How Skeptics Can Prove Bigfoot is Unlikely, But Don’t

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Skeptics like to say that they cannot disprove the existence of Bigfoot and leverage this as justification for saying it doesn’t exist in absence of a body. But this isn’t totally true. 

To understand this issue you first have to understand error in science. Even scientific laws can be wrong, although the chances are very small. Theories are more likely to be incorrect than laws but less likely to be incorrect when compared to hypotheses. Science actively recognizes that it’s own findings can be wrong and as research continues, findings can become more or less likely to be true. Nothing in science is 100% certain. 

The argument that the existence of Bigfoot cannot be disproven is often told in this fashion: If I go to a lake and see only white swans I could say that only white Swans exist, but it would only take a single black Swan to invalidate my statement. Unless I counted every single Swan and found no Black ones I could not possibly know black Swans do not exist. 

And this is a correct statement, but it misses a key point – deduction. Science often involves making educated leaps or at least steps. That’s what testing is for and that’s why nothing in science is set in stone. 

Let’s go back to our Swan example. For the sake of simplicity we’ll say the total population of Swans in existence is 1,000,000. Finding every single Swan to see if there are any black ones would be a big task and is not very realistic. If we look at 10 Swans and find no black Swans we wouldn’t have much confidence in the statement no black Swans exist since we haven’t looked at very many Swans. But if we increase our search to 10,000 Swans and still find no black Swans the idea that black Swans don’t exist seems more likely. Now we cannot conclude definitively that Black Swans don’t exist but we can say we believe it is unlikely black Swans exist. This is a perfectly reasonable statement based on the observations. 

Let’s apply this to Bigfoot. Now I know the title of this article is about disproving the existence of Bigfoot which is still impossible with 100% certainty, but maybe not with 70% certainty, or 80% certainty. After all we have decades of collected tracks, photos and videos. All a skeptic would have to do is analyze a large sample of this evidence and prove that these were due to hoaxes or misidentification. And of course some evidence like blurry photos would remain inconclusive. If that skeptic could show that the vast majority of the evidence could be reasonably attributed to natural phenomena we could say it is unlikely Bigfoot exists. And that would be logical. We are not saying he doesn’t exist, instead we are simply saying given the existing evidence it is unlikely he exists. But no skeptic has done this and the notion that Bigfoot doesn’t exist swirls in skeptical circles. In fact many in the skeptical community label anyone who believes or even entertains the possibility of Bigfoot as loony or a moron. 

I find it strange, almost paranormal, that scientists who work with this uncertainty daily stick to the line that Bigfoot cannot be disproven. It seems like this is an excuse for lazy science: This is a way to dodge the burden of actually investigating paranormal claims to determine if these phenomena truly have a natural cause. It is much easier to write articles and books from an armchair. Plus there is no risk of proving yourself wrong if you never really investigate the claims. 

The root of the problem is in the way unknowns are handled. When a believer sees a light in the sky and doesn’t know what it is they say its aliens. I’m generalizing here. A skeptic looks at the same light in the sky, can’t determine a cause and says it’s natural. Meanwhile the objective investigator sees the light, cannot determine a cause, and labels it unknown. It seems like an easy choice to use objectivism to investigate unknowns yet so many in the world of the paranormal stick with these flawed thought processes. Maybe it just easier to believe or disbelieve than to remain in wonder. Ultimately following the evidence is the best path to truth, not preconceived biases or over-reliance on existing knowledge without respect for error. 

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