Potential Pitfalls in Research
From active scientific research to its end goal which is a peer-reviewed publication, one needs to ensure that all scientific endeavor require the utmost care in maintaining a distance from all sorts of biases and false assumptions. There are 12 cognitive biases and 24 logical fallacies that the human mind is inclined to fall into. If unaware, a scientist may fall prey to one of these and may draw false conclusions from the data from their scientific experiments. Needless to say, that such an incident may have drastic consequences especially in the field of space exploration, health science, information technology.
One such logical fallacy is called the “black-or-white.” In my personal experience, I have seen various scientific publications in which when a possible reason for a particular observation is proven wrong, its contrary is held to be the truth. Often times a third possibility/reason could be at play. This is particularly true for natural systems that are used in the life sciences sector. Another logical fallacy that is particularly pernicious is called “appeal to authority.” Many a times the pioneers of a particular field subscribe to a particular line of thought, only based on experience without any proof, which is then held to be universally true. Derivations based on the factual nature of an unproven theory like that may lead one to draw false conclusions.
A cognitive bias that may creep into scientific research is called “confirmation bias.” This kind of bias may involve a scientist referring to only those data and publications that help confirm their own findings and theories. Such a bias shows its ugly head in the current scientific funding processes as well. Scientists who are reviewing their peer’s funding applications may be more inclined to grant those to peers who align with their scientific thinking. This is a symptom of the human condition which derives legitimacy based on conformity to a group. Perhaps one of the most prolific cognitive bias amongst scientists is the “observational selection bias.” Scientific research is strongly hypothesis driven. In framing a hypothesis, one may easily slip into observational bias. This entails that a scientist may make those observations that they are trying to prove. These logical fallacies and cognitive biases are some of the pitfalls that scientists may encounter.