But Don't Rule Out Malice

Via- American Thinker

By Ryan Scott Welch

There is an adage that reads "never attribute to malice that which can be adequately explained by stupidity... but don't rule out malice." This is known as Heinlein's or Hanlon's Razor (there is only a slight difference between the two). Unfortunately many people only go by the first part of Heinlein's Razor, leaving out the "but don't rule out malice" part. People using this heuristic decision-making shortcut often think that even though some things that people do seem very suspect, and even though mental red flags are going up and instinctive alarms are sounding, that there must be some explanation, other than malice, to explain the actions of people. This is especially true when the suspicious people are connected to them is some way like family, friends, or even the politicians that they support. Many people using Heinlein's Razor shrug off these suspicious actions as if they were just a mistake, or maybe the actions that people did were the result of "bad luck", or possibly that ignorance can explain why they made those decisions. But I would like to focus on the second part of Heinlein's Razor which of course is: but don't rule out malice.

Sometimes, some people actually act out of malice. Malicious people do exist in the world and always have, as far back as the beginning of recorded human history. It is easily possible that you know, or know of, some malicious people. They could be your acquaintances or friends; they could even be in your family, and yes, they might be one or more of your political leaders. In support of the second part of Heinlein's Razor there's another adage called Occam's razor that says among competing hypotheses, the one that makes the fewest assumptions should be selected -- the simpler the explanation, the more likely it is to be true, everything else being equal. If you have to mentally jump through a lot of hoops to explain how someone's motive cannot be malice then Occam's Razor says that the more assumptions you need to make the less likely that your hypothesis is true.


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