, it's only correct if the group you've defined as "experts"
really have generated correct theories more often than the group you've defined as "not experts". Anyone who's ever set up Bayesian spam filter knows exactly what I'm talking about. Without good, accurate SPAM and HAM sources to train it on, the filter is useless and its probabilities are meaningless. Before your statements have any validity even within the Bayesian model, you need to: A) define precisely what qualifies an individual as an expert in the field, and B) quantify the frequency of correct theories by the group so defined.