Single Geniuses vs. Making Everyone a Bit of an Einstein
In the natural sciences today, there is the perception that scientific excellence lives in universities. You succeed in those universities by having thoughts that no one else has had, by establishing how you can do something that no one else can do.
This model of brilliance produces pinpoints of light, bright flashes for all to gaze at and be inspired by. We need these flashes, to be sure.
But the single-genius model is less helpful for fixing most environmental and social problems—the solutions to which often lie not in individual brilliance, but involve catalyzing and coordinating small innovative actions among thousands or even millions of people.
The light bulb was a great invention, but it didn’t change the world until there was a power grid providing electricity to every house. Both the bulb and the grid were brilliant inventions, but we hear a lot more about Thomas Edison (the bulb) than we do about whoever invented the grid (the person is so not-famous I can’t even figure out who it was).
Here’s an environmental example of the same situation from some of my colleagues. Fishery stock assessment and management is a classic realm of sophisticated, advanced science. Rigorous models have tens if not hundreds of parameters, and require Ph.D level scientists to run and interpret.
It’s costly, too: The collection of data on stocks to inform these assessments can run in the hundreds of thousands to millions of dollars. The best assessments use large research vessels and whole teams of university professors and government scientists. These resource-heavy requirements are part of the reason that 95% of the world’s fisheries regularly go un-assessed.
For example, Atlantis is arguably the world’s best stock assessment model, and Beth Fulton, the CSIRO scientist in Australia who developed it, is truly brilliant. The model is a masterpiece of sophistication and complexity and it has had staggering success as far as these kinds of complex models go.
But it’s been applied in 20 marine fisheries globally….of the 15,000+ fisheries that need to be assessed.
To get all fisheries globally on stable footing, we need an infusion of the applied kind of brilliance, too. Capacity limitations in many fisheries will mean they will crash before someone comes around who could apply a model like Atlantis to their management.
There’s a small group of scientists taking a very different approach, in another version of what I see as true brilliance. Jeremy Prince (an academic), Noah Idechong (a Pew Fellow) and Steven Victor (an NGO scientist) are starting in Palau: small, yes, but promising.
Instead of requiring complex, integrated foodweb ecosystem models and large research vessels, they are piloting a method that requires a knife, a ruler and some fishermen. You can also just walk into a fish market and use it.
The trick here is that the science builds on existing data—reams of it, on the life history traits of different species and size at reproductive maturity. So Prince, Idechong and Victor are relying on the brilliance of tens of point-of-light scientists who have come before and done the pure science to define how fish grow and when they become reproductively mature.
The equally brilliant and novel advance here is synthesizing that knowledge and applying it in an entirely different way that’s simple and effective.