An early career scientist's thoughts on mathematics.
E.O. Wilson wrote an essay entitled, “Great Scientist ≠ Good at Math”. If you haven’t read it, here is my summary of E.O. Wilson’s statement:
I didn’t learn much math, and I am a successful scientist because I think critically and found collaborators who were good at math. If you think critically, and find collaborators who are good at mathematics and statistics, you can be a successful scientist without personally knowing much math.
The name of my blog is _math_bionerd. I loved math in high school (thanks Mr. Boerner), and majored in Mathematics in college at Creighton University. I did a summer research experience at the University of Nebraska, Lincoln in the Mathematics department. And, for graduate school, I applied to both Mathematics programs and Bioinformatics programs, ultimately choosing the latter, but volunteering to be a teaching assistant for Calculus. I currently study biological questions and large datasets using computer programs and statistical models. So, uh, yes, I think math is important.
Edward Frenkel has an excellent piece responding to Wilson’s essay. I completely agree with his conclusion:
“It would be fine if Wilson restricted the article to his personal experience, a career path that is obsolete for a modern student of biology. We could then discuss the real question, which is how to improve our math education and to eradicate the fear of mathematics that he is talking about.”
The first thought that struck me, too, about Wilson’s essay is that he is giving antiquated advice to modern students. But, the more I thought about it, I realized that the mark he missed is much larger than that. In any field of scientific research, we can gain more insights by taking a different perspective. This perspective may come from collaborators, but truly successful scientists are able to integrate new opinions, and see their own data in new light. Collaborators are very important, but we should be able to critically assess the contributions of our collaborators. Blindly trusting in a mathematician’s computations is just as foolish as a mathematician unquestioningly accepting the results of a biological experiment. The roots of scientific inquiry are curiosity and skepticism. Curiosity is developed by what we want to discover, but do not yet know. Skepticism occurs when new data are evaluated, within the context of what we know. The two go hand in hand to result in new, exciting, discoveries. But, being curious without being skeptical makes for poor scientific inquiry.
We become scientists because we are curious. While in training, we learn how to be skeptical by increasing our base knowledge. I cannot imagine a point in my career when that training will end. It can be uncomfortable to be a novice, to admit when we don’t understand, and to take the time to learn new material, especially after years of training. But we must, if we are to continue to make progress. This may mean learning more about cardiac disease, or aphid digestion, or polio replication, or linear algebra, or differential equations.
Are there good scientists who are not good at math? Of course there are.
Must one be good at math to be a good scientist? Not necessarily.
But, can anything be gained from perpetuating the notion that math is untouchable, except by experts? No.