People and research taste
Something I've been thinking about recently is the development of research taste. I sometimes consider research taste as a filter problem. This allows us to filter ideas into four categories:
- True negatives: ideas that we expect, when pursued, to be utterly incosequential or actively harmful towards our research agenda.
- False negatives: ideas that are worth exploring in service of our research agenda, but we choose not to pursue.
- False positives: dead ends that we run into, but do not directly contribute towards our research agenda.
- True positives: ideas that are worth exploring in service of our research agenda, which we choose to pursue.
Setting aside the definition of a "research agenda" for now (to be addressed in a later post!), do ideas cleanly fall into these categories?
Imagine you're a theoretical physicist establishing a research agenda in epidemiological dynamics. We can likely assume that that Lie algebras and group theory do not contribute to epidemiology relevant to public health: we can confidently classify these as true negatives.
Perhaps quantum electrodynamics is also irrelevant: after all, how do perturbations and Feynman diagrams factor into virus transmission? But wait! The initial stages of an outbreak determine whether perturbations from a healthy baseline balloon into epidemics. Perhaps perturbation theory can be applied to virus dynamics. And indeed it is.
Here, the distinction between a true and false negative becomes blurred. If one observes an underlying mathematical similarity between two disparate ideas, the cost of modelling this thought is minimal. But how do we spot these patterns of thought?
Daniel Kahneman's Thinking, fast and slow breaks down reasoning into System 1 and System 2. System 1 is intuitive: we instinctively know that 8 times 2 equals 16. Yet System 2 is analytical: most people don't know off the top of their head what 89 times 32 is, but the procedural knowledge of multiplying by the tens and units, carrying the digits, and summing is there.
In an analogous manner, good research taste comes from a good balance of Systems 1 and 2. Intuition should provide a general filter for true negatives. As a student or junior research, this intuition is shaped by your supervisors, advisors, professors, and mentors. During this stage, system 1 can be pulled in many directions, and the student has to discover what filter they're happy with.
In my book, System 2 is built through the Popperian scientific method of conjecture and refutation. We begin to glimpse the superstructure of science, and choose the methods we employ to find new hypotheses and verify them.
Therefore, the development of good research taste consists of a constructing a reliable filter, and picking the right set of tools to investigate the questions that bother you. Most importantly, neither is developed in isolation: Abraham Flexner, in his essay the usefulness of useless knowledge, traces the development of probability theory alongside an attempted rationalisation of gambling. Perhaps your tools aren't suitable for the question at hand, but you can be fairly sure that someone else's tools might be correct.
As a student exploring the intersection of industrial and academic research, this raises the question: how do you maximise this surface of serendipity? My thoughts are as follows:
- Find people whose toolkits are relatively different. Become an expert in the ones that interest you, and read widely: the right problem will appear!
- People advance up the career/academic ladder because of good taste: their mentorship can be incredibly valuable, and completely reshape how you view a problem. This recently happened to me in viral genetics.
- Maintain a research agenda: this prevents unnoticed mission drift, but allows your objectives to evolve over time.
(This is the beginning of a daily 12-minute writing experiment. I often agonise over the precise wording I want to employ in my writing. Whilst this is an important skill, I hope this experiment helps me overcome this anxiety!)