Accepting “I Don’t Know” As An Answer

There is something that all of us do if we aren’t careful, mostly stemming from a deep discomfort of not having an immediate explanation or answer to something we want to know, but don’t – the argument from ignorance – a fallacy of thought by which we draw a conclusion not from data, but from a lack of data, from what we don’t know, a conclusion which more often than not turns out to be false when properly investigated.

One of the first things I had to learn as a skeptic was a tolerance for ambiguity, habits of thought by which I could say to myself “It’s okay to not have an answer for such-and-such a question right now.” It’s perfectly fine to say, “I don’t know…yet.”

There’s a great many people who are just terrified by the thought of not knowing everything with conclusive surety, even when that conclusiveness is wrong. So many people go to great lengths to convince themselves that they do, in fact, know what that strange light in the sky is, or what that creaking noise in the house late at night is, when they really don’t.

This is particularly true of those with a tendency to claim an event as being impossible to explain by natural or normal causes, and thus dismissing such causes prematurely, especially that dual bugaboo of paranormal and fringe-science advocates, coincidence and statistical noise.

A common argument is stated something like “X is so unlikely as to not possibly be due to the laws of chance(or nature)!”(read; the claimant’s understanding of those laws). In fact, it would be even more improbable that unusual coincidences don’t occur as often as they do, in accordance with the Law of Truly Large Numbers. For example, in a city of say, ten million people, with a daily frequency of at least one one-in-million event, one should by chance alone expect ten of these to happen each day.

This and other seemingly counterintuitive results of statistics are well within the bounds of the laws of chance, with no need to invoke anything paranormal. Not yet.

Statistical correlation does not by necessity imply causation, nor scientific importance. For example, if I wanted to and was willing to juggle the numbers, I could draw a correlation between someone’s eye color and their IQ, but there would be no causative or scientific significance to it.

Yes, it’s tempting to think you have all the answers at your fingertips, but the I think that the best knowledge anybody can have is an awareness of their own ignorance and the admission that they, like anyone else, can be mistaken in their conclusions when shown evidence to that effect.

In my experience, I haven’t noticed any tendency to jump to conclusions in lieu of evidence in the more seasoned and better-known skeptics, though I have found it among some novice skeptics and many of the paranormalists I’ve met.

It’s the same whether we try to definitively explain a strange light in the moors as either a ghost or as swamp-gas without enough information – we are committing the same error either way.

Probabilistic, uncertain thinking and a tolerance for it can be difficult at first, but it gets easier with time and practice, becoming second nature. One can only learn when no longer convinced that one already knows without sound reason to think so. It’s how good science is done.

A wise man knows his own ignorance, while a fool knows everything.