Chris Nolan's Joker is a very clever guy, almost Monroesque in his ability to identify hypocrisy and inconsistency. One of his most interesting scenes in the film has him point out how people estimate horrible things differently depending on whether they're part of what's "normal", what's "expected", rather than on how inherently horrifying they are, or how many people are involved.
Soon people extrapolated this observation to other such apparent inconsistencies in human judgment, where a behaviour that once was acceptable, with a simple tweak or change in context, becomes the subject of a much more serious reaction.
I think there's rationalist merit in giving these inconsistencies a serious look. I intuit that there's some sort of underlying pattern to them, something that makes psychological sense, in the roundabout way that most irrational things do. I think that much good could come out of figuring out what that root cause is, and how to predict this effect and manage it.
Phenomena that come to mind, are, for instance, from an Effective Altruism point of view, the expenses incurred in counter-terrorism (including some wars that were very expensive in treasure and lives), and the number of lives said expenses save, compared with the number of lives that could be saved by spending that same amount into improving road safety, increasing public helathcare expense where it would do the most good, building better lightning rods (in the USA you're four times more likely to be struck by thunder than by terrorists), or legalizing drugs.
What do y'all think? Why do people have their priorities all jumbled-up? How can we predict these effects? How can we work around them?
During the initial coverage of the ebola outbreak, there were several comparisons to the malaria death toll, with the conclusion that paying so much attention to the (much, much smaller) death toll from ebola was irrational. This was wrong, because the ebola outbreak was undergoing exponential growth, and so the early death toll had huge importance as evidence about the long-term growth rate, and because arresting the exponential process in the early stages might be very cost effective. At the time, there were credible predictions that we might see 1.5 million cases in a relatively small region (with perhaps .75 million deaths), compared to a rate of 0.5 million global deaths from malaria. Thankfully, these predictions now look unlikely, but it is very much rational to care about possible early evidence for something that might be on track for substantial growth.