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.

Taking Science Public

            As I was reading through the posted articles, two in particular caught my attention, because their topics were near and dear to my interests. I am interested in how the general population interacts with science, scientists, and how this perception can be shaped or warped. The articles posted on Vox and written by Julia Belluz took different angles at examining or negotiating the relationship between the lay and the lab. While I absolutely don’t deny the prevalence of irreproducibility in “science”, I’m not really ready to hop on the hype train like some others who seem happy to disregard the myriad advances which have been made by science despite it apparently being broken. One thing I liked from the articles was the frankness of the interviewee in the Why you can't always believe what you read in scientific journals piece. (S)he spoke candidly about the politics of science, specifically in his last comment, which was tangentially related to irreproducibility or “bad science” but actually highlighted one of the actual problems with science: it’s done by humans. This seems like a far more foundational or central issue, and a more interesting conversation to have. It’s not “peer review” or “good stats” (as someone who is good in lab and terrible at stats, I am herein making the assumption that someone who is as good at stats as I am in lab would find it just as easy to “massage” the data and obtain the answer they desire), it’s that we are prideful, ambitious, and defensive in perfectly normal, human levels.

            I honestly have no segue into what my next thoughts were, but I didn’t want to go on for too long about something that wasn’t really that related to the dialogue we’re trying to have. One thing I will note about Ms.Belluz (herself a decorated science journalist) is that she seems a little quick to redirect the attention away from the individuals who disseminate the majority of these falsehoods or exaggerated claims, the journalists themselves. While I don’t believe it is ethical to continue portraying science to the public as this infallible discipline with participants entirely unfazed by their own human emotions, I also think it is important to think about how we phrase and shape arguments out of what statistics or data we have. The example to which I alluded earlier is a clear instance of presentation dictating the takeaway. Belluz doesn’t say “while it is true that about 30% of cases where specific phrases were used are cases where doctors are using these terms, and it is sometimes unjustified. However, dwarfing the 30% of cases which pertained to doctors, 55% of cases pertained to journalists using these phrases.”, a short paragraph I could write in a manner that seems a little biased in favor of scientists. Instead she begins the paragraph by getting that 55% out in the open, then focuses the remaining paragraph elaborating on the smaller percentage of cases which are perpetrated by doctors, leaving readers with the notion of doctors who “medically overhyping”, not journalists. This is then of course laid to rest with a warning statement addressing the grave danger that is medical overhype. The order in which we present data, the careful phrasing we use, and the overall presentation of specific data all have a significant effect on the takeaway message a reader gets. One question I struggle with after reading some of the articles is: how can we have an honest discussion about the realities of science and how reliable or unreliable studies are, without creating a million tiny Jenny McCarthys? Is the nature of public debate and discussion nuanced enough to handle the realities of scientific research, many of which have been true for centuries? How can the largest proportion of cases, perpetrated by journalists, be policed? Should they be?

Science Issues

As I am beginning to spread my fledgling scientist wings by managing my own projects, generating data, and asking new questions, the discussion of bias is a timely one. The discussion in class and the articles such as Berg’s presented me with the undeniable reality that as a graduate student, I am offered an incredible chance to impact the field of science, and this opportunity comes at a high cost. The need to draw accurate conclusions in research is clear; however, recognition of bias and selecting methods to control or eliminate skewing can be a hazy endeavor. The article “Identifying and Avoiding Bias in Research” provided a clear breakdown of the sources of bias within evidenced based methods of clinical studies, as well as helpful guidelines on how to avoid particular biases. I believe such literature and increased and continued dialogue on the issue of bias is necessary to educate the scientific community and to propel scientific discovery.

Prior to last week, I had never considered the existence of my own scientific philosophy. One aspect of the class presentation and discussion that I found particularly interesting was the implied incorporation of science and moral code. Science culture seems to say that a purist approach is the only way to produce good science. I find that in paradoxical separation and integration, the scientific method and my own moral code corroborate and strengthen each other. Concepts highlighted in class, namely the necessity for honesty and integrity in research, caused me to realize that the seemingly remote worlds of science and my own faith both place utmost importance on the pursuit of truth. Though the realms of my scientific work and constructs of faith do not intersect, my worldview and faith do inform how I live by influencing daily choices of integrity and at times, even how I process information. The high value of truth in my worldview enhances my concern for producing accurate data and conclusions and bolsters my commitment as a steward of science to handle data in a detached, unbiased manner. While possibly unconventional, I believe discussion and awareness  of the role of worldview in science may enhance discovery.

“No doubt those who really founded modern science were usually those whose love of truth exceeded their love of power.”

-          C. S. Lewis, The Abolition of Man

Feeling biased about science bias

Based on these articles, it’s clear that there is a fair amount of concern about the quality of science. At the heart of these concerns is the reproducibility of science data, best outlined by the articles published in ASBMB and the Economist. Both of these articles suggest that 36% of experiments are false positives. Two major concerns about the science process were particularly critiqued by the authors of these articles: the “publish or perish” culture of science careers, as well as the peer review process. Basically, scientists are so anxious to publish, that this decreases the quality and time necessary for decent science to occur. In addition, because the peer review process is ran completely by professional obligation and not monetary motivations, there is little oversight when accepting publications.

I’m going to go ahead and admit now that my personal opinions about these critiques are definitely bias, which I assume most of us feel considering that we are within the scientific community that is being critiqued by these articles. We all like to think that we are trying out best to commit to “good science.” There’s a lot of thought and effort being made into testing valid hypotheses, controlling for all foreseeable variables, etc. But like all humans, scientists may make a mistake. It’s unfair and unreasonable to expect 100% accuracy from science. And I was more prone to agree with the opinions of Hovarth: “Science progresses in subtle degrees, half-truths, and chance.” His argument basically goes with the idea this randomness and irreproducibility is not such a bad thing. Science is a little bit of luck, something that I think we can all agree with. Reproducibility is difficult, and historically speaking, some of the greatest science theories have been borne by chance. I think where the trust needs to lie is that scientists are not purposefully doing “bad science.” When this trust is broken is that point where I will consider “irreproducible data” to be a chronic and urgent problem.  

That being said, yes. There are definite changes that need to be made to ensure the best science continues to be produced. I think that’s why a lot of us are taking statistics. Science research now is very different from science research of the past. Internet has made more information available to us. New technology has completely changed the face of research. And if the public is concerned, then we as scientists need to do our best to strike an acceptable balance between having the freedom to make human mistakes while still delivering the most accurate science possible. I’m curious to see if efforts towards having better funding for reproducing data will provide a viable solution for addressing current concerns. Like most science, I’m sure there will be a fair amount of “trial and error” before we can fix things.