Why? We could just half our resource consumption.
If you believe we can freely choose to do so on a global basis as a preventative measure, you are far more of an optimist than I am.
If you believe that things will get bad enough that we will be forced to do so, you might be more of a pessimist than I am.
There a good reason why magic numbers aren't popular among rationalists. Reducing complex system where you can turn multiple variables to single numbers doesn't help you to understand them.
Yes, if you're tempted to use magic numbers you should just use unknowns with clearly stated support ranges and get a general result. I would rather have this discussion at the level of "let f(m,t) be the fraction of earth's maximum capacity 'm' we can exploit at technology level 't' , let k(x) be the technology level at year 'x', and let p(x) be population at year 'x'. What properties must f(m,t), k(x), and p(x) have to insure that p(x) - f(m,t) > 0 for all x > today()?"
I'm plugging in magic numbers because otherwise I'll be misunderstood even worse. Maybe I'm wrong about that.
If you believe we can freely choose to do so on a global basis as a preventative measure, you are far more of an optimist than I am.
If you believe that things will get bad enough that we will be forced to do so, you might be more of a pessimist than I am.
Compared to freely choose to cut population numbers in half or even further, I think the problem of resource usage seems easier. It's still a hard problem.
But maybe we don't even have to cut energy consumption that much. Solar energy seem to get cheaper by 50% every 7 years. Batteries also seem to impro...
In an unrelated thread, one thing led to another and we got onto the subject of overpopulation and carrying capacity. I think this topic needs a post of its own.
TLDR mathy version:
let f(m,t) be the population that can be supported using the fraction of Earth's theoretical resource limit m we can exploit at technology level t
let t = k(x) be the technology level at year x
let p(x) be population at year x
What conditions must constant m and functions f(m,k(x)), k(x), and p(x) satisfy in order to insure that p(x) - f(m,t) > 0 for all x > today()? What empirical data are relevant to estimating the probability that these conditions are all satisfied?
Long version:
Here I would like to explore the evidence for and against the possibility that the following assertions are true:
Please note: I'm not proposing that the above assertions must be true, only that they have a high enough probability of being correct that they should be taken as seriously as, for example, grey goo:
Predictions about the dangers of nanotech made in the 1980's shown no signs of coming true. Yet, there is no known logical or physical reason why they can't come true, so we don't ignore it. We calibrate how much effort should be put into mitigating the risks of nanotechnology by asking what observations should make us update the likelihood we assign to a grey-goo scenario. We approach mitigation strategies from an engineering mindset rather than a political one.
Shouldn't we hold ourselves to the same standard when discussing population growth and overshoot? Substitute in some other existential risks you take seriously. Which of them have an expectation2 of occuring before a Malthusian Crunch? Which of them have an expectation of occuring after?
Footnotes:
1: By carrying capacity, I mean finite resources such as easily extractable ores, water, air, EM spectrum, and land area. Certain very slowly replenishing resources such as fossil fuels and biodiversity also behave like finite resources on a human timescale. I also include non-finite resources that expand or replenish at a finite rate such as useful plants and animals, potable water, arable land, and breathable air. Technology expands carrying capacity by allowing us to exploit all resource more efficiently (paperless offices, telecommuting, fuel efficiency), open up reserves that were previously not economically feasible to exploit (shale oil, methane clathrates, high-rise buildings, seasteading), and accelerate the renewal of non-finite resources (agriculture, land reclamation projects, toxic waste remediation, desalinization plants).
2: This is a hard question. I'm not asking which catastrophe is the mostly likely to happen ever while holding everything else constant (the possible ones will be tied for 1 and the impossible ones will be tied for 0). I'm asking you to mentally (or physically) draw a set of survival curves, one for each catastrophe, with the x-axis representing time and the y-axis representing fraction of Everett branches where that catastrophe has not yet occured. Now, which curves are the upper bound on the curve representing Malthusian Crunch, and which curves are the lower bound? This is how, in my opinioon (as an aging researcher and biostatistician for whatever that's worth) you think about hazard functions, including those for existential hazards. Keep in mind that some hazard functions change over time because they are conditioned on other events or because they are cyclic in nature. This means that the thing most likely to wipe us out in the next 50 years is not necessarily the same as the thing most likely to wipe us out in the 50 years after that. I don't have a formal answer for how to transform that into optimal allocation of resources between mitigation efforts but that would be the next step.