In 1954, Roger Bannister ran the Miracle Mile.
He was the first man in history to run a mile in under four minutes. His ground speed was 15 mph. That’s about as fast as the average person can full-out sprint.
Today, running a four-minute mile is a standard for competitive middle distance runners. But with no evolution in human biomechanics, how has this feat become so achievable?
Technological advance doesn’t feel like a sufficient explanation. There are very few pieces of equipment: shoes, socks, shorts, shirt, running surface, and measurement equipment. In fact, this explanation isn’t even necessary. In 1964, De Villiers Lampracht ran a 3:59:70 mile… barefoot.
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Improvements in running technique also appear insufficient. I estimate that there are too few strides for a small improvement in technique to affect total running time much.
It could also be explained by the amount of runners in the world. The more people exposed to the sport, the higher the probability that a freak athlete finds themselves a competitive runner.
That last explanation is the strongest in my opinion, but slightly misses the point. This is where protocols come into the picture. My theory is that the training protocol for middle-distance running, which enables people to unlock more of their athletic potential, has 1) improved over time and 2) replicated broadly. This explains why sub-4 minute miles happen far more often now.
The same goes for other technically difficult activities – climbing Mt. Everest, setting high jump records, brewing tasty beers, developing software applications. Improvements to, and replication of, protocols have enabled more and more people to accomplish these activities.
The scale at which we can accomplish difficult things is not simply a function of how many people attempt them. That is a factor, but it’s protocols that improve the “hit rate”. The ‘generative’ dimension [2] of a protocol creates a higher percentage of successful attempts. Protocols systematically overcome bottlenecks in an activity. And over time, protocols are tinkered with and, as I suggested above, “1) improved over time”. In isolation, that wouldn’t matter much. These protocols must also be ‘learnable’ so that they can be, “2) replicated broadly”.
Which brings me to my point about labor mobility. The learnability of protocol makes professional skills like brewing, coding, building, and cooking more fungible. Because learnable protocols replicate broadly, the people that are familiar with them can move their labor between protocolized areas.
[1] https://venkatesh-rao.gitbook.io/summer-of-protocols/ In the paper, “The Unreasonable Sufficiency of Protocols” there are 10 proposed dimensions of sufficiency for protocols, including two mentioned in this article: sufficiently generative and sufficiently learnable. Sufficiently evolvable is also closely related to the subject of this article.
