I’ve never seen a black swan. Until 1697 when Willem de Vlamingh and his group of explorers landed in Australia, no one in the Western world had. They always presumed that black swans didn’t exist because they had no observable evidence to prove otherwise.
The story of the first black swan sighting is an example of the fragility of knowledge; millions of people can make a single observation, but one new observation can disprove it. The black swan theory likely resonates with scientists because scientific discovery depends on falsifiability. The classical model of the scientific method requires one to make a hypothesis and set out to prove it wrong. Although scientists dislike presenting negative data, scientific knowledge is shaped by failed hypotheses.
How we define scientific fact has been on the forefront of my mind during the pandemic. How can we trust a scientific finding if it can be disproven with a single observation, and how do we explain this paradox to non-scientists? The answer, I think, does not lie in biology or chemistry, but philosophy and sociology. I consulted Why Trust Science by Naomi Oreskes to understand how we differentiate between scientific fact and fiction.
In her book, Oreskes reviews the history of science philosophy over the past 200 years and how it shapes our definition of scientific truth today. Oreskes listed five key elements to “prove” that a scientific conclusion is trustworthy: consensus, diversity, method, evidence, and values.
Essentially, a scientific finding can be deemed trustworthy if it is backed by sound evidence obtained using stringent methods that are vetted by a diverse group of scientists. Once scientists within a field collectively agree in the trustworthiness of a particular hypothesis or theory, others can feel comfortable trusting the scientific conclusion as well.
Although the measures of scientific accuracy are the same, the bar to meet them is higher than ever. Today, a diverse group of scientists is required not only for reviewing the data itself, but also for making the initial observations. Collaboration amongst scientists across institutions and fields is no longer lagniappe; it’s essential for gathering the evidence needed to find scientific truths.
A quick look at the literature exemplifies how highly specialized scientific experts come together to solve one scientific question. In 1980, Nobel laureates Aaron Ciechanover, Avram Hershko, and Irwin Rose published two landmark publications in PNAS providing the first description of the ubiquitin-mediated proteasomal degradation process that we know today. Each paper had five authors and about seven figures, each with a single panel of data.
The first listed publication in the most recent edition of Science has more than fifty authors and sixteen figures, each with several panels of data.
A study published in Science in 2008 reported that not only had the number of authors on a single paper grown exponentially in the past thirty years, but the number of collaborations across institutions also substantially increased. Additionally, the more collaborations spanning institutions, the higher the impact of the published study. Diverse collaboration moves research forward and improves it.
In the end, a single scientist may go through life thinking that there are only white swans, but scientists across fields must work together to collect data, searching for the black swan.