Three definitional assumptions:
E is only evidence if there is some hypothesis H to which E makes an evidential difference, i.e., P(H|E)≠P(H).
E is incomplete if and only if it is evidence such that there is a hypothesis H such that 0 < P(H|E)<1, i.e., E doesn’t make everything certain.
E is misleading with respect to a hypothesis H if and only if either H is true and E is evidence against H (i.e., P(H|E)<P(H)) or H is false and E is evidence for H (i.e., P(H|E)>P(H)).
Then:
- Every piece of incomplete evidence is misleading (with respect to some hypothesis).
[Proof: Suppose E is incomplete evidence. Either E is or is not true. If it is not true, it is misleading, since it lowers its own probability to zero. So, suppose that E is true. Let H1 be a hypothesis such that 0 < P(H1|E)<1. Replacing H1 by its negation if necessary, we can assume H1 is true. Note that the fact that E is evidence implies that 0 < P(E)<1. Let H be the disjunctive hypothesis: ∼E or (H1&E). This is true as the second disjunct is true. Now, note that P(H1&E)<P(E) as P(H1|E)<1. Thus, (1 − P(E))P(H1&E)<(1 − P(E))P(E). Thus, P(H1&E)<P(E)P(H1&E)+(1 − P(E))P(E). Thus: P(H1|E)=P(H1&E)/P(E)<P(H1&E)+(1 − P(E)) = P(H1&E)+P(∼E)=P(H). Thus, E is evidence against H even though H is true.]
In particular, we should not take misleadingness of evidence to be an evil. Misleadingness of evidence is a normal part of reasoning with incomplete information.
Blind men and an elephant.
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ReplyDeleteInteresting. But there are two typos, and it was difficult to follow the proof's logic regardless. The evidential difference condition should read "P(H|E)≠P(H)," not "P(H|E)≠P(E)," and conditional probability means "P(H1|E)=P(H1&E)/P(E)" and not "P(H1|E)=P(H1&E)P(E)."
ReplyDeleteFeryll:
ReplyDeleteIt was worse than that: most of the proof was wrong. I revised it. Is it better?