Tuesday, February 2, 2016

Is bias a necessary evil?

Biases are ubiquitous. And because they are ubiquitous, we must embrace them for we cannot escape. This is especially true to science. I see biases as vital and necessary components of science. I often see bias portrayed as being bad--rightfully so as bias can really screw us over as portrayed by the articles I read. But from reading these articles, I wanted to find reasons for how bias can be good. Perhaps I am misunderstanding the connotation of the word "bias" or applying the word subjectively? No matter what, here are some reasons why I think bias could be a good thing:

  1. Biases, aka hypotheses, are the impetuses for projects. Scientist must have a central belief, which are biased by our expertise, past life experiences, our colleagues, mentors, and etc, to which we frame our scientific questions. I believe that these biases provides the momentum for the creation of projects and propel discovery. Without our constantly changing biases science would not be in perpetual motion. 
  2. Biases allow us to be more critical, allowing for the advancement of science. We are taught as scientist to always question what we see, what we read, and what we hear. We would not have such critical minds if we did not have a bias that something published is not always true or causative. I think that such skepticism pushes science forward. 
  3. Biases force us to do better science. The point of publishing is share your discoveries with supportive evidences that try to minimize biases. Because we have these biases and want our results to be as objective as possible, we design "controlled" experiments. Thus, bias forces us perform scientifically valid experiments and analyze data that can best confirm our hypotheses.

Here are my thoughts on how bias is a necessary evil in science. Without them it may be hard to pose a scientific question, make it impossible to be more critical, and most importantly, perform and analyze truly honest and objective experiments. Since there are many examples of how bias can be detrimental to science, I just wanted to be a devil's advocate and provide some reflections about how bias can actually be good for science.


  1. I think this is a nice, positive spin on the word "bias," however, I think in the process, you conflate bias with a slew of terms it never is supposedly to work with, just by pure definition.

    Your first point is interesting, and holds some truth to it. Yes, scientists must have past experiences to frame their scientific thought -- but if we are to believe in natural laws of the universe and these past experience have revealed those truths, then describing them as "biases" actually makes them sound subjective. These are objective truths! Now, I think it would be more understandable if you said that biases aligned with schools of thought or debating theories, I would agree with that.

    Are biases really similar to the proclivity to be critical? No, I'd also disagree with this. In fact, I'd say that biases are the exact opposite of being critical. Biases represent a "stuck"-ness about them. The inability to move and it affecting how we think and see the world; most specifically how we see the objective truths we may have revealed previously.

    Finally, I think your definition of bias is applied too broadly. I get where you are coming from, but I do not think it lines up with how we traditionally learn about bias. Maybe this is my own intellectual shortcoming, but it sounds like you demand a redefinition of the word, not an examination of bias that is already inherent.

  2. Upon reading the title to this post, I thought "Bias is bad, not a necessary evil." But I am glad I read the rest of the post, because you do bring up many points that I do agree with. First, for reference I looked up the term being discussed.

    Bias: (n) a particular tendency, trend, inclination, feeling, or opinion, especially one that is preconceived or unreasonable. (From dictionary.com)

    Addressing the first point: A scientist will often having a feeling or inclination about what it happening to a system in an experiment. They will then systematically test these hypothesizes to discover the truth. Sometimes, depending on who you speak to, these preconceived hypothesis my even seen unreasonable to people. One could say that these hypothesis started out as a biased opinion about the underlying mechanisms of an observation.

    I don’t think biases allow us to be more critical of our experiments. Bias alone can have a harsh effect on results, but recognizing bias may help us avoid these misleading effects by allowing us to design properly randomized and/or blinded experiments.

    The last point seems to relate back to the first two points. By recognizing our own initial bias going into experiments and eliminating possible ways that our experiments may bias certain results, we are able to get at the underlying truth. Getting at the underlying truth is what science is really about. Having biased experiments is not good, but developing hypothesis and recognizing sources of bias are essential for good science.

  3. What really speaks to me from your post is the fact that bias helps to propel our standards of scientific research and questioning. Our rigor to control for bias is what leads to good science...if everyone just ignored bias, then the scientific community would be even more saturated with science and it'd be difficult (more so than it is currently) to sort through what is the "truth".
    Another point in how bias may be a "positive" is in terms of graduate school education. I think learning how to be critical and think about controls and bias is one of the most important skills that we learn as graduate students. Without having this background and understanding of bias, there is no way we can be the successful scientists that we all are striving to be. Sure, we come here to learn experimental protocols, but the true key to a successful PhD is understanding thorough experimental design. Though we can't avoid bias, bias helps to serve as the foundation for graduate school.

  4. Danny, you present a very interesting angle on bias here. Especially the commentary on the use of bias to potentiate new scientific questions for investigation. While on the other hand you maintain a belief we seem to have in common: question EVERYTHING, especially those in which bias may play a role.

    While I do agree that in science bias is ubiquitous, I think that an understanding of the effects experimental bias on data can ensure proper experimental design and the avoidance of confounding results. The ability to recognize potential sources of bias and understanding how to eliminate them is crucial to the production of "good science".

  5. I disagree that bias causes us to be more critical as scientists. While it is true that biases cause us to question the work of others, this is not usually done in a constructive way. Bias causes people to question research that contradicts their own preconceived notions of how a system works. This unwillingness to listen to unconventional ideas actually keeps science from pushing forward. Although all humans are going to have inherent biases, it is important that we recognize our biases and try to minimize the impact they have on our critique of others' work.

  6. There are many nuances to "bias" and I think that you are interpreting it as its most forgiving definition, that is of a bias being a goal. If we, as scientists, have a goal that we would like to see come into fruition, aka a scientific hypothesis to be proved, then of course we devote the effort required to come to a conclusion, we are critical in our experimental design and analysis, and we want our data to support the attainment of the original goal. But, if you look hard enough you'll always find Waldo. If you go into an experiment with one goal in mind, we are only willing to observe the conclusion that we want. Bias, using the less liberal connotation, is a natural sway of thinking that ultimately might impair our ability to discover the real truth -- that we're in fact wrong.

  7. I think that you are on to something with your blog post. Ad you state, the word "bias" is typically associated with a negative connotation in the scientific community, but many experiments that are performed actually start out due to bias towards one concept or specific organism.

    For example, I have been performing experiments looking at T-cells during an infection, and I think that these cells are important in pathogenesis in my model. I have done quite a large number of in vitro and ex vivo experiments that would support this idea, and I have now started presenting the data to various PIs to get critical feedback prior to submission of a manuscript. I have actually been rather stunned with the amount of bias that I have encountered with regard to an individuals specific field. For example, an innate immunologist told me that even though the data I had were compelling that the innate immune system is likely driving my phenotype. This is a clear example where someone is bias towards what they study even when there was no evidence that this was the case. On the one hand, this bias could be detrimental if a similar individual was to get my paper for review, but on the other, such bias could drive for inviduals to do experiments to better understand the T-cell innate immune interactions in my model.

    In the end, I think that bias is inherent in science, and as you believe, it makes us progress forward. However, it is important to recognize bias in the context of analysis to ensure we are not deceived either on purpose or on accident.