On the first day of DukeEngage Academy, Professor Williams asked us a seemingly simple question: what is science? Dumbfounded, my peers and I sat in silence trying to think of a concrete definition that we could apply to such a broad term. The majority of our cohort is made up of people with STEM majors, and I was sure most of them were overthinking every little intricacy the same way that I was. It wasn’t before long until people began discussing data-driven analysis and spouting off the difference between hard sciences and everything else. Most people were dismissive of the notion that policy-making is a science in its own way, and it was apparent (to me at least) that Professor Williams was biting his tongue while some of my fellow STEM majors were rattling off all of the reasons that “our” science is so much more complicated than policy.
Fast-forward one month, and I was reading a paper for work when I stumbled upon UNESCO’s definition of science:
Science – the enterprise whereby mankind, acting individually or in small or large groups, makes an organized attempt, by means of the objective study of observed phenomena, to discover and master the chain of causalities; bring together in a coordinated form the resultant sub-systems of knowledge by means of systematic reflection and conceptualization, often largely expressed in the symbols of mathematics; and thereby furnishes itself with the opportunity of using, to its own advantage, understanding of the processes and phenomena occurring in nature and society.
It fit the idea I had in my head but was unable to express through words, and it’s just broad enough that you could apply it to pretty much any process that requires rigorous analysis.
As the summer went on and my understanding of the policy world grew, I was able to draw connections between the steps I take in the research lab I work in and the steps that policymakers take here to pass a law. In both cases, your first step is identifying a problem or the question you want to look at. Next, whether it be via applying for grants or seeking election, you put forth your case for why you should be doing this job. You then decide how you would like to generate the data that can inform your conclusions about said issue. In a researcher’s case, your data collection will take place in a lab of some sort, while for policymakers you may speak to constituents directly or analyze census data and other federally collected statistics. Both types of professionals will then utilize their data to draw conclusions. The researcher’s final product, a publication, will undergo scrutiny via the peer-review process. Meanwhile, the policymaker’s final product, a law, must first be scrutinized as a bill in both the house and the senate. Both products will then lead to new questions, setting off a chain reaction that highlights the human desire to understand and improve the world that we live in.
While I did not come into this program with my mind closed off about what science could be, I definitely had some misconceptions about the science vs policy debate. I used to think that anyone who does hard science is probably ‘smart’ enough to do policy, but that it wouldn’t work vice versa. Because of that, my implicit bias used to be that hard sciences required higher levels of intelligence. Not only have I come to realize how subjective the term intelligence is, I have also concluded that it is not fair to value certain skillsets over others. Policy requires an important skill that many scientists are missing, which is the ability to adjust how you communicate depending on who you are speaking to. Scientists, on the other hand, are able to understand physiological mechanisms in a way that many policy makers cannot. Each field requires people to bring very specific skillsets to the table, so policymakers must make up for scientists’ weaknesses and vice versa.
Our enrichment activities have lead me to the conclusion that hard sciences, which are necessary for the innovations that improve our quality of life, would be useless if we did not have policymakers to facilitate the transfer of science to the public. Take the FDA for example, which must deal with the intricacies of bringing life-saving drugs (that were developed via hard science) to the public. Another example is NIST, which must evaluate technological advances and create guidelines to keep our technology uniform and safe for the public. I like to think of science and policy as a mutualistic relationship, and if you lose half of the equation, the other field is ultimately rendered useless. I have learned a lot about how science and policy interact this summer and I am glad that as a scientist, I now better understand the role that policy plays in enabling the efficacy of my work.