You cannot expect that future evidence will sway you in a particular direction. “For every expectation of evidence, there is an equal and opposite expectation of counterevidence.”
The (related) way I would expand this is “if you know what you will believe in the future, then you ought to believe that now.”
Here’s a short and incomplete list of habits I would include in qualitative Bayes:
Base rate attention.
Consider alternative hypotheses.
Compare hypotheses by likelihood ratios, not likelihoods.
Search for experiments with high information content (measured by likelihood ratio) and low cost.
Conservation of evidence.
Competing values should have some tradeoff between them.
Each one of those is a full post to explain, I think. I also think they’re strongly reinforcing; 3 and 4 are listed as separate insights, here, but I don’t think one is very useful without the other.
Another useful thing for qualitative Bayes from Jaynes—always include a background information I in the list of information you’re conditioning on. It reminds you that your estimates are fully contextual on all your knowledge, most of which is unstated and unexamined.
Actually, this seems like a General Semantics meets Bayes kind of principle. Surely Korzybski had a catchy phrase for a similar idea. Anyone got one?
Actually, this seems like a General Semantics meets Bayes kind of principle. Surely Korzybski had a catchy phrase for a similar idea. Can anyone got one?
Korzybski did “turgid” rather than “catchy”, but this seems closely related to his insistence that characteristics are always left out by the process of abstraction, and that one can never know “all” about something. Hence his habitual use of “etc.”, to the degree that he invented abbreviations for it.
The (related) way I would expand this is “if you know what you will believe in the future, then you ought to believe that now.”
Quoting myself from Yvain’s blog:
Another useful thing for qualitative Bayes from Jaynes—always include a background information I in the list of information you’re conditioning on. It reminds you that your estimates are fully contextual on all your knowledge, most of which is unstated and unexamined.
Actually, this seems like a General Semantics meets Bayes kind of principle. Surely Korzybski had a catchy phrase for a similar idea. Anyone got one?
Korzybski did “turgid” rather than “catchy”, but this seems closely related to his insistence that characteristics are always left out by the process of abstraction, and that one can never know “all” about something. Hence his habitual use of “etc.”, to the degree that he invented abbreviations for it.