Innovation and population size

More people means we have the ability to consider solving harder problems

Being alive is solving problems. Everything we do, or don’t do, requires solving a problem of some shape or other… provided that you look at things from a certain point of view.

Some human activities have been around for a long time, we might expect, for example, that building structures out of bricks and stones - being something that we have been doing for thousands of years - we should have encountered all the problems that there are… and maybe we have… except we have forgotten a lot of the solutions: we don’t know how to build the Colosseum in Rome any more… their building techniques are lost to us

The Colosseum in Rome

Now, you may say something like “Ok, but that was built over 2,000 years ago, it’s only reasonable to expect that we might have forgotten a trick or two… and maybe we don’t need those tricks any more”… and you might even be correct… but let’s take a closer example…

A Saturn V rocket launching

We have lost the ability to make Saturn V rockets. Back in 1975 we were able to build them, we still have the technical design documents… but all the little Rocket Engineer’s common knowledge ways of working that nobody writes down, that go into creating each of the engines that make up the Saturn V, were lost once all the Rocket Engineers that knew those things retired and died. Not even 50 years have passed since the last one was made and we cannot make them any more.

So instead we have Elon and others having to re-learn how to solve the problems of launching a rocket into space… and this time they are also adding in being able to mass produce the engines, so we should have a slightly different solution that optimizes for other concerns.

Innovation is solving problems

Elon and Co are solving problems in rockets through innovation. Innovation is a process that involves skill, persistence and a bit of luck.

If you have 10 equally skilled people working on solving a problem:

• the probability that one of the 10 gets “lucky” will be about ten times the probability of just one of them

• the total persistence by all 10 of them will be about ten times as much over a period of time

So, in the average, 10 equally skilled people would be expected to solve a problem about ten times faster than just one of those skilled people.

Now there are other factors that can impact, for example

• If all ten people use the exact same approach to try and solve the problem and make the same mistakes, and so on… well we might have wasted the potential multiplier

• If all ten people are communicating with each other and effectively and efficiently sharing their learnings and optimizing their efforts to reduce duplication we may be able to multiply out the persistence and luck and get a multiplier closer to 100

If you have more people you can solve problems faster

This should come as no surprise, we can be more scientific than that though as we would expect the pace of innovation to thus increase with the population size.

Measuring the amount of innovation is more of an art than a science, but if you look at the kinds of graphs you will see something like this:

Another wild stab in the dark at estimating the pace of innovation

Compare that with the world’s population over the same time period:

The world’s population from 1400 to present

The observant reader might spot the correlation in shape! So our theory, that innovation is proportional to population size, made a prediction and the data agrees!

Now there is another benefit of having more people and being able to solve problems faster…

More people means that harder problems become solvable

Let’s suppose that Space X has their efforts directed by a core group of 10 experts, and let’s say it takes them collectively 7 years to solve a specific hard problem. If there was only one of those experts, it would probably take them 70 years to build up all the knowledge (from mistakes made, etc) to solve the same problem which means they’ll probably be dead as it took them at least 25 years to get enough qualifications to get funding to even start trying to solve the problem.

What that means is that right now the hardest problems we have the ability to solve are approximately ten times harder than the hardest problems we could solve in the 1750’s

If we reduced the global population by a factor of ten, as some Malthusians are advocating, we will be returning our pace of innovation back to the pace of the 1750’s.

And it’s worse than that, in a sense, because if we need to maintain our current technological infrastructure (in order to retain all our learned knowledge) we will need to be tasking the 1/10th as many skilled people at maintenance of that infrastructure and they will not have time for innovation.

• Digital media needs to be refreshed every couple of years or it becomes unreadable

• Computer chips age, and the more powerful the chips the faster the aging

• Fabs to make replacement chips require a high skill set and a large market to justify their cost of production

If we reduce our global population by a factor of ten, within 30 years we will likely have the great digital equivalent in terms of loss of knowledge as the fire of Alexandria had on the Roman world.

The more I think about the relationship between innovation and population size, the more I agree with Elon that we face an underpopulation crisis… and if you consider that even if we set about fulfilling the Malthusians’ wet dreams and reduced the global population by a factor of ten, we’d likely create a lot of hard problems in the process while simultaneously making more of those problems too hard to even consider solving… I guess I don’t buy the Malthusian Kool-aid!