, 3 min read
A trichotomy of intellectual activity
I like to separate intellectual work among three categories:
- Emulation: the reproduction or direct application of existing ideas. Most academic work and maybe most business work falls in this category. You seek the best ideas and you reproduce them, sometimes with minor adaptations. As argued convincing in Zero To One by Peter Thiel, it represents the bulk of what might pass as entrepreneurial activity. In the Social Leap, von Hippel argues that our brain are so large in large part because of the need to deal with our social reality, with its incentives to follow the herd cognitively. We have a strong tendency to emulate, and it is probably a great trait. One an idea starts spreading, it keeps on spreading. Without emulation, good ideas would not spread. We have even constructed entire institutions to support emulation: schools and universities. Kuhn might have called emulation “normal science”.
- Free inquiry is when you set aside what people are doing and you go on your own, trying to ask new questions, find new tools, or apply tools in a new way. You deliberately avoid the taken path. We have orders of magnitude more scholars and researchers than a century ago, but who believes that we have free inquiry than in the Einstein era? In Science Is Getting Less Bang for Its Buck, Collison and Nielsen argue that science has slowed enormously per dollar or hour spent. They would have to acknowledge that the number of research papers and patents has continued on its course, growing exponentially over time. If science is slowing but the output is continuing, then it suggests that most of the work has become emulation. While our institutions like to take credit for “out of the blue” innovations, the case that, for example, the CERN is responsible for the invention of the Web is shaky at best. Rather, our institutions are good at taking credit. There is clear evidence that some societies and cultures are better at free inquiry than others. For example, Jews represent less than 0.2% of the world’s population but they have received 40% of the Nobel prizes in economics. This suggests that the rest of humanity could stand to learn a thing or two about how to have fresh ideas.1. Transfer: bringing abstract ideas in the real world. You may think you know how you would design a COVID-19 vaccine from a DNA data dump, but actually doing it is transfer. You take existing mature ideas and you turn them into a new product or service. While many people assume that once an idea has matured in the abstract, bringing it to bear is easy. Yet transfer is a difficult process. Kealey and Nelson found that ninety per cent of new technology arises from the industrial development of existing technology, not from academic science. Though we had remarkable success with COVID-19 vaccines, we must recognize that they were developed under special circumstances with massive investments in transfer. There are not many more therapies approved by the government every year than there were in the 1950s. In fact, there is even a decline in the number of new therapies for the worst (killer) diseases. The very fact that an emergency (COVID-19) enabled us to act much faster than would have been otherwise possible suggests that much of the ongoing research (cancer, aging, heart disease) is probably happening at a far slower rate than it could if we cared enough. It now seems possible that the technology used to produce a COVID-19 vaccine in weeks could produce cancer vaccines. Why did we need a pandemic to find out that about this great technology and what it can deliver? Meanwhile you learn that archaic paper records submitted by fax hold up real-time COVID-19 data in hospitals: it is 2021 and our hospitals are still unable to send data over the Internet. Many organizations only adopt new ideas and new technologies by emulation: they move once everyone has decided to move.
My expectation is that human beings consistently over-invest in emulation and underinvest in both free inquiry and transfer. Emulation is far easier to manage and scale than free inquiry and transfer. The benefits are most obvious. However, I expect we could evolve faster if we treated more problems the way we treat COVID-19: as true “mission critical” problems.