It is a part of difficulty to subvert - it is difficult to arrange a scheme with positive expected utility for falsifying data.
Given that one gets fame for "spectacular" discoveries, not at all especially in fields like biology where there are frequently lots of confounding variables that you can use to provide cover.
That has always been the problem with experimental science, sometimes you can't really protect from falsification.
Actually, thing is, given the list of biases, one shouldn't trust one's own rationality, let alone rationality of other people (If a rationalist trusts his own rationality while knowing of biases... that's just a new kind of irrationalist). Other issue is that introduction of novel hypotheses with 'correct priors' allows to introduce a cherry picked selection of hypotheses that would lead to a new hypothesis with undue confidence that wouldn't ...
Today's post, Science Doesn't Trust Your Rationality was originally published on 14 May 2008. A summary (taken from the LW wiki):
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