Two R&D cultures: Creativity and consistency
As an undergraduate in the 1960s, I was encouraged to read The Two Cultures and the Scientific Revolution by Charles Percy Snow (CP to friends), a British physical chemist and novelist (1905-1980). The book was based on a lecture given at Cambridge in 1959. For context, this was two years after Sputnik and panic over the relative strengths of socialist technocracies vs. traditional democratic debating societies. While the circumstances in the United Kingdom at the time properly disturbed Snow, the title gained more importance than the book. We do like things that come in twos_a binary choice is always convenient for making an argument. I will steal that notion here.
The fact that humanists and scientists/engineers had little to say to each other disturbed Snow. The presumed clash of cultures was an active topic for debate in undergraduate seminars. I have not forgotten it. This was a time when entire college freshman classes were expected to read a single book and debate its implications after arriving on campus, anxious about leaving home. The two cultures debate became entwined with the Cold War and the marvelous freeing of government largess to encourage we science majors to keep going. English and history majors are still complaining.
I am retiring from academic life this summer after 47 years. I use this as an excuse to briefly review a more recent cultural debate within the sciences alone. I am reducing the complexity of academic and industrial science to sharply drawn choices, each of which has taken 50 percent of my time. Reality is more nuanced.
In academic science and engineering, creativity is the dominant research theme. It is what we expect of Ph.D. students and faculty. Something new is our goal, and getting it published is how we reflect success. Early in my career I worried about not being able to achieve this. Much to my delight, I found it relatively easy to do new things in chemistry. The harder objective was to discover something important, something that really mattered.
Five decades later, it is both easier to be novel and harder to have it matter. We have far more channels to disseminate what is new. Measurement tools enable data that CP likely could not have imagined 60 years ago. The number of scientists and engineers exploded with the cold war, and pressure for both funding and notoriety has expanded unsustainably ever since. IT tools do now enable us to find what others have achieved and they can find our gold nuggets.
On the other hand, publications are a very poor source to reveal what matters because most of what matters is not ever published. Instead, it is purchased. The criticism that academic papers are often not reproducible is fair only relative to the puffed-up claims for it. In this culture, weak validation is expected. Through an iterative process, the good stuff rises. The top academic labs slow down a bit and get closer to the truth when they have the resources to do so. This is rare. Validation takes a larger team and a longer time...