This post is a guest contribution by Dr. Prosanta Chakrabarty, Assistant Professor/Curator of Fishes at Louisiana State University. Prosanta studies the systematics and evolution of both marine and freshwater fishes worldwide. His research has been featured in Science, NPR and the BBC. You can follow him on Twitter.
We live in a rapidly changing world. There is a great deal of information available to us, most of it at our fingertips through computers, smartphones and the like. It is easy to think that having the internet at our reach means that we are all on an equal playing field in terms of knowledge: everything we don’t know we can find the answer to with a quick Google search. I’ve written this post because I think this view is flawed.
It may be true that we can find a great many answers on the internet, the problem is that there are many wrong answers out there as well (Fig. 1). Knowing right from wrong has never been harder. Thinking like a scientist is the best way to sort through the mess.
So how does a scientist think? As a scientist I should know better than to speak for all scientists, but I’m going to do so anyway. When presented with a problem a scientist attempts to solve it without bias. (Although we may want a certain outcome, influencing a test or experiment to get that result is not science.) One common way scientists tackle a problem is through falsification (also called the hypothetico-deductive method). Using falsification, we construct hypotheses and conduct tests that are capable, in theory, of proving those hypotheses are incorrect. (Hypotheses are essentially answers to a question.) Following those tests, the hypothesis that is not falsified lives to fight another day but we can soundly reject the one that was demonstrated false. The next time we can refine the hypotheses and make the tests stricter. Will we then find the truth? Potentially. The truth is out there but we will never know for sure if we’ve found it. Truth, is unknowable. All we have done through falsification is proven what isn’t true, or at least, what is least true.