Fighting hypothesis myopia

Irreproducibility downright scares me. When I decided to embark on this journey as a scientist, I thought I knew what I was getting into, but having come across the need to reproduce results in science, I realize that there’s sides to this I never considered. I’ve always been afraid of failure, and whether that comes in the form of my work not reproducing expected results or my work not being able to be reproduced by others because of mistakes I’ve made, I know that I will encounter “failure” frequently in this line of work. Much of this fright comes from not being able to step away from the notion that a failed replication does not equal scientific failure. Jeff Leek’s article relaxed me, mainly because it reminded me that success in science comes in many flavors, not just successful replication. He summarizes it well when he states that failure to replicate could stem from an “unusual event” or other “unmodeled confounders”. I know that I am human, and I will make mistakes, but all I can do is focus on my skills and ensure that my procedures are rigorous and my reports are authentic. I should listen to Claude Levi Strauss, who once said “A scientist is not a person who gives the right answers, but one who asks the right questions.”

The biggest trap that could lead to irreproducible studies is this so-called “hypothesis myopia”, of which I will admit, I have been and possibly still am guilty. The basis of this cognitive fallacy is the fixation and falling in love with a single hypothesis but failing to try to disprove it. Any finding coming as a result of hypothesis myopia could completely distort the way in which we see the world, by making us focus on what we wish the data to be instead of what the data truly show. The solution, as Regina Nuzzo so eloquently phrased it in her nature article, is to counter biases, which act like an accelerator in the world of science, by pumping the brakes and slowing down to be more skeptical of findings. We must fight hypothesis myopia with further testing, and remember the words of Adam Savage at the San Francisco March for Science last year, “Bias is the enemy of science, but science is also the enemy of bias.”