Today’s guest blogger is Abraham Loeb. Avi is the Frank B. Baird Jr. Professor of Science at Harvard University. He serves as chair of the Harvard Astronomy department and director of the Institute for Theory & Computation at the Harvard-Smithsonian Center for Astrophysics. Avi is also the father of two young daughters and is working to make the scientific world a better place by the time they enter university.
Science can only blossom if young researchers are rewarded for acquired skills and growth rather than inherited academic ancestry.
Will a match catch fire when it scratches against the rugged matchbox wall? Knowing the answer is of paramount importance if we want to collect useful matches in our box. One way to find out is to try them all. The only problem with this approach is that by the time we will know the answer, the burnt matches will be of no value. The challenge is how to select useful matches reliably in advance? Putting this challenge into an academic context, how can we select a cohort of promising scientists before they have made their discoveries? This is the fundamental challenge of academic planning. Prestigious universities are plagued by past hirings which led to ‘duds’ or ‘dead wood’, namely faculty who when hired were labeled as geniuses with great promise but in retrospect, decades later, had little impact on the progress of science. At the same time, some of their contemporaries who were not endorsed by prominent scientists and hence moved to faculty positions at lesser schools, carried the day. Without mentioning names, suffice it to say that this is a familiar occurrence. Why is this phenomenon so prevalent?
Senior scientists who serve on promotion, prize, or search committees are often asked to evaluate the promise of their younger colleagues. One would naively expect them to approach this challenge in the same way that they address a scientific problem, namely study all available data and construct a model that extrapolates into the future. In order to avoid biases, it would appear natural to adopt a dynamical model which takes into consideration the special initial conditions of an individual and allows for growth in forecasting the individual’s future. For example, a young researcher who did not benefit from the privilege of being nurtured by top quality mentors or had to transition from a different culture or an inferior socio-economic status, should be given more slack. This is common sense. But is it common practice?
